Louis BECQUEY / biorseo

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Louis BECQUEY
0b17971f 2 parents ed92d4ff 78f08463

rien^4

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Showing 20 changed files with 2481 additions and 919 deletions
......@@ -23,5 +23,11 @@ results/*
log_of_the_run.sh
logBadDesc.txt
gurobi.log
IL*
HL*
temp/*
# data
data/modules/BGSU/HL/3.2/diagnostic/*
data/modules/BGSU/HL/3.2/lib/*
data/modules/BGSU/IL/3.2/diagnostic/*
data/modules/BGSU/IL/3.2/lib/*
data/modules/DESC/*.desc
\ No newline at end of file
......
......@@ -2,8 +2,6 @@
CPLEXDir="/opt/ibm/ILOG/CPLEX_Studio128"
IEIGEN="/usr/local/include/eigen3"
INUPACK="/usr/local/include/nupack"
jar3dexec="/home/persalteas/Software/jar3dbin/jar3d_2014-12-11.jar"
ILmotifDir="/home/persalteas/Data/RNA/motifs/Matlab_results/IL/3.2/lib"
HLmotifDir="/home/persalteas/Data/RNA/motifs/Matlab_results/HL/3.2/lib"
descfolder="/home/persalteas/Data/RNA/motifs/Rna3Dmotif/No_Redondance_DESC/"
bypdir="/home/persalteas/Software/BayesPairing/bayespairing/src"
biorseoDir="/nhome/siniac/lbecquey/Software/biorseo"
jar3dexec="/nhome/siniac/lbecquey/Software/jar3dbin/jar3d_2014-12-11.jar"
bypdir="/nhome/siniac/lbecquey/Software/BayesPairing/bayespairing/src"
......
This is a bi-objective integer programming algorithm.
It predicts the secondary structure of a RNA sequence with pieces of 3D information (non-canonical contacts) at some places,
by identifying zones that can fold like known motifs from the RNA 3D Motif Atlas.
Biorseo (Bi-Objective RNA Structure Efficient Optimizer)
===================================
This tool predicts the secondary structure of a RNA sequence with pieces of 3D information (non-canonical contacts) at some places,
by identifying zones that can fold like known modules from data like the RNA 3D Motif Atlas or Rna3Dmotifs.
Contact : louis.becquey@univ-evry.fr
1/ How it works
===================================
......@@ -8,24 +12,123 @@ INPUT:
- An RNA sequence (tested with sequences ~100 bases)
THEN
- Identifies possible 2D folds with RNAsubopt.
- Knowing possible 2D folds, locate every possibly unpaired loop (hairpin loop, internal loop, multiple loop...)
- align each unpaired loop to the catalogue of models of known RNA motifs (The 3D Motif Atlas of the BGSU RNA group)
- retrieve a list of potential motif-insertion-sites in the RNA sequence. Use them to define the constraints for the IP problem.
- Solve a bi-objective IP problem:
* Maximize the expected accuracy of the secondary structure,
* Maximize the number and size of motifs inserted in the structure.
- **Pattern-matching step** : Find all possible occurrences of known RNAmodules in the query sequence, by finding subsequences of the querythat score well with the probabilistic models of the modules (like JAR3D, or BayesPairing)
- **Constraints definition step** : Define constraints on the secondary structure imposed by modules if they would be included (in this case, some of the canonical base-pairs are forbidden)
- **Solve a bi-objective IP problem** : Find a secondary structure that satisfies as much as possible both the expected accuracy of the structure and a criterion taking into account module inclusions, by solving a bi-objective integer linear programming problem, using the previous constraints defined in the previous step.
OUTPUT:
- A set of secondary structures from the pareto front,
- The list of known motif inserted in the corresponding structures (and the non-canonical contacts)
- (lower score structures from k-Pareto sets, not implemented yet.)
- A set of secondary structures from the Pareto front,
- The list of known modules inserted inplace in the corresponding structures
2/ The different models
==================================
MODULE SOURCES
Biorseo can be used with two modules datasets (yet):
* Rna3Dmotifs (from the work of *Djelloul & Denise, 2008*), but with the 3D data of 2018
* The RNA 3D Motif Atlas of BGSU's RNA lab (*Petrov et al, 2013*, see http://rna.bgsu.edu/rna3dhub/motifs/)
* RNA-Bricks 2 or CaRNAval could theoretically be used, but are not supported (yet). You might write your own API.
2/ Installation
PATTERN MATCHING STEP
- Use **simple pattern matching**. Rna3Dmotifs modules are available with sequence information. We use regular expressions to find those known loops in your query. This is the approach of RNA-MoIP (*Reinharz et al, 2012*), we deal the same way with short components and wildcards.
- Use **JAR3D**. The RNA 3D Motif Atlas modules can be scored against a given loop sequence by an hybrid SCFG/MRF method (*Zirbel et al, 2015*). This first requires to identify potential loops, which is achieved by a run of RNAsubopt first.
- Use **Bayesian networks with BayesPairing**. To accurately model probability dependancies between nucleotides, one can use BayesPairing to build bayesian networks of the modules (the RNA 3D Motif Atlas and Rna3Dmotifs are both supported). Then, sequences are sampled with the Bayesian network of a module, and we use regular expressions to find them in your query.
OBJECTIVE FUNCTIONS FOR THE MODULE INSERTION CRITERIA
* **Function A** : weights a module by its squared number of nucleotides (like RNA-MoIP).
* **Function B** : weights a module by its number of components (strands) and penalizes it by the log^(_2) of its nucleotide size.
* **Function C** : weights a module by its insertion site score (JAR3D or BayesPairing score).
* **Function D** : weights a module by its number of components (strands) and insertion site score (JAR3D or BayesPairing score), and penalizes it by the log^(_2) of its nucleotide size.
3/ Recommended uses
==================================
- Download and install RNAsubopt from the ViennaRNA package (https://www.tbi.univie.ac.at/RNA/)
- Download and install IBM ILOG Cplex optimization studio (https://www.ibm.com/analytics/cplex-optimizer), free academic account required
- If **you know you have no pseudoknot**:
* Benchmarks show Biorseo does not perform better than simpler tools like RNAsubopt alone. Please use RNAsubopt (ViennaRNA package) or Fold (RNAstructure package).
- If you **might expect a pseudoknot, or don't know**:
* The most promising method is the use of direct pattern matching with Rna3Dmotifs and function B. But this method is sometimes subject to combinatorial explosion issues. If you have a long RNA or a large number of loops, don't use it. Example:
`./bin/biorseo -s PDB_00304.fa --descfolder ./data/modules/DESC --type B -o PDB_00304.rawB `
* The use of the RNA 3D Motif Atlas placed by JAR3D and scored with function B is not subject to combinatorial issues, but performs a bit worse. It also returns less solutions. Example:
`./bin/biorseo -s PDB_00304.fa --jar3dcsv PDB_00304.sites.csv --type B -o PDB_00304.jar3dB`
4/ Installation
==================================
### DEPENDENCIES
- Make sure you have Python 3.5+, Cmake, and a C++ compiler installed on your distribution.
- Install automake and libboost-filesystem.
- Download and install [IBM ILOG Cplex optimization studio](https://www.ibm.com/analytics/cplex-optimizer), an academic account is required. The free version is too limited, you must register as academic. This is also free.
- Download and install Eigen: Get the latest Eigen archive from http://eigen.tuxfamily.org. Unpack it, and install it.
```bash
wget http://bitbucket.org/eigen/eigen/get/3.3.7.tar.gz -O eigen_src.tar.gz
tar -xf eigen_src.tar.gz
cd eigen-eigen-323c052e1731
mkdir build
cd build
cmake ..
sudo make install
```
- Download and install NUPACK: Register on [Nupack's website](http://www.nupack.org/downloads/source), download the source, unpack it, build it, and install it:
```bash
wget http://www.nupack.org/downloads/serve_file/nupack3.2.2.tar.gz
tar -xf nupack3.2.2.tar.gz
cd nupack3.2.2
mkdir build
cd build
cmake ..
make -j4
sudo make install
```
### OPTIONAL DEPENDENCIES FOR USE OF JAR3D
- Download and install RNAsubopt from the [ViennaRNA package](https://www.tbi.univie.ac.at/RNA/).
- Download and install Java runtime (Tested with Java 10)
- Download and install the latest JAR3D executable "jar3d_releasedate.jar" and motif models in this folder (http://rna.bgsu.edu/data/jar3d/models/)
Note that for HL and ILs, only the latest version is required (not all the versions provided in the folders).
- Download and install a C++ compiler and building dependencies and utilities (g++ or clang, automake, libboost)
- Download the latest JAR3D executable "*jar3d_releasedate.jar*", and latest IL and HL models from [here](http://rna.bgsu.edu/data/jar3d/models/).
Note that only the latest version is required (not all the versions provided in the folders).
### OPTIONAL DEPENDENCIES FOR USE OF BAYESPAIRING
- Download and install RNAfold from the [ViennaRNA package](https://www.tbi.univie.ac.at/RNA/).
- Make sure you have Python 3.5+ with packages networkx, numpy, regex, wrapt and biopython
- Clone the latest BayesPairing Git repo, and install it :
```
git clone http://jwgitlab.cs.mcgill.ca/sarrazin/rnabayespairing.git BayesPairing
cd BayesPairing
pip install .
```
### RNA3DMOTIFS DATA
If you use Rna3Dmotifs, you need to get RNA-MoIP's .DESC dataset: download it from [GitHub](https://github.com/McGill-CSB/RNAMoIP/blob/master/CATALOGUE.tgz). Put all the .desc from the `Non_Redundant_DESC` folder into `./data/modules/DESC`. Otherwise, you also can run Rna3Dmotifs' `catalog` program to get your own DESC modules collection from updated 3D data (download [Rna3Dmotifs](https://rna3dmotif.lri.fr/Rna3Dmotif.tgz)). You also need to move the final DESC files into `./data/modules/DESC`.
### THE RNA 3D MOTIF ATLAS DATA
If not done during the installation of JAR3D, get the latest version of the HL and IL module models from the [BGSU website](http://rna.bgsu.edu/data/jar3d/models/) and extract the Zip files. Put the HL and IL folders into `./data/modules/BGSU`.
### BUILDING
* Clone this git repository : `git clone https://github.com/persalteas/biorseo.git` and `cd biorseo`.
* Edit the file `EditMe` to set the paths of the above dependencies and data. Fileds that you will not use can be ignored (ex: bypdir if you do not use BayesPairing). Example of my setup:
* CPLEXDir="/opt/ibm/ILOG/CPLEX_Studio128_Student"
* IEIGEN="/usr/local/include/eigen3"
* INUPACK="/usr/local/include/nupack"
* jar3dexec="/nhome/siniac/lbecquey/Software/jar3dbin/jar3d_2014-12-11.jar"
* ILmotifDir="/nhome/siniac/lbecquey/Data/RNA/motifs/BGSU/Matlab_results/IL/3.2/lib"
* HLmotifDir="/nhome/siniac/lbecquey/Data/RNA/motifs/BGSU/Matlab_results/HL/3.2/lib"
* descfolder="/nhome/siniac/lbecquey/Data/RNA/motifs/Rna3Dmotifs/No_Redondance_DESC/"
* bypdir="/nhome/siniac/lbecquey/Software/BayesPairing/bayespairing/src"
* biorseoDir="/nhome/siniac/lbecquey/Software/biorseo"
* You might want to edit `Makefile` if you are not using clang as compiler. For example, if you use g++, replace clang++ by g++.
* Build it: `make -j4`
* The working executable file is `./bin/biorseo`.
### BAYESPAIRING USERS: PREPARE BAYESIAN NETWORKS
We run an example job for it to build the bayesian networks of our modules.
```
cd rnabayespairing/src
python3 parse_sequences.py -d rna3dmotif -seq ACACGGGGUAAGAGCUGAACGCAUCUAAGCUCGAAACCCACUUGGAAAAGAGACACCGCCGAGGUCCCGCGUACAAGACGCGGUCGAUAGACUCGGGGUGUGCGCGUCGAGGUAACGAGACGUUAAGCCCACGAGCACUAACAGACCAAAGCCAUCAU -ss ".................................................................((...............)xxxx(...................................................)xxx).............."
```
Use `-d rna3dmotif` or `-d 3dmotifatlas` depending on the module source you are planning to use.
This is a quite long step, but the bayesian networks will be ready for all the future uses.
......
>E.coli_alpha_operon_mRNA
UGUGCGUUUCCAUUUGAGUAUCCUGAAAACGGGCUUUUCAGCAUGGAACGUACAUAUUAAAUAGUAGGAGUGCAUAGUGGCCCGUAUAGCAGGCAUUAACAUUCCUGA
(((((((.(((((........[[[[....[[[[....{{{{.))))))))))))..........................]]]].....]]]]...........}}}}
\ No newline at end of file
>E.coli_alpha_operon_mRNA
UGUGCGUUUCCAUUUGAGUAUCCUGAAAACGGGCUUUUCAGCAUGGAACGUACAUAUUAAAUAGUAGGAGUGCAUAGUGGCCCGUAUAGCAGGCAUUAACAUUCCUGA
E.coli_alpha_operon_mRNA
UGUGCGUUUCCAUUUGAGUAUCCUGAAAACGGGCUUUUCAGCAUGGAACGUACAUAUUAAAUAGUAGGAGUGCAUAGUGGCCCGUAUAGCAGGCAUUAACAUUCCUGA
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(((((((.(((((........[[[[....[[[[....{{{{.))))))))))))..........................]]]].....]]]]...........}}}}
E.coli_alpha_operon_mRNA
UGUGCGUUUCCAUUUGAGUAUCCUGAAAACGGGCUUUUCAGCAUGGAACGUACAUAUUAAAUAGUAGGAGUGCAUAGUGGCCCGUAUAGCAGGCAUUAACAUUCCUGA
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((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1YIT.0.13 + 2BTE.E.3 + 2V49.A.72 + 2Z4N.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZE.A.89 + 3IZF.A.191 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1JZX.A.84 + 1YIT.0.13 + 2BTE.E.3 + 2V49.A.72 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1YIT.0.13 + 2BTE.E.3 + 2V49.A.72 + 2Z4N.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1YIT.0.13 + 2BTE.E.3 + 2V49.A.72 + 2Z4N.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZF.A.191 + 3O58.1.74 + 3O58.1.74 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1YIT.0.13 + 2BTE.E.3 + 2Z4N.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 + 3PYO.A.85 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1JZX.A.84 + 1YIT.0.13 + 2BTE.E.3 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 + 3PYO.A.85 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1YIT.0.13 + 2BTE.E.3 + 2Z4N.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 + 3PYO.A.85 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1YIT.0.13 + 2BTE.E.3 + 2Z4N.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZF.A.191 + 3O58.1.74 + 3O58.1.74 + 3PYO.A.85 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1YIT.0.13 + 2BTE.E.3 + 2V49.A.72 + 2Z4N.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1YIT.0.13 + 2BTE.E.3 + 2V49.A.72 + 2Z4N.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 6.5590302 27.7426287
((.((((.((.((((.((...((((....))))...)).)).)).)))))).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1YIT.0.13 + 2BTE.E.3 + 2Z4N.B.71 + 3IZ9.A.80 + 3IZF.A.191 + 3O58.1.74 + 3O58.1.74 + 3PYO.A.85 6.5590302 27.7426287
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2VHN.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 + 3PYO.A.85 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2V49.A.72 + 2VHN.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZE.A.89 + 3IZF.A.191 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2V49.A.72 + 2VHN.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZE.A.89 + 3IZF.A.191 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2VHN.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 + 3PYO.A.85 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2VHN.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZE.A.89 + 3IZF.A.191 + 3PYO.A.85 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2V49.A.72 + 2VHN.B.71 + 3IZ9.A.80 + 3IZF.A.191 + 3O58.1.74 + 3O58.1.74 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2V49.A.72 + 2VHN.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZF.A.191 + 3O58.1.74 + 3O58.1.74 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2V49.A.72 + 2VHN.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2V49.A.72 + 2VHN.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2VHN.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 + 3PYO.A.85 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2V49.A.72 + 2VHN.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2VHN.B.71 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 + 3PYO.A.85 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2V49.A.72 + 2VHN.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZE.A.89 + 3IZF.A.191 + 3O58.1.74 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2VHN.B.71 + 3IZ9.A.196 + 3IZ9.A.80 + 3IZF.A.191 + 3O58.1.74 + 3O58.1.74 + 3PYO.A.85 7.5724746 24.6241106
((.((.((..(((((.((...((........))...)).)).))).)).)).))(((...))).((.((.((..((.((.((.((...)).)))).)).)).)).)). + 1F1T.A.4 + 1FKA.A.92 + 1YIT.0.13 + 2BTE.E.3 + 2OM7.B.1 + 2VHN.B.71 + 3IZ9.A.80 + 3IZF.A.191 + 3O58.1.74 + 3O58.1.74 + 3PYO.A.85 7.5724746 24.6241106
This file is too large to display.
#!/usr/bin/python3
# coding=utf-8
import sys
import getopt
from scipy import stats
import subprocess
from os import path, makedirs, getcwd, chdir, devnull
import matplotlib.pyplot as plt
from matplotlib import colors
from math import sqrt
from multiprocessing import Pool, cpu_count, Manager
import multiprocessing
import ast
# ================== DEFINITION OF THE PATHS ==============================
# Retrieve Paths from file EditMe
jar3dexec = ""
bypdir = ""
biorseoDir = "."
exec(compile(open(biorseoDir+"/EditMe").read(), '', 'exec'))
runDir = path.dirname(path.realpath(__file__))
outputDir = biorseoDir + "/results/"
HLmotifDir = biorseoDir + "/data/modules/BGSU/HL/3.2/lib"
ILmotifDir = biorseoDir + "/data/modules/BGSU/IL/3.2/lib"
descfolder = biorseoDir + "/data/modules/DESC"
# ================== CLASSES AND FUNCTIONS ================================
class NoDaemonProcess(multiprocessing.Process):
@property
def daemon(self):
return False
@daemon.setter
def daemon(self, value):
pass
class NoDaemonContext(type(multiprocessing.get_context())):
Process = NoDaemonProcess
# We sub-class multiprocessing.pool.Pool instead of multiprocessing.Pool
# because the latter is only a wrapper function, not a proper class.
class MyPool(multiprocessing.pool.Pool):
def __init__(self, *args, **kwargs):
kwargs['context'] = NoDaemonContext()
super(MyPool, self).__init__(*args, **kwargs)
class Loop:
def __init__(self, header, subsequence, looptype, position):
self.header = header
self.seq = subsequence
self.type = looptype
self.position = position
def get_header(self):
return self.header
def subsequence(self):
return self.seq
class InsertionSite:
def __init__(self, loop, csv_line):
# BEWARE : jar3d csv output is crap because of java's locale settings.
# On french OSes, it uses commas to delimit the fields AND as floating point delimiters !!
# Parse with caution, and check what the csv output files look like on your system...
info = csv_line.split(',')
self.loop = loop # the Loop object that has been searched with jar3d
# position of the loop's components, so the motif's ones, in the query sequence.
self.position = loop.position
# Motif model identifier of the RNA 3D Motif Atlas
self.atlas_id = info[2]
# alignment score of the subsequence to the motif model
self.score = int(float(info[4]))
# should the motif model be inverted to fit the sequence ?
self.rotation = int(info[-2])
def __lt__(self, other):
return self.score < other.score
def __gt__(self, other):
return self.score > other.score
class Job:
def __init__(self, command=[], function=None, args=[], how_many_in_parallel=0, priority=1, timeout=None, checkFunc=None, checkArgs=[]):
self.cmd_ = command
self.func_ = function
self.args_ = args
self.checkFunc_ = checkFunc
self.checkArgs_ = checkArgs
self.priority_ = priority
self.timeout_ = timeout
if not how_many_in_parallel:
self.nthreads = cpu_count()
elif how_many_in_parallel == -1:
self.nthreads = cpu_count() - 1
else:
self.nthreads = how_many_in_parallel
class BiorseoInstance:
def __init__(self, argv):
# set default options
self.type = "dpm"
self.modules = "desc"
self.func = 'B'
self.outputf = outputDir
self.jobcount = 0
# Parse options
try:
opts, args = getopt.getopt(
argv, "hil::o:", ["type=", "func=", "modules="])
except getopt.GetoptError:
print("Please provide arguments !")
sys.exit(2)
for opt, arg in opts:
if opt == "-h":
print("biorseo.py -i myRNA.fa -o myRNA.jar3dB --type jar3d --func B")
sys.exit()
elif opt == "-i":
self.inputfile = arg
self.mode = 0 # single sequence mode
elif opt == "-l":
self.inputfile = arg
self.mode = 1 # batch mode
elif opt == "-o":
self.outputf = arg # output file or folder...
elif opt == "--func":
if arg in ['A', 'B', 'C', 'D']:
self.func = arg
else:
raise "Unknown scoring function " + arg
elif opt == "--type":
if arg in ['dpm', 'jar3d', 'byp']:
self.type = arg
else:
raise "Unknown pattern matching method " + arg
elif opt == "--modules":
if arg in ['desc', 'bgsu']:
self.modules = arg
else:
raise "Unsupported module model type " + arg
else:
raise "Unknown option " + opt
if self.mode:
# Create a job manager
self.manager = Manager()
self.running_stats = self.manager.list()
self.running_stats.append(0) # n_launched
self.running_stats.append(0) # n_finished
self.running_stats.append(0) # n_skipped
self.fails = self.manager.list()
# Create the output folder
subprocess.call(["mkdir", "-p", self.outputf])
def enumerate_loops(self, s):
def resort(unclosedLoops):
loops.insert(len(loops)-1-unclosedLoops, loops[-1])
loops.pop(-1)
opened = []
openingStart = []
closingStart = []
loops = []
loopsUnclosed = 0
consecutiveOpenings = []
if s[0] == '(':
consecutiveOpenings.append(1)
consecutiveClosings = 0
lastclosed = -1
previous = ''
for i in range(len(s)):
# If we arrive on an unpaired segment
if s[i] == '.':
if previous == '(':
openingStart.append(i-1)
if previous == ')':
closingStart.append(i-1)
# Opening basepair
if s[i] == '(':
if previous == '(':
consecutiveOpenings[-1] += 1
else:
consecutiveOpenings.append(1)
if previous == ')':
closingStart.append(i-1)
# We have something like (...(
if len(openingStart) and openingStart[-1] == opened[-1]:
# Create a new loop starting with this component.
loops.append([(openingStart[-1], i)])
openingStart.pop(-1)
loopsUnclosed += 1
# We have something like )...( or even )(
if len(closingStart) and closingStart[-1] == lastclosed:
# Append a component to existing multiloop
loops[-1].append((closingStart[-1], i))
closingStart.pop(-1)
opened.append(i)
# Closing basepair
if s[i] == ')':
if previous == ')':
consecutiveClosings += 1
else:
consecutiveClosings = 1
# This is not supposed to happen in real data, but whatever.
if previous == '(':
openingStart.append(i-1)
# We have something like (...) or ()
if len(openingStart) and openingStart[-1] == opened[-1]:
# Create a new loop, and save it as already closed (HL)
loops.append([(openingStart[-1], i)])
openingStart.pop(-1)
resort(loopsUnclosed)
# We have something like )...)
if len(closingStart) and closingStart[-1] == lastclosed:
# Append a component to existing multiloop and close it.
loops[-1].append((closingStart[-1], i))
closingStart.pop(-1)
loopsUnclosed -= 1
resort(loopsUnclosed)
if i+1 < len(s):
if s[i+1] != ')': # We are on something like: ).
# an openingStart has not been correctly detected, like in ...((((((...)))...)))
if consecutiveClosings < consecutiveOpenings[-1]:
# Create a new loop (uncompleted)
loops.append([(opened[-2], opened[-1])])
loopsUnclosed += 1
# We just completed an HL+stem, like ...(((...))).., we can forget its info
if consecutiveClosings == consecutiveOpenings[-1]:
consecutiveClosings = 0
consecutiveOpenings.pop(-1)
else: # There are still several basepairs to remember, forget only the processed ones, keep the others
consecutiveOpenings[-1] -= consecutiveClosings
consecutiveClosings = 0
else: # We are on something like: ))
# we are on an closingStart that cannot be correctly detected, like in ...(((...(((...))))))
if consecutiveClosings == consecutiveOpenings[-1]:
# Append a component to the uncomplete loop and close it.
loops[-1].append((i, i+1))
loopsUnclosed -= 1
resort(loopsUnclosed)
# Forget the info about the processed stem.
consecutiveClosings = 0
consecutiveOpenings.pop(-1)
opened.pop(-1)
lastclosed = i
previous = s[i]
# print(i,"=",s[i],"\t", "consec. Op=", consecutiveOpenings,"Cl=",consecutiveClosings)
return(loops)
def launch_JAR3D_worker(self, loop):
# write motif to a file
newpath = getcwd()+'/'+loop.header[1:]
if not path.exists(newpath):
makedirs(newpath)
chdir(newpath)
filename = loop.header[1:]+".fasta"
fasta = open(filename, 'w')
fasta.write('>'+loop.get_header()+'\n'+loop.subsequence()+'\n')
fasta.close()
# Launch Jar3D on it
if loop.type == 'h':
cmd = ["java", "-jar", jar3dexec, filename, HLmotifDir+"/all.txt",
loop.header[1:]+".HLloop.csv", loop.header[1:]+".HLseq.csv"]
else:
cmd = ["java", "-jar", jar3dexec, filename, ILmotifDir+"/all.txt",
loop.header[1:]+".ILloop.csv", loop.header[1:]+".ILseq.csv"]
nowhere = open(devnull, 'w')
logfile = open("log_of_the_run.sh", 'a')
logfile.write(' '.join(cmd))
logfile.write("\n")
logfile.close()
subprocess.call(cmd, stdout=nowhere)
nowhere.close()
# Retrieve results
insertion_sites = []
if loop.type == 'h':
capstype = "HL"
else:
capstype = "IL"
csv = open(loop.header[1:]+".%sseq.csv" % capstype, 'r')
l = csv.readline()
while l:
if "true" in l:
insertion_sites.append(InsertionSite(loop, l))
l = csv.readline()
csv.close()
# Cleaning
chdir("..")
subprocess.call(["rm", "-r", loop.header[1:]])
return insertion_sites
def launch_JAR3D(self, seq_, basename):
rnasubopt_preds = []
# Extracting probable loops from RNA-subopt structures
rna = open(outputDir + basename + ".subopt", "r")
lines = rna.readlines()
rna.close()
for i in range(2, len(lines)):
ss = lines[i].split(' ')[0]
if ss not in rnasubopt_preds:
rnasubopt_preds.append(ss)
HLs = []
ILs = []
for ss in rnasubopt_preds:
loop_candidates = self.enumerate_loops(ss)
for loop_candidate in loop_candidates:
if len(loop_candidate) == 1 and loop_candidate not in HLs:
HLs.append(loop_candidate)
if len(loop_candidate) == 2 and loop_candidate not in ILs:
ILs.append(loop_candidate)
# Retrieve subsequences corresponding to the possible loops
loops = []
for i, l in enumerate(HLs):
loops.append(
Loop(">HL%d" % (i+1), seq_[l[0][0]-1:l[0][1]], "h", l))
for i, l in enumerate(ILs):
loops.append(
Loop(">IL%d" % (i+1), seq_[l[0][0]-1:l[0][1]]+'*'+seq_[l[1][0]-1:l[1][1]], "i", l))
# Scanning loop subsequences against motif database
pool = MyPool(processes=cpu_count())
insertion_sites = [x for y in pool.map(
self.launch_JAR3D_worker, loops) for x in y]
insertion_sites.sort(reverse=True)
# Writing results to CSV file
c = 0
resultsfile = open(outputDir+basename+".sites.csv", "w")
resultsfile.write("Motif,Rotation,Score,Start1,End1,Start2,End2\n")
for site in insertion_sites:
if site.score > 10:
c += 1
string = "FOUND with score %d:\t\t possible insertion of motif " % site.score + site.atlas_id
if site.rotation:
string += " (reversed)"
string += (" on " + site.loop.get_header() + " at positions")
resultsfile.write(site.atlas_id+',' +
str(bool(site.rotation))+",%d" % site.score+',')
positions = [','.join([str(y) for y in x]) for x in site.position]
if len(positions) == 1:
positions.append("-,-")
resultsfile.write(','.join(positions)+'\n')
resultsfile.close()
def launch_BayesPairing(self, module_type, seq_, header_, basename):
chdir(bypdir)
cmd = ["python3", "parse_sequences.py", "-seq", outputDir +
basename + ".fa", "-d", module_type, "-interm", "1"]
logfile = open("log_of_the_run.sh", 'a')
logfile.write(" ".join(cmd))
logfile.write("\n")
logfile.close()
out = subprocess.check_output(cmd).decode('utf-8')
BypLog = out.split('\n')
idx = 0
l = BypLog[idx]
while l[:3] != "PUR":
idx += 1
l = BypLog[idx]
insertion_sites = [x for x in ast.literal_eval(l.split(":")[1][1:])]
if module_type == "rna3dmotif":
rna = open(outputDir + basename + ".byp.csv", "w")
else:
rna = open(outputDir + basename + ".bgsubyp.csv", "w")
rna.write("Motif,Score,Start1,End1,Start2,End2...\n")
for i, module in enumerate(insertion_sites):
if len(module):
for (score, positions, sequence) in zip(*[iter(module)]*3):
pos = []
q = -2
for p in positions:
if p-q > 1:
pos.append(q)
pos.append(p)
q = p
pos.append(q)
rna.write(module_type+str(i)+','+str(int(score)))
for (p, q) in zip(*[iter(pos[1:])]*2):
if q > p:
rna.write(','+str(p)+','+str(q))
rna.write('\n')
rna.close()
def execute_job(self, j):
if j.checkFunc_ is not None:
if j.checkFunc_(*j.checkArgs_):
self.running_stats[2] += 1
print("["+str(self.running_stats[0]+self.running_stats[2]) +
'/'+str(self.jobcount)+"]\tSkipping a finished job")
return 0
self.running_stats[0] += 1
if len(j.cmd_):
logfile = open("log_of_the_run.sh", 'a')
logfile.write(" ".join(j.cmd_))
logfile.write("\n")
logfile.close()
print("["+str(self.running_stats[0]+self.running_stats[2]) +
'/'+str(self.jobcount)+"]\t"+" ".join(j.cmd_))
r = subprocess.call(j.cmd_, timeout=j.timeout_)
elif j.func_ is not None:
print("["+str(self.running_stats[0]+self.running_stats[2])+'/'+str(self.jobcount) +
"]\t"+j.func_.__name__+'('+", ".join([a for a in j.args_])+')')
try:
r = j.func_(*j.args_)
except:
r = 1
pass
if r:
self.fails.append(j)
self.running_stats[1] += 1
return r
def check_result_existence(self, datatype, method, function, with_PK, basename):
folder = self.outputf+"PK/" if with_PK else self.outputf+"noPK/"
if datatype == "bgsu":
if method == "jar3d":
extension = ".jar3d"
elif method == "byp":
extension = ".bgsubyp"
else:
raise "Unknown method !"
elif datatype == "desc":
if method == "dpm":
extension = ".raw"
elif method == "byp":
extension = ".byp"
else:
raise "Unknown method !"
else:
raise "Unknown data type !"
return path.isfile(folder + basename + extension + function)
def check_csv_existence(self, datatype, method, basename):
if datatype == "bgsu":
if method == "jar3d":
extension = ".sites.csv"
elif method == "byp":
extension = ".bgsubyp.csv"
else:
raise "Unknown method !"
elif datatype == "desc":
if method == "byp":
extension = ".byp.csv"
else:
raise "You cannot use " + method + " with " + datatype + " data !"
else:
raise "Unknown data type !"
return path.isfile(self.outputf + basename + extension)
if __name__ == "__main__":
BiorseoInstance(sys.argv)
......@@ -8,7 +8,7 @@
#include <string>
#include <vector>
using Eigen::MatrixXf, Eigen::Matrix;
using Eigen::MatrixXf;
using std::map;
using std::pair;
using std::string;
......
>>__'BRANCHPOINT_HELIX_FROM_YEAST_AND_BINDING_SITE_FOR_PHAGE_GA/MS2_COAT_PROTEINS,_NMR,_12_STRUCTURES_'_(PDB_00002)
GGCGUAAGGAUUACCUAUGCC
(((((.(((....))))))))
>>__'LOOP_D/LOOP_E_ARM_OF_E._COLI_5S_RRNA,_NMR,_9_STRUCTURES_'_(PDB_00004)
GGCCGAUGGUAGUGUGGGGUCUCCCCAUGCGAGAGUAGGCC
(((((((((((((((((((...)))))))))))))))))))
>>__'NMR_STRUCTURE_OF_A_CLASSICAL_PSEUDOKNOT:_INTERPLAY_OF_SINGLE-AND_DOUBLE-STRANDED_RNA,_24_STRUCTURES_'_(PDB_00005)
GGGAGCUCAACUCUCCCCCCCUUUUCCGAGGGUCAUCGGAACCA
(((((.......)))))[[[...((((((]]]...))))))...
>>__'SOLUTION_STRUCTURE_OF_A_SUBSTRATE_FOR_THE_ARCHAEAL_PRE-TRNA_SPLICING_ENDONUCLEASES:_THE_BULGE-HELIX-BULGE_MOTIF,_NMR,_12_STRUCTURES_'_(PDB_00006)
GGGUGACUCCAGAGGUCGAGAGACCGGAGAUAUCACCC
((((((((((...((((....))))))))...))))))
>>__'UGAA_EUKARYOTIC_RIBOSOMAL_RNA_TETRALOOP,_NMR,_13_STRUCTURES_'_(PDB_00007)
GGUGUGAACACC
((((....))))
>>__'HIV-2_TAR-ARGININAMIDE_COMPLEX,_NMR,_20_STRUCTURES_'_(PDB_00010)
GGCCAGAUUGAGCCUGGGAGCUCUCUGGCC
(((((((..((((......)))))))))))
>>__'CIS-ACTING_RNA_REGULATORY_ELEMENT_(HIV-1_TAR),_NMR,_20_STRUCTURES_'_(PDB_00012)
GGCAGAUCUGAGCCUGGGAGCUCUCUGCC
..(((....((((......)))).)))..
>>__'IRON_RESPONSIVE_ELEMENT_RNA_HAIRPIN,_NMR,_15_STRUCTURES_'_(PDB_00013)
GGAGUGCUUCAACAGUGCUUGGACGCUCC
((((((.((.((......)).))))))))
>>__'THE_STRUCTURE_OF_THE_ISOLATED,_CENTRAL_HAIRPIN_OF_THE_HDV_ANTIGENOMIC_RIBOZYME,_NMR,_10_STRUCTURES_'_(PDB_00014)
GGCACCUCCUCGCGGUGCC
(((((((.....)))))))
>>__'HAIRPIN_WITH_AGAU_TETRALOOP,_NMR,_3_STRUCTURES_'_(PDB_00016)
GCUCCAGAUGGAGCG
(((((....))))).
>>__'NMR_STRUCTURE_OF_THE_DIMER_INITIATION_COMPLEX_OF_HIV-1_GENOMIC_RNA,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00018)
GGCAAUGAAGCGCGCACGUUGCCGGCAAUGAAGCGCGCACGUUGCC
(((((((.[[..[[[[)))))))(((((((.]]]]..]])))))))
>>__'S8_RRNA_BINDING_SITE_FROM_E._COLI,_NMR,_6_STRUCTURES_'_(PDB_00019)
GGGAUACUGCUUCGGUAAGUCCC
((((..((((....)).))))))
>>__'RNA_LOOP-LOOP_COMPLEX:_THE_COLE1_INVERTED_LOOP_SEQUENCE,_NMR,_8_STRUCTURES_'_(PDB_00020)
GGCAACGGAUGGUUCGUUGCCGCACCGAACCAUCCGGUGC
((((((([[[[[[[)))))))((((((]]]]]]]))))))
>>__'SL3_HAIRPIN_FROM_THE_PACKAGING_SIGNAL_OF_HIV-1,_NMR,_11_STRUCTURES_'_(PDB_00021)
GGACUAGCGGAGGCUAGUCC
((((((((....))))))))
>>__'HIV-1_RNA_A-RICH_HAIRPIN_LOOP_'_(PDB_00022)
GGCGACGGUGUAAAAAUCUCGCC
(((((.((((....)))))))))
>>__'STABILIZATION_OF_THE_ANTICODON_STEM-LOOP_OF_TRNALYS,3_BY_AN_A+C_BASE_PAIR_AND_BY_PSEUDOURIDINE,_NMR,_1_STRUCTURE_'_(PDB_00024)
UCAGACUUUUAAUCUGA
((((((.....))))))
>>__'STABILIZATION_OF_THE_ANTICODON_STEM-LOOP_OF_TRNALYS,3_BY_AN_A+C_BASE_PAIR_AND_BY_PSEUDOURIDINE,_NMR,_1_STRUCTURE_'_(PDB_00025)
UCAGACUUUUAAUCUGA
(((((((...)))))))
>>__'STRUCTURE_OF_THE_RIBOZYME_SUBSTRATE_HAIRPIN_OF_NEUROSPORA_VS_RNA._A_CLOSE_LOOK_AT_THE_CLEAVAGE_SITE_'_(PDB_00040)
GUGCGAAGACGAAAGUCCGAGCGC
((((((((((....))))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_PSEUDOKNOT_OF_SRV-1_RNA,_INVOLVED_IN_RIBOSOMAL_FRAMESHIFTING_'_(PDB_00041)
GCGGCCAGCUCCAGGCCGCCAAACAAUAUGGAGCAC
((((((.[[[[[[)))))).........]]]]]]..
>>__'NMR_ANALYSIS_OF_HELIX_I_FROM_THE_5S_RNA_OF_ESCHERICHIA_COLI_'_(PDB_00048)
UUGCCUGGCGGCAACUGCCAGGCAU
..(((((((((...)))))))))..
>>__'NMR_STRUCTURE_OF_STEM_LOOP_SL2_OF_THE_HIV-1_PSI_RNA_PACKAGING_SIGNAL_REVEALS_A_NOVEL_A-U-A_BASE-TRIPLE_PLATFORM_'_(PDB_00051)
GGCGACUGGUGAGUACGCC
(((((((....)).)))))
>>__'CRYSTAL_STRUCTURE_OF_A_BIOTIN-BINDING_RNA_PSEUDOKNOT_'_(PDB_00053)
ACCGUCAGAGGACACGGUUAAAAAGUCCUC
[[[[[..((((((]]]]]......))))))
>>__'SOLUTION_STRUCTURE_OF_THE_KISSING_DIMER_OF_H3_GACG_STEM-_LOOP_IN_THE_5\'-END_DIMERIZATION_SIGNAL_OF_MOLONEY_MURINE_LEUKEMIA_VIRUS_GENOMIC_RNA_'_(PDB_00056)
GGUGGGAGACGUCCCACCGGUGGGAGACGUCCCACC
(((((((..[[)))))))(((((((..]])))))))
>>__'SOLUTION_STRUCTURE_OF_THE_RNASE_P_RNA_(M1_RNA)_P4_STEM_OLIGORIBONUCLEOTIDE_'_(PDB_00057)
GGAAGUCCGGUCUUCGGACCGGCUUCC
(((((.(((((......))))))))))
>>__'SOLUTION_STRUCTURE_OF_RNASE_P_RNA_(M1_RNA)_P4_STEM_OLIGORIBONUCLEOTIDE_COMPLEXED_WITH_COBALT_(III)_HEXAMINE,_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00059)
GGAAGUCCGGUCUUCGGACCGGCUUCC
(((((.(((((......))))))))))
>>__'SOLUTION_STRUCTURE_OF_HCV_IRES_RNA_DOMAIN_IIID_'_(PDB_00065)
GGCCGAGUAGUGUUGGGUCGCGAAAGGCC
.(((((.(((((......)))))))))).
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_ANTICODON_OF_TRNA(LYS3)_WITH_T6A_MODIFICATION_AT_POSITION_37_'_(PDB_00068)
GCAGACUUUUAAUCUGC
((((((.....))))))
>>__'NMR_STRUCTURE_OF_THE_690_LOOP_OF_16_S_RRNA_OF_E._COLI_'_(PDB_00069)
GGCGGUGAAAUGCC
(((((....)))))
>>__'NMR_VALIDATED_MODEL_OF_DOMAIN_IIID_OF_HEPATITIS_C_VIRUS_INTERNAL_RIBOSOME_ENTRY_SITE_'_(PDB_00073)
GCCGAGUAGUGUUGGGUCGCGAAAGGC
(((((.(((((......))))))))))
>>__'SOLUTION_STRUCTURE_OF_RNA_HAIRPIN_LOOP_UUAACU_AS_PART_OF_HAIRPIN_R(GCGUUAACUCGCA)_'_(PDB_00083)
GCGUUAACUCGCA
((((....)))).
>>__'SOLUTION_STRUCTURE_OF_RNA_HAIRPIN_LOOP_UUAAGU_AS_PART_OF_HAIRPIN_R(GCGUUAAGUCGCA)_'_(PDB_00084)
GCGUUAAGUCGCA
((((....)))).
>>__'SOLUTION_STRUCTURE_OF_RNA_HAIRPIN_LOOP_UUAAUU_AS_PART_OF_HAIRPIN_R(GCGUUAAUUCGCA)_'_(PDB_00085)
GCGUUAAUUCGCA
((((....)))).
>>__'SOLUTION_STRUCTURE_OF_RNA_HAIRPIN_LOOP_UUAAAU_AS_PART_OF_HAIRPIN_R(GCGUUAAAUCGCA)_'_(PDB_00086)
GCGUUAAAUCGCA
((((....)))).
>>__'SOLUTION_STRUCTURE_OF_RNA_HAIRPIN_LOOP_UCAAUU_AS_PART_OF_HAIRPIN_R(GCGUCAAUUCGCA)_'_(PDB_00087)
GCGUCAAUUCGCA
((((....)))).
>>__'SOLUTION_STRUCTURE_OF_THE_VS_RIBOZYME_SUBSTRATE_STEM-LOOP_'_(PDB_00088)
GGUGCGAAGGGCGUCGUCGCCCCGAGCGCC
((((((((((((......))))))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_A_LOOP_OF_23S_RIBOSOMAL_RNA_'_(PDB_00089)
GGCUGGCUGUUCGCCAGCC
((((((((...))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_A_LOOP_OF_23S_RIBOSOMAL_RNA._'_(PDB_00090)
GGCUGGCUGUUCGCCAGCC
((((((((...))))))))
>>__'THE_SOLUTION_STRUCTURE_OF_THE_MUTANT_STEM_LOOP_C_5\'GUA3\'_TRILOOP_OF_BROME_MOSAIC_VIRUS_(+)_STRAND_RNA_'_(PDB_00091)
GGUGCGUAGCACC
(((((...)))))
>>__'THE_SOLUTION_STRUCTURE_OF_THE_MAJOR_FAMILY_OF_THE_MUTANT_STEM_LOOP_C_5\'UUA3\'_TRILOOP_OF_BROME_MOSAIC_VIRUS_(+)_STRAND_RNA_'_(PDB_00092)
GGUGCUUAGCACC
(((((...)))))
>>__'THE_SOLUTION_STRUCTURE_OF_THE_MINOR_FAMILY_OF_THE_MUTANT_STEM_LOOP_C_5\'UUA3\'_TRILOOP_OF_BROME_MOSAIC_VIRUS_(+)_STRAND_RNA_'_(PDB_00093)
GGUGCUUAGCACC
(((((...)))))
>>__'CRYSTAL_STRUCTURE_ANALYSIS_OF_A_TRNA-NEOMYCIN_COMPLEX_'_(PDB_00095)
GCGGAUUUAGCUCAGUUGGGAGAGCGCCAGACUGAAGACUGGAGGUCCUGUGUUCGAUCCACAGAAUUCGCACCA
(((((((..((((........))))(((((........)))))....(((((.......))))))))))))....
>>__'NMR_STRUCTURE_OF_HCV_IRES_RNA_DOMAIN_IIIC_'_(PDB_00097)
GGGCGUGCCC
(((....)))
>>__'NMR_SOLUTION_STRUCTURE_OF_AN_IN_VITRO_SELECTED_RNA_WHICH_IS_SEQUENCE_SPECIFICALLY_RECOGNIZED_BY_HAMSTER_NUCLEOLIN_RBD12._'_(PDB_00098)
GGCCGAAAUCCCGAAGUAGGCC
((((((..........))))))
>>__'SOLUTION_STRUCTURE_OF_AN_IN_VITRO_SELECTED_RNA_WHICH_IS_SEQUENCE_SPECIFICALLY_RECOGNIZED_BY_RBD12_OF_HAMSTER_NUCLEOLIN.SNRE_(ANTI)_'_(PDB_00099)
GGCCGAAAUCCCGAAGUAGGCC
((((((..........))))))
>>__'SOLUTION_STRUCTURE_OF_AN_RNA_HAIRPIN_FROM_HRV-14_'_(PDB_00100)
GGUACUAUGUACCA
(((((...))))).
>>__'SOLUTION_STRUCTURE_OF_THE_UNMODIFIED_ANTICODON_STEM-LOOP_FROM_E._COLI_TRNA(PHE)_'_(PDB_00103)
GGGGAUUGAAAAUCCCC
(((((((...)))))))
>>__'NMR_STRUCTURE_OF_THE_LP5.1_HAIRPIN_FROM_BACILLUS_RNASE_P_RNA_REFINED_WITH_RESIDUAL_DIPOLAR_COUPLINGS_'_(PDB_00108)
GGCGGUGCUGAGAUGCCCGUC
(((((.((......)))))))
>>__'NMR_STRUCTURE_OF_THE_LP5.1_HAIRPIN_FROM_BACILLUS_RNASE_P_RNA_REFINED_WITHOUT_RESIDUAL_DIPOLAR_COUPLINGS_'_(PDB_00109)
GGCGGUGCUGAGAUGCCCGUC
(((((.((......)))))))
>>__'SOLUTION_STRUCTURE_OF_HIV-1LAI_MUTATED_SL1_HAIRPIN_'_(PDB_00110)
CUUGCUGAAGCACGCACGGCAAG
(((((((.........)))))))
>>__'THE_SOLUTION_STRUCTURE_OF_THE_MUTANT_5\'AUG3\'_TRILOOP_IN_THE_RNA_PROMOTER_REGION_OF_THE_BROME_MOSAIC_VIRUS_GENOMIC_(+)-_RNA_'_(PDB_00114)
GGUGCAUGGCACC
((((.....))))
>>__'STRUCTURE_OF_AGUU_RNA_TETRALOOP,_NMR,_20_STRUCTURES_'_(PDB_00118)
GGUUCAGUUGAACC
(((((....)))))
>>__'NMR_STRUCTURE_OF_A_RIBOSOMAL_RNA_HAIRPIN_CONTAINING_A_CONSERVED_CUCAA_PENTALOOP_'_(PDB_00119)
GGACCCGGGCUCAACCUGGGUCC
((((((((((...))))))))))
>>__'HIV-1(MAL)_RNA_DIMERIZATION_INITIATION_SITE_'_(PDB_00123)
UUUGCUGAGGUGCACACAGCAAUUUUGCUGAGGUGCACACAGCAAUUUUGCUGAGGUGCACACAGCAAUUUUGCUGAGGUGCACACAGCAAU
..(((((..[[[[[[.)))))..(((((((..]]]]]].)))))))..(((((..[[[[[[.)))))..(((((((..]]]]]].)))))))
>>__'CONFORMATION_OF_AN_RNA_PSEUDOKNOT_FROM_MOUSE_MAMMARY_TUMOR_VIRUS,_NMR,_1_STRUCTURE_'_(PDB_00124)
GGCGCAGUGGGCUAGCGCCACUCAAAAGCCCG
((((((..[[[[.))))))........]]]].
>>__'TAR-TAR_"KISSING"_HAIRPIN_COMPLEX_DERIVED_FROM_THE_HIV_GENOME,_NMR,_1_STRUCTURE_'_(PDB_00128)
GAGCCCUGGGAGGCUCGCUGUUCCCAGACAGC
((((([[[[..)))))(((((.]].]])))))
>>__'SOLUTION_STRUCTURE_OF_THE_UNMODIFIED_ANTICODON_STEM-LOOP_FROM_E._COLI_TRNA(PHE)_'_(PDB_00129)
GGGGAUUGAAAAUCCCC
(((((((...)))))))
>>__'STRUCTURE_OF_THE_HISTONE_MRNA_HAIRPIN_REQUIRED_FOR_CELL_CYCLE_REGULATION_OF_HISTONE_GENE_EXPRESSION_'_(PDB_00130)
GGAAGGCCCUUUUCAGGGCCACCC
....((((((....))))))....
>>__'SOLUTION_NMR_STRUCTURE_OF_AN_ANALOG_OF_THE_YEAST_TRNA_PHE_T_STEM_LOOP_CONTAINING_RIBOTHYMIDINE_AT_ITS_NATURALLY_OCCURRING_POSITION_'_(PDB_00131)
CUGUGUUCGAUCCACAG
(((((.......)))))
>>__'A_MUTANT_RNA_PSEUDOKNOT_THAT_PROMOTES_RIBOSOMAL_FRAMESHIFTING_IN_MOUSE_MAMMARY_TUMOR_VIRUS,_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00133)
GGCGCAGUGGGCUAGCGCCACUCAAAGGCCCG
(((((...[[[[[.))))).......]]]]].
>>__'PEMV-1_P1-P2_FRAMESHIFTING_PSEUDOKNOT,_15_LOWEST_ENERGY_STRUCTURES_'_(PDB_00134)
UCCGGUCGACUCCGGAGAAACAAAGUCA
(((((..[[[.)))))........]]].
>>__'PEMV-1_P1-P2_FRAMESHIFTING_PSEUDOKNOT_REGULARIZED_AVERAGE_STRUCTURE_'_(PDB_00135)
UCCGGUCGACUCCGGAGAAACAAAGUCA
(((((..[[..))))).........]].
>>__'ATOMIC_RESOLUTION_CRYSTAL_STRUCTURE_OF_A_VIRAL_RNA_PSEUDOKNOT_'_(PDB_00138)
GGCGCGGCACCGUCCGCGGAACAAACGG
..(((((..[[[.))))).......]]]
>>__'LOW_RESOLUTION_CRYSTAL_STRUCTURE_OF_A_VIRAL_RNA_PSEUDOKNOT_'_(PDB_00139)
GGCGCGGCACCGUCCGCGGAACAAACGG
..(((((..[[[.))))).......]]]
>>__'SOLUTION_STRUCTURE_OF_THE_U6_INTRAMOLECULAR_STEM-LOOP_RNA_'_(PDB_00141)
GGUUCCCCUGCAUAAGGAUGAACC
((((((((((...))))).)))))
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_ANTICODON_OF_YEAST_TRNA-PHE_WITH_4_MODIFICATIONS_(OMC32_OMG34_1MG37_5MC40)_'_(PDB_00147)
CCAGACUGAAGAUCUGG
((((((.....))))))
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_ANTICODON_OF_YEAST_TRNA-PHE_WITH_3_MODIFICATIONS_(OMC32_OMG34_M5C40)_'_(PDB_00148)
CCAGACUGAAGAUCUGG
((((((.....))))))
>>__'CRYSTAL_STRUCTURE_ANALYSIS_OF_A_26MER_RNA_MOLECULE,_REPRESENTING_A_NEW_RNA_MOTIF,_THE_HOOK-TURN_'_(PDB_00155)
CCAUGCGAACCGCGAUCCUAGUGUGG
((((((((..........))))))))
>>__'STRUCTURE_OF_23S_RIBOSOMAL_RNA_HAIRPIN_35_'_(PDB_00160)
GGCGUAACGUUGAAAAGUUACGCC
(((((((((......)))))))))
>>__'SOLUTION_STRUCTURE_OF_B._SUBTILIS_T_BOX_ANTITERMINATOR_RNA_'_(PDB_00168)
GAGGGUGGAACCGCGCGCGUCCCUC
((((........((....)).))))
>>__'SOLUTION_STRUCTURE_OF_THE_P2B_HAIRPIN_FROM_HUMAN_TELOMERASE_RNA_'_(PDB_00171)
GGGCUGUUUUUCUCGCUGACUUUCAGCCCC
((((((((((((.....)))))))))))).
>>__'IRON_RESPONSIVE_ELEMENT_RNA_HAIRPIN,_NMR,_15_STRUCTURES_'_(PDB_00172)
GGAGUGCUUCAACAGUGCUUGGACGCUCC
((((((.(((((......)))))))))))
>>__'U80G_U6_INTRAMOLECULAR_STEM-LOOP_RNA_FROM_SACCHAROMYCES_CEREVISIAE_'_(PDB_00173)
GGUUCCCCUGCAUAAGGAGGAACC
((((((((((...)))).))))))
>>__'SOLUTION_STRUCTURE_OF_THE_S._CEREVISIAE_U6_INTRAMOLECULAR_STEM-LOOP_CONTAINING_AN_SP_PHOSPHOROTHIOATE_AT_NUCLEOTIDE_U80_'_(PDB_00177)
GGUUCCCCUGCAUAAGGAUGAACC
((((((((((...))))).)))))
>>__'P6.1_STEM_LOOP_FROM_THE_ACTIVATION_DOMAIN_OF_HTR_'_(PDB_00180)
GAGAGUUGGGCUCUC
((((((...))))))
>>__'SOLUTION_STRUCTURE_OF_HCV_IRES_DOMAIN_IIB_'_(PDB_00184)
GGCAGAAAGCGUCUAGCCAUGGCGUUAGUAUGCC
(((((((((((((.......))))))).))))))
>>__'SOLUTION_STRUCTURE_OF_HCV_IRES_DOMAIN_II_'_(PDB_00185)
GGCUGUGAGGAACUACUGUCUUCACGCAGAAAGCGUCUAGCCAUGGCGUUAGUAUGAGUGUCGUGCAGCCUCCAGCC
(((((.((((.....((((((.((((((((..(((((.......)))))...)))))))).)).)))))))))))))
>>__'SOLUTION_STRUCTURE_OF_HCV_IRES_DOMAIN_II_(MINIMIZED_AVERAGE_STRUCTURE)_'_(PDB_00186)
GGCUGUGAGGAACUACUGUCUUCACGCAGAAAGCGUCUAGCCAUGGCGUUAGUAUGAGUGUCGUGCAGCCUCCAGCC
(((((.((((.....((((((((((((((((((((((.......))))))).))))))))))).)))))))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_DYSKERATOSIS_CONGENITA_MUTANT_P2B_HAIRPIN_FROM_HUMAN_TELOMERASE_RNA_'_(PDB_00191)
GGCUCUCAGUGAGCC
(((((.....)))))
>>__'NMR_STRUCTURE_OF_TAU_EXON_10_SPLICING_REGULATORY_ELEMENT_RNA_'_(PDB_00197)
GGCAGUGUGAGUACCUUCACACGUC
....(((((((....)))))))...
>>__'NMR_STRUCUTRE_OF_5\'-R(GGACACGAAAUCCCGAAGUAGUGUCC)-3\'_:_AN_RNA_HAIRPIN_CONTAINING_THE_IN_VITRO_SELECTED_CONSENSUS_SEQUENCE_FOR_NUCLEOLIN_RBD12_'_(PDB_00201)
GGACACGAAAUCCCGAAGUAGUGUCC
((((((((((.....)).))))))))
>>__'24-MER_RNA_HAIRPIN_COAT_PROTEIN_BINDING_SITE_FOR_BACTERIOPHAGE_R17_(NMR,_MINIMIZED_AVERAGE_STRUCTURE)_'_(PDB_00206)
GGGACUGACGAUCACGCAGUCUAU
.((((((.((....))))))))..
>>__'THE_STRUCTURE_OF_AN_RNA_PSEUDOKNOT_THAT_CAUSES_EFFICIENT_FRAMESHIFTING_IN_MOUSE_MAMMARY_TUMOR_VIRUS_'_(PDB_00209)
GGCGCAGUGGGCUAGCGCCACUCAAAAGGCCCAU
[[[[[..((((((.]]]]]........)))))).
>>__'FIRST_STEM_LOOP_OF_THE_SL1_RNA_FROM_CAENORHABDITIS_ELEGANS,_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00216)
UUACCCAAGUUUGAGGUAA
(((((((....)).)))))
>>__'FIRST_STEM_LOOP_OF_THE_SL1_RNA_FROM_CAENORHABDITIS_ELEGANS,_NMR,_16_STRUCTURES_'_(PDB_00217)
UUACCCAAGUUUGAGGUAA
(((((((....)).)))))
>>__'REFINED_SOLUTION_STRUCTURE_OF_THE_S._CEREVISIAE_U6_INTRAMOLECULAR_STEM_LOOP_(ISL)_RNA_USING_RESIDUAL_DIPOLAR_COUPLINGS_(RDCS)_'_(PDB_00218)
GGUUCCCCUGCAUAAGGAUGAACC
((((((((((...))))).)))))
>>__'SOLUTION_STRUCTURE_OF_ITALY1_("INITIATOR_TRNA_ANTICODON_LOOP_FROM_YEAST"),_AN_UNMODIFIED_21-NT_RNA_WITH_THE_SEQUENCE_OF_THE_ANTICODON_STEM-LOOP_OF_YEAST_INITIATOR_TRNA_'_(PDB_00219)
GGCAGGGCUCAUAACCCUGCC
(((((((.......)))))))
>>__'STEM_LOOP_IIA_FROM_U2SNRNA_OF_SACCHAROMYCES_CEREVISIAE,_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00224)
GGUCAGUGUAACAACUGACC
((((((((....))))))))
>>__'STRUCTURE_OF_AN_RNA_HAIRPIN_LOOP_WITH_A_5\'-CGUUUCG-3\'_LOOP_MOTIF_BY_HETERONUCLEAR_NMR_SPECTROSCOPY_AND_DISTANCE_GEOMETRY,_15_STRUCTURES_'_(PDB_00225)
GGCGUACGUUUCGUACGCC
(((((((.....)))))))
>>__'CONSERVED_RNA_COMPONENT_OF_THE_PEPTIDYL_TRANSFERASE_CENTER,_NMR,_33_STRUCTURES_'_(PDB_00226)
GACUGGGGCGGUC
(((((...)))))
>>__'YEAST_INITIATOR_TRNA_'_(PDB_00229)
AGCGCCGUGGCGCAGUGGAAGCGCGCAGGGCUCAUAACCCUGAUGUCCUCGGAUCGAAACCGAGCGGCGCUACCA
(((((((..((((.......))))(((((((.....)))))))....(((((.......))))))))))))....
>>__'GAAA_RNA_TETRALOOP,_NMR,_10_STRUCTURES_'_(PDB_00231)
GGGCGAAAGCCU
(((......)))
>>__'SOLUTION_NMR_STRUCTURE_OF_A_SUBSTRATE_FOR_THE_ARCHAEAL_PRE-_TRNA_SPLICING_ENDONUCLEASES:_THE_BULGE-HELIX-BULGE_MOTIF,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00240)
GGGUGACUCCAGAGGUCGAGAGACCGGAGAUAUCACCC
((((((((((...((((....))))))))...))))))
>>__'RNA_LOOP-LOOP_COMPLEX:_THE_COLE1_INVERTED_LOOP_SEQUENCE,_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00241)
GGCAACGGAUGGUUCGUUGCCGCACCGAACCAUCCGGUGC
((((((([[[[[[[)))))))((((((]]]]]]]))))))
>>__'AN_INVESTIGATION_OF_THE_STRUCTURE_OF_THE_PSEUDOKNOT_WITHIN_THE_GENE_32_MESSENGER_RNA_OF_BACTERIOPHAGE_T2_USING_HETERONUCLEAR_NMR_METHODS_'_(PDB_00243)
GCUGACCAGCUAUGAGGUCAUACAUCGUCAUAGCAC
..[[[[[.(((((((]]]]].......)))))))..
>>__'STEM_LOOP_IIA_FROM_U2_SNRNA_OF_SACCHAROMYCES_CEREVISIAE,_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00245)
GGUCAGUGUAACAACUGACC
((((((((....))))))))
>>__'RNA_PSEUDOKNOT_WITH_3D_DOMAIN_SWAPPING_'_(PDB_00256)
UCCGAAGUGCAACGGGAAAAUGCACU
.((((......))))...........
>>__'STRUCTURE_OF_THE_3\'_HAIRPIN_OF_THE_TYMV_PSEUDOKNOT:_PREFORMATION_IN_RNA_FOLDING_'_(PDB_00258)
GGUUCCGAGGGUCAUCGGAACCA
((((((((......)))))))).
>>__'CRYSTAL_STRUCTURE_OF_AN_RNA_PSEUDOKNOT_FROM_BEET_WESTERN_YELLOW_VIRUS_INVOLVED_IN_RIBOSOMAL_FRAMESHIFTING_'_(PDB_00269)
GGCGCGGCACCGUCCGCGGAACAAACGG
..(((((..[[[.))))).......]]]
>>__'STRUCTURE_OF_THE_HIV-1_NUCLEOCAPSID_PROTEIN_BOUND_TO_THE_SL3_PSI-RNA_RECOGNITION_ELEMENT,_NMR,_25_STRUCTURES_'_(PDB_00285)
GGACUAGCGGAGGCUAGUCC
((((((((....))))))))
>>__'SATELLITE_TOBACCO_MOSAIC_VIRUS/RNA_COMPLEX_'_(PDB_00286)
AAAAAAAAAAUUUUUUUUUU
..((((((...))))))...
>>__'LOOP_D/LOOP_E_ARM_OF_ESCHERICHIA_COLI_5S_RRNA,_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00288)
GGCCGAUGGUAGUGUGGGGUCUCCCCAUGCGAGAGUAGGCC
(((((((((((((((((((...)))))))))))))))))))
>>__'SOLUTION_STRUCTURE_OF_PHAGE_P22_N_PEPTIDE-BOX_B_RNA_COMPLEX,_NMR,_20_STRUCTURES_'_(PDB_00289)
GCGCUGACAAAGCGC
((((((...))))))
>>__'CRYSTAL_STRUCTURE_OF_THE_SPLICEOSOMAL_U2B\'\'-U2A\'_PROTEIN_COMPLEX_BOUND_TO_A_FRAGMENT_OF_U2_SMALL_NUCLEAR_RNA_'_(PDB_00293)
CCUGGUAUUGCAGUACCUCCAGGUCCUGGUAUUGCAGUACCUCCAGGU
((((((...........)))))).((((((...........)))))).
>>__'HIV-2_TRANS_ACTIVATING_REGION_RNA_COMPLEX_WITH_ARGININAMIDE,_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00299)
GGCCAGAUUGAGCCUGGGAGCUCUCUGGCC
(((((((..((((......)))))))))))
>>__'BACTERIOPHAGE_MS2_CAPSID_PROTEIN/RNA_COMPLEX_'_(PDB_00303)
AUGAGGAUUACCCAUGUGAGGAUUACCC
(((.((....)))))....((....)).
>>__'STRUCTURE_OF_A_MS2_COAT_PROTEIN_MUTANT_IN_COMPLEX_WITH_AN_RNA_OPERATOR_'_(PDB_00304)
AUGAGGAUUACCCAUGAUGAGGAUUACCCA
(((.((....)))))..((.((....))))
>>__'ARG-BOUND_TAR_RNA,_NMR_'_(PDB_00306)
GGCAGAUCUGAGCCUGGGAGCUCUCUGCC
..((((...((((......))))))))..
>>__'U1A-UTRRNA,_NMR,_31_STRUCTURES_'_(PDB_00312)
GGCAGAGUCCUUCGGGACAUUGCACCUGCC
(((((.((((....)))).......)))))
>>__'BOVINE_IMMUNODEFICIENCY_VIRUS_TAT-TAR_COMPLEX,_NMR,_5_STRUCTURES_'_(PDB_00317)
GGCUCGUGUAGCUCAUUAGCUCCGAGCC
((((((...((((....)))).))))))
>>__'HEPATITIS_DELTA_VIRUS_RIBOZYME_'_(PDB_00335)
GGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGCGAAUGGGAC
(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_5S_RRNA_E-LOOP/L25_COMPLEX_'_(PDB_00339)
GGACCGAUGGUAGUGUCUUCGGAUGCGAGAGUAGGUC
.((((((((((((((((....))))))))))))))))
>>__'CRYSTAL_STRUCTURE_OF_E.COLI_RIBOSOMAL_PROTEIN_L25_COMPLEXED_WITH_A_5S_RRNA_FRAGMENT_AT_1.8_A_RESOLUTION_'_(PDB_00341)
CCCAUGCGAGAGUAGGGACUGCCGAUGGUAGUGUGGGG
((((((((((((((((.....)))))))))))))))).
>>__'U1A_SPLICEOSOMAL_PROTEIN/HEPATITIS_DELTA_VIRUS_GENOMIC_RIBOZYME_COMPLEX_'_(PDB_00346)
GGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGCGAAUGGGAC
(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CORE_OF_THE_ALU_DOMAIN_OF_THE_MAMMALIAN_SRP_'_(PDB_00352)
GGGCCGGGCGCGGUGGCGCGCGCCUGUAGUCCCAGCUACUCGGGAGGCUC
(((((((((((((..[[))))))))....((((.]].....)))))))))
>>__'CRYSTAL_STRUCTURE_OF_NOVA-2_KH3_K-HOMOLOGY_RNA-BINDING_DOMAIN_BOUND_TO_20-MER_RNA_HAIRPIN_'_(PDB_00357)
GAGGACCUAGAUCACCCCUCGAGGACCUAGAUCACCCCUC
(((((..........)))))(((((..........)))))
>>__'STRUCTURAL_BASIS_FOR_RECOGNITION_OF_THE_RNA_MAJOR_GROOVE_IN_THE_TAU_EXON_10_SPLICING_REGULATORY_ELEMENT_BY_AMINOGLYCOSIDE_ANTIBIOTICS_'_(PDB_00361)
GGCAGUGUGAGUACCUUCACACGUC
....((((((......))))))...
>>__'THE_CRYSTAL_STRUCTURE_OF_PHENYLALANYL-TRNA_SYNTHETASE_FROM_THERMUS_THERMOPHILUS_COMPLEXED_WITH_COGNATE_TRNAPHE_'_(PDB_00362)
GCCGAGGUAGCUCAGUUGGUAGAGCAUGCGACUGAAAAUCGCAGUGUCCGCGGUUCGAUUCCGCGCCUCGGCACCA
(((((((..((((........))))((((((.......))))))....(((((.......))))))))))))....
>>__'CRYSTAL_STRUCTURE_OF_GLUTAMINYL-TRNA_SYNTHETASE_COMPLEXED_WITH_A_TRNA-GLN_MUTANT_AND_AN_ACTIVE-SITE_INHIBITOR_'_(PDB_00373)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAGCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..((((.......))))((((((((...))))))))..(((((.......))))))))))).....
>>__'GLUTAMINYL-TRNA_SYNTHETASE_COMPLEXED_WITH_A_TRNA_MUTANT_AND_AN_ACTIVE_SITE_INHIBITOR_'_(PDB_00374)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAAGCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..((((.......))))((((((((...))))))))...(((((.......))))))))))).....
>>__'CRYSTAL_STRUCTURE_OF_A_TIGHT-BINDING_GLUTAMINE_TRNA_BOUND_TO_GLUTAMINE_AMINOACYL_TRNA_SYNTHETASE_'_(PDB_00376)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGAGGUCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..(((.........)))((((((((...))))))))...(((((.......))))))))))).....
>>__'SOLUTION_STRUCTURE_OF_HTLV-1_PEPTIDE_BOUND_TO_ITS_RNA_APTAMER_TARGET_'_(PDB_00377)
GGGCGCCGGUACGCAAGUACGACGGUACGCUCC
((((((((((((....))))..)))..))))).
>>__'NMR_STRUCTURE_OF_THE_HIV-1_NUCLEOCAPSID_PROTEIN_BOUND_TO_STEM-LOOP_SL2_OF_THE_PSI-RNA_PACKAGING_SIGNAL._IMPLICATIONS_FOR_GENOME_RECOGNITION_'_(PDB_00383)
GGCGACUGGUGAGUACGCC
(((((((....)).)))))
>>__'INSIGHTS_INTO_EDITING_FROM_AN_ILE-TRNA_SYNTHETASE_STRUCTURE_WITH_TRNA(ILE)_AND_MUPIROCIN_'_(PDB_00402)
GGGCUUGUAGCUCAGGUGGUUAGAGCGCACCCCUGAUAAGGGUGAGGUCGGUGGUUCAAGUCCACUCAGGCCCAC
(((((((..((((.........))))(((((((.....)))))))....(((((.......))))))))))))..
>>__'SOLUTION_STRUCTURE_OF_NUCLEOLIN_RBD12_IN_COMPLEX_WITH_SNRE_RNA_'_(PDB_00407)
GGCCGAAAUCCCGAAGUAGGCC
((((((..........))))))
>>__'COMPLEX_OF_HIV-1_RRE-IIB_RNA_WITH_RSG-1.2_PEPTIDE_'_(PDB_00420)
GGUCUGGGCGCACUUCGGUGACGGUACAGGCC
...((((((((((....))).))).))))...
>>__'STRUCTURAL_BASIS_OF_ANTICODON_LOOP_RECOGNITION_BY_GLUTAMINYL-TRNA_SYNTHETASE_'_(PDB_00425)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..(((.........)))((((((((...))))))))....(((((.......))))))))))).....
>>__'STRUCTURAL_BASIS_FOR_TRANSFER_RNA_AMINOACEYLATION_BY_ESCHERICHIA_COLI_GLUTAMINYL-TRNA_SYNTHETASE_'_(PDB_00426)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..(((.........))).(((((((...))))))).....(((((.......))))))))))).....
>>__'BACTERIOPHAGE_HK022_NUN-PROTEIN-NUTBOXB-RNA_COMPLEX_'_(PDB_00434)
GCCCUGAAAAAGGGC
((((((...))))))
>>__'CRYSTAL_STRUCTURE_OF_ARCHAEAL_TYROSYL-TRNA_SYNTHETASE_COMPLEXED_WITH_TRNA(TYR)_AND_L-TYROSINE_'_(PDB_00474)
CCGGCGGUAGUUCAGCCUGGUAGAACGGCGGACUGUAGAUCCGCAUGUCGCUGGUUCAAAUCCGGCCCGCCGGA
(((((((..((((.........))))(((((((.....)))))))....(((((.......)))))))))))).
>>__'CRYSTAL_STRUCTURE_OF_THE_RIBOTOXIN_RESTRICTOCIN_AND_A_31-_MER_SRD_RNA_INHIBITOR_'_(PDB_00481)
GCGCUCCUCAGUACGAGAGGAACCGGAGCGCGCGCUCCUCAGUACGAGAGGAACCGGAGCGC
((((((((((.(((....)))))))))))))((((((((((.(((....)))))))))))))
>>__'CRYSTAL_STRUCTURE_OF_RIBOTOXIN_RESTRICTOCIN_AND_A_29-MER_SRD_RNA_ANALOG_'_(PDB_00482)
CGCUCCUCAGUACGAUAGGAACCGGAGCGCGCUCCUCAGUACGAUAGGAACCGGAGCG
(((((((((.(((....))))))))))))(((((((((.(((....))))))))))))
>>__'CRYSTAL_STRUCTURE_OF_RIBOTOXIN_RESTRICTOCIN_COMPLEXED_WITH_A_29-MER_SARCIN/RICIN_DOMAIN_RNA_ANALOG_'_(PDB_00483)
CGCUCCUCAGUACGAGAGGAACCGGAGCGCGCUCCUCAGUACGAGAGGAACCGGAGCG
(((((((((.(((....))))))))))))(((((((((.(((....))))))))))))
>>__'HUMAN_SRP19_IN_COMPLEX_WITH_HELIX_6_OF_HUMAN_SRP_RNA_'_(PDB_00487)
GGUGACCUCCCGGGAGCGGGGGACCACUA
((((((((((((....)))))))))))).
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_RNA_HAIRPIN_BINDING_SITE_FOR_THE_HISTONE_STEM-LOOP_BINDING_PROTEIN_'_(PDB_00495)
GGCCCUUUUCAGGGCC
((((((....))))))
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_RNA_HAIRPIN_BINDING_SITE_FOR_THE_HISTONE_STEM-LOOP_BINDING_PROTEIN_'_(PDB_00497)
GGCCCUUUUCAGGGCC
....((....))....
>>__'CRYSTAL_STRUCTURE_OF_THE_E._COLI_PSEUDOURIDINE_SYNTHASE_TRUB_BOUND_TO_A_T_STEM-LOOP_RNA_'_(PDB_00513)
GGCAACGGUUCGAUCCCGUUGC
.(((((((.......)))))))
>>__'RNA_APTAMER_COMPLEXED_WITH_ARGININE,_NMR_'_(PDB_00526)
AGAAGGAGCGUACAGGUAGGUCGCU
.....(((...........)))...
>>__'CRYSTAL_STRUCTURE_OF_T3C_MUTANT_S15_RIBOSOMAL_PROTEIN_IN_COMPLEX_WITH_16S_RRNA_'_(PDB_00535)
GGGCGGCCUUCGGGCUAGACGGUGGGAGAGGCUUCGGCUGGUCCACCCGUGACGCUC
((((.(((....)))...((((((((((.(((....)))))))))).)))...))))
>>__'CRYSTAL_STRUCTURE_OF_THE_SRP19-7S.S_SRP_RNA_COMPLEX_OF_M._JANNASCHII_'_(PDB_00547)
UCGGCGGUGGGGGAGCAUCUCCUGUAGGGGAGAUGUAACCCCCUUUACCUGCCGAACCCCGCCAGGCCCGGAAGGGAGCAACGGUAGGCAGGACGUC
..((((..(((((.(((((((((....)))))))))..)))))....((((((((....((((.(((((....))))).)))).)))))))).))))
>>__'STRUCTURE_OF_TAR_RNA_COMPLEXED_WITH_A_TAT-TAR_INTERACTION_NANOMOLAR_INHIBITOR_THAT_WAS_IDENTIFIED_BY_COMPUTATIONAL_SCREENING_'_(PDB_00553)
GGCCAGAUCUGAGCCUGGGAGCUCUCUGGCC
(((((((...((((......)))))))))))
>>__'DETAILED_ANALYSIS_OF_RNA-PROTEIN_INTERACTIONS_WITHIN_THE_BACTERIAL_RIBOSOMAL_PROTEIN_L5/5S_RRNA_COMPLEX_'_(PDB_00570)
GGCACCUGACCCCAUGCCGAACUCAGAAGUGCCCGGCACCUGACCCCAUGCCGAACUCAGAAGUGCCC
(((((((((....((....)).))))..))))).(((((((((....((....)).))))..))))).
>>__'BIV_TAT_PEPTIDE_(RESIDUES_68-81),_NMR,_MINIMIZED_AVERAGE_STRUCTURE_'_(PDB_00574)
GGCUCGUGUAGCUCAUUAGCUCCGAGCC
((((((...((((....)))).))))))
>>__'LAMBDA3_ELONGATION_COMPLEX_WITH_FOUR_PHOSPHODIESTER_BOND_FORMED_'_(PDB_00588)
GGGGGUAGCCCCCCCC
.((.......))....
>>__'REOVIRUS_POLYMERASE_LAMBDA3_ELONGATION_COMPLEX_WITH_ONE_PHOSPHODIESTER_BOND_FORMED_'_(PDB_00590)
GCUUAGCUCC
((...))...
>>__'SACCHARIDE-RNA_RECOGNITION_IN_THE_NEOMYCIN_B_/_RNA_APTAMER_COMPLEX_'_(PDB_00603)
GGACUGGGCGAGAAGUUUAGUCC
((((((((((...))))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_BACTERIOPHAGE_PHI21_N_PEPTIDE-_BOXB_RNA_COMPLEX_'_(PDB_00617)
GGUUCACCUCUAACCGGGUGAGCC
((((((((((....))))))))))
>>__'CRYSTAL_STRUCTURE_OF_L-GLUTAMINE_AND_AMPCPP_BOUND_TO_GLUTAMINE_AMINOACYL_TRNA_SYNTHETASE_'_(PDB_00620)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..((((.......))))(((((((.....)))))))....(((((.......))))))))))).....
>>__'CRYSTAL_STRUCTURE_OF_L-GLUTAMATE_AND_AMPCPP_BOUND_TO_GLUTAMINE_AMINOACYL_TRNA_SYNTHETASE_'_(PDB_00621)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..((((.......)))).(((((((...))))))).....(((((.......))))))))))).....
>>__'MODEL_FOR_THIOSTREPTON_ANTIBIOTIC_BINDING_TO_L11_SUBSTRATE_FROM_50S_RIBOSOMAL_RNA_'_(PDB_00627)
GCUGGGAUGUUGGCUUAGAAGCAGCCAUCAUUUAAAGAGUGCGUAACAGCUCACCAGC
(((((((((..((((.......))))..)))........((((....)))).))))))
>>__'CRYSTAL_STRUCTURE_OF_THE_TRNA_DOMAIN_OF_TRANSFER-MESSENGER_RNA_IN_COMPLEX_WITH_SMPB_'_(PDB_00637)
GAUUCGACGGGGACUUCGGUCCUCGGACGCGGGUUCGAUUCCCGCUCGACGGGGACUUCGGUCCUCGGA
......((((((((....))))))))..(((((.......)))))...((((((((....)))))))).
>>__'CHEMICAL_TRAPPING_AND_CRYSTAL_STRUCTURE_OF_A_CATALYTIC_TRNA_GUANINE_TRANSGLYCOSYLASE_COVALENT_INTERMEDIATE_'_(PDB_00648)
AGCACGGCUUAAACCGUGCAGCACGGCUUAAACCGUGCUUUU
(((((((......)))))))((((((......))))))....
>>__'CHEMICAL_TRAPPING_AND_CRYSTAL_STRUCTURE_OF_A_CATALYTIC_TRNA_GUANINE_TRANSGLYCOSYLASE_COVALENT_INTERMEDIATE_'_(PDB_00649)
AGCACGGCUGUAAACCGUGCAGCACGGCUUAAACCGUGC
(((((((.......)))))))((((((......))))))
>>__'HIV-1_TAR_RNA/NEOMYCIN_B_COMPLEX_'_(PDB_00664)
GCCAGAUUUGAGCCUGGGAGCUCUCUGGC
((((((...((((......))))))))))
>>__'BACTERIOPHAGE_LAMBDA_N-PROTEIN-NUTBOXB-RNA_COMPLEX_'_(PDB_00668)
GCCCUGAAAAAGGGC
((((((...))))))
>>__'GLUTAMINYL-TRNA_SYNTHETASE_MUTANT_D235N_COMPLEXED_WITH_GLUTAMINE_TRANSFER_RNA_'_(PDB_00669)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..(((.........)))((((((((...))))))))....(((((.......))))))))))).....
>>__'GLUTAMINYL-TRNA_SYNTHETASE_MUTANT_D235G_COMPLEXED_WITH_GLUTAMINE_TRANSFER_RNA_'_(PDB_00670)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..(((.........)))(((((((.....)))))))....(((((.......))))))))))).....
>>__'GLUTAMINYL-TRNA_SYNTHETASE_MUTANT_I129T_COMPLEXED_WITH_GLUTAMINE_TRANSFER_RNA_'_(PDB_00671)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..(((.........)))((((((.......))))))....(((((.......))))))))))).....
>>__'GLUTAMINYL-TRNA_SYNTHETASE_COMPLEXED_WITH_TRNA_AND_AN_AMINO_ACID_ANALOG_'_(PDB_00672)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..((((.......))))((((((((...))))))))....(((((.......))))))))))).....
>>__'INSIGHTS_INTO_EDITING_FROM_AN_ILE-TRNA_SYNTHETASE_STRUCTURE_WITH_TRNA(ILE)_AND_MUPIROCIN_'_(PDB_00673)
GGGCUUGUAGCUCAGGUGGUUAGAGCGCACCCCUGAUAAGGGUGAGGUCGGUGGUUCAAGUCCACUCAGGCCCAC
(((((((..((((.........))))(((((((.....)))))))....(((((.......))))))))))))..
>>__'INSIGHTS_INTO_EDITING_FROM_AN_ILE-TRNA_SYNTHETASE_STRUCTURE_WITH_TRNA(ILE)_AND_MUPIROCIN_'_(PDB_00674)
GGGCUUGUAGCUCAGGUGGUUAGAGCGCACCCCUGAUAAGGGUGAGGUCGGUGGUUCAAGUCCACUCAGGCCCAC
(((((((..((((.........))))(((((((.....)))))))....(((((.......))))))))))))..
>>__'SOLUTION_STRUCTURE_OF_THE_COMPLEX_FORMED_BY_THE_TWO_N-_TERMINAL_RNA-BINDING_DOMAINS_OF_NUCLEOLIN_AND_A_PRE-RRNA_TARGET_'_(PDB_00691)
GGAUGCCUCCCGAGUGCAUCC
((((((.........))))))
>>__'THE_STRUCTURE_OF_A_RIBOSOMAL_PROTEIN_S8/SPC_OPERON_MRNA_COMPLEX_'_(PDB_00702)
GGACGAUGGCGAAACUGCAUGAGGCAAUUCAUGCAAGUCCCUCGUCCGGACGAUGGCGAAACUGCAUGAGGCAAUUCAUGCAAGUCCCUCGUCC
((((((.((.((..((((((((......)))))).))))))))))))((((((.((.((..((((((((......)))))).))))))))))))
>>__'AVERAGE_SOLUTION_STRUCTURE_OF_A_PSEUDO-5\'-SPLICE_SITE_FROM_THE_NEGATIVE_REGULATOR_OF_SPLICING_OF_ROUS_SARCOMA_VIRUS_'_(PDB_00705)
GGGGAGUGGUUUGUAUCCUUCCC
((((((.((......))))))))
>>__'SOLUTION_STRUCTURE_OF_RESIDUES_907-929_FROM_ROUS_SARCOMA_VIRUS_'_(PDB_00706)
GGGGAGUGGUUUGUAUCCUUCCC
((((((.(((....)))))))))
>>__'HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR,_WITH_MG2+_BOUND_'_(PDB_00714)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
.(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_A_C75U_MUTANT_HEPATITIS_DELTA_VIRUS_RIBOZYME_PRECURSOR,_IN_CU2+_SOLUTION_'_(PDB_00715)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
.(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_THE_HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR,_WITH_C75U_MUTAION,_IN_COBALT_HEXAMMINE_SOLUTION_'_(PDB_00716)
AUGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
..(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'SOLUTION_STRUCTURE_OF_THE_S._CEREVISIAE_U6_INTRAMOLECULAR_STEM_LOOP_(ISL)_RNA_AT_PH_5.7_'_(PDB_00721)
GGUUCCCCUGCAUAAGGAUGAACC
((((((((((...))))).)))))
>>__'HIGH_RESOLUTION_STRUCTURE_OF_A_PICORNAVIRAL_INTERNAL_CIS-_ACTING_REPLICATION_ELEMENT_'_(PDB_00727)
GGUCAUCGUUGAGAAAACGAAACAGACGGUGGCC
((..(((((................)))))..))
>>__'NMR_STRUCTURE_OF_THE_VS_RIBOZYME_STEM-LOOP_V_RNA_IN_THE_ABSENCE_OF_MULTIVALENT_IONS._'_(PDB_00730)
GCGAGUUGACUACUCGC
((((((.....))))))
>>__'SACCHARIDE-RNA_RECOGNITION_IN_AN_AMINOGLYCOSIDE_ANTIBIOTIC-_RNA_APTAMER_COMPLEX,_NMR,_7_STRUCTURES_'_(PDB_00737)
GGCACGAGGUUUAGCUACACUCGUGCC
(((((((((((....))).))))))))
>>__'CRYSTAL_STRUCTURE_OF_CYSTEINYL-TRNA_SYNTHETASE_BINARY_COMPLEX_WITH_TRNACYS_'_(PDB_00742)
GGCGCGUUAACAAAGCGGUUAUGUAGCGGAUUGCAAAUCCGUCUAGUCCGGUUCGACUCCGGAACGCGCCUCCA
(((((((..(((.........))).((((((.....))))))....(((((.......))))))))))))....
>>__'CRYSTAL_STRUCTURE_OF_A_COMPLEX_BETWEEN_WT_BACTERIOPHAGE_MS2_COAT_PROTEIN_AND_AN_F5_APTAMER_RNA_STEMLOOP_WITH_2AMINOPURINE_SUBSTITUTED_AT_THE-10_POSITION_'_(PDB_00743)
CCGGGGGAUCACCACGGCGGGGGAUCACCACGG
((((.((....))))))(((.((....))))).
>>__'THE_STRUCTURE_OF_A_RIBOSOMAL_PROTEIN_L1-MRNA_COMPLEX_'_(PDB_00746)
GGGAGUGAAGGAGGCUCGCGAACUCGCGAAGCCGAGAAACUUCACUCCCGGGAGUGAAGGAGGCUCGCGAACUCGCGAAGCCGAGAAACUUCACUCCC
.(((((((((((((((((((....)))).)))))....))))))))))..(((((((((((((((((((....)))).)))))....)))))))))).
>>__'GUANINE_RIBOSWITCH_BOUND_TO_HYPOXANTHINE_'_(PDB_00749)
GGACAUAUAAUCGCGUGGAUAUGGCACGCAAGUUUCUACCGGGCACCGUAAAUGUCCGACUAUGUCC
(((((((...(((((((.[[..[[)))))))........((((((]]...]]))))))..)))))))
>>__'REOVIRUS_POLYMERASE_LAMBDA-3_LOCALIZED_BY_ELECTRON_CRYOMICROSCOPY_OF_VIRIONS_AT_7.6-A_RESOLUTION_'_(PDB_00753)
GGGGGUAGCCCCCCCC
.((.......))....
>>__'U1A_MUTANT/RNA_COMPLEX_+_GLYCEROL_'_(PDB_00754)
AAUCCAUUGCACGGAUUAAUCCAUUGCACUCCGGAUUUAAUCCAUUGCACGGAUU
.((((.......)))).(((((..........)))))...(((.......)))..
>>__'DESIGNED_HIV-1_TAR_BINDING_LIGAND_'_(PDB_00755)
GGCAGAUCUGAGCCUGGGAGCUCUCUGCC
((((((...((((......))))))))))
>>__'NMR_STRUCTURE_OF_A_SYNTHETIC_SMALL_MOLECULE,_RBT203,_BOUND_TO_HIV-1_TAR_RNA_'_(PDB_00756)
GGCAGAUCUGAGCCUGGGAGCUCUCUGCC
((((((...((((......))))))))))
>>__'NMR_STRUCTURE_OF_A_SYNTHETIC_SMALL_MOLECULE,_RBT158,_BOUND_TO_HIV-1_TAR_RNA_'_(PDB_00757)
GGCAGAUCUGAGCCUGGGAGCUCUCUGCC
((((((...((((......))))))))))
>>__'THE_STRUCTURAL_BASIS_FOR_RNA_SPECIFICITY_AND_CA2_INHIBITION_OF_AN_RNA-DEPENDENT_RNA_POLYMERASE_PHI6P2_CA2+_INHIBITION_COMPLEX_'_(PDB_00759)
UUCCUUCCUUCCGGGGGG
..((..[[..{{))]]}}
>>__'CRYSTAL_STRUCTURE_OF_THE_HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR,_WITH_C75U_MUTAION,_IN_EDTA_SOLUTION_'_(PDB_00760)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
.(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_THE_HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR,_WITH_C75U_MUTAION,_AND_MN2+_BOUND_'_(PDB_00761)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
.(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_THE_HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR,_WITH_C75U_MUTAION,_IN_BA2+_SOLUTION_'_(PDB_00762)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
.(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_THE_HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR,_WITH_C75U_MUTAION,_IN_IMIDAZOLE_AND_SR2+_SOLUTION_'_(PDB_00763)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
.(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_THE_WILD_TYPE_HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR,_IN_EDTA_SOLUTION_'_(PDB_00764)
GGCCGGCAUGGUCCCAGCCUCCUCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGCGAAUGGGAC
(((((((....[[[[[(((.[[...))))))))))]]...(((((..........)))))....]]]]].
>>__'CRYSTAL_STRUCTURE_OF_THE_HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRODUCT_WITH_C75U_MUTAION,_CLEAVED_IN_IMIDAZOLE_AND_MG2+_SOLUTIONS_'_(PDB_00765)
GGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_THE_HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR,_WITH_C75U_MUTAION,_IN_SR2+_SOLUTION_'_(PDB_00766)
AUGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
..(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_TRNA_NUCLEOTIDYLTRANSFERASE_COMPLEXED_WITH_A_PRIMER_TRNA_AND_AN_INCOMING_ATP_ANALOG_'_(PDB_00767)
GGCCAGGGGCGGUUCGAUUCCGCCCCUGGCCGGCCAGGGGCGGUUCGAUUCCGCCCCUGGCCACCAA
(((((((.(((.........))).)))))))(((((((.(((.........))).))))))).....
>>__'SOLUTION_STRUCTURE_OF_AN_RNA_STEM-LOOP_DERIVED_FROM_THE_3\'_CONSERVED_REGION_OF_EEL_LINE_UNAL2_'_(PDB_00798)
GGCUUUGGAUAAAAGCC
(((((((...)))))))
>>__'SOLUTION_STRUCTURE_OF_THE_EXTENDED_U6_ISL_AS_OBSERVED_IN_THE_U2/U6_COMPLEX_FROM_SACCHAROMYCES_CEREVISIAE_'_(PDB_00809)
GAGCAGUUCCCCUGCAUAAGGAUGAACCGUUC
((((((((((((((...))))).)))))))))
>>__'THE_STRUCTURE_OF_A_RIGOROUSLY_CONSERVED_RNA_ELEMENT_WITHIN_THE_SARS_VIRUS_GENOME_'_(PDB_00810)
GGAGUUCACCGAGGCCACGCGGAGUACGAUCGAGGGUACAGUGAAUU
..((((((((...(((((((((...)))..)).))))..))))))))
>>__'HIV-1_SUBTYPE_F_GENOMIC_RNA_DIMERIZATION_INITIATION_SITE_'_(PDB_00816)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'HIV-1_SUBTYPE_B_GENOMIC_RNA_DIMERIZATION_INITIATION_SITE_'_(PDB_00817)
CUUGCUGAAGCGCGCACGGCAAGCUUGCUGAAGCGCGCACGGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'HIV-1_SUBTYPE_A_GENOMIC_RNA_DIMERIZATION_INITIATION_SITE_'_(PDB_00818)
CUUGCUGAGGUGCACACAGCAAGCUUGCUGAGGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'SOLUTION_STRUCTURE_OF_AUCGCA_LOOP_'_(PDB_00825)
GGAGAUCGCACUCCA
(((((....))))).
>>__'A-RIBOSWITCH-ADENINE_COMPLEX_'_(PDB_00828)
CGCUUCAUAUAAUCCUAAUGAUAUGGUUUGGGAGUUUCUACCAAGAGCCUUAAACUCUUGAUUAUGAAGUG
(((((((((...(((((((.[[[.[[)))))))........((((((]]..]]]))))))..)))))))))
>>__'G-RIBOSWITCH-GUANINE_COMPLEX_'_(PDB_00829)
GGAUCAUAUAAUCGCGUGGAUAUGGCACGCAAGUUUCUACCGGGCACCGUAAAUGUCCGACUAUGGUC
.(((((((...(((((((.[[..[[)))))))........((((((]]...]]))))))..)))))))
>>__'HIV-1_DIS_RNA_SUBTYPE_F-_MN_SOAKED_'_(PDB_00831)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'HIV-1_DIS_RNA_SUBTYPE_F-_MPD_FORM_'_(PDB_00832)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'SOLUTION_STRUCTURE_OF_THE_SCYLV_P1-P2_FRAMESHIFTING_PSEUDOKNOT,_20_LOWEST_ENERGY_STRUCTURES_'_(PDB_00842)
AGUGGCGCCGACCACUUAAAAACACCGG
(((((..[[[.))))).........]]]
>>__'SOLUTION_STRUCTURE_OF_THE_SCYLV_P1-P2_FRAMESHIFTING_PSEUDOKNOT,_REGULARIZED_AVERAGE_STRUCTURE_'_(PDB_00843)
AGUGGCGCCGACCACUUAAAAACACCGG
(((((..[[[.))))).........]]]
>>__'NMR_STRUCTURE_OF_THE_APOB_MRNA_STEM-LOOP_AND_ITS_INTERACTION_WITH_THE_C_TO_U_EDITING_APOBEC1_COMPLEMENTARY_FACTOR_'_(PDB_00855)
GGAUAUAUGAUACAAUUUGAUCAGUAUAUCC
((((((.((((........))))..))))))
>>__'SOLUTION_STRUCTURE_OF_THE_P2B-P3_PSEUDOKNOT_FROM_HUMAN_TELOMERASE_RNA_'_(PDB_00857)
GGGCUGUUUUUCUCGCUGACUUUCAGCCCCAAACAAAAAAGUCAGCA
[[[[[[........(((((((((]]]]]]........))))))))).
>>__'SOLUTION_STRUCTURE_OF_THE_VS_RIBOZYME_STEM-LOOP_V_IN_THE_PRESENCE_OF_MGCL2_'_(PDB_00858)
GCGAGUUGACUACUCGC
((((((.....))))))
>>__'SOLUTION_STRUCTURE_OF_THE_NEUROSPORA_VS_RIBOZYME_STEM-LOOP_V_IN_THE_PRESENCE_OF_MGCL2_WITH_MODELING_OF_BOUND_MANGANESE_IONS_'_(PDB_00859)
GCGAGUUGACUACUCGC
((((((.....))))))
>>__'NMR_STRUCTURE_OF_THE_APOB_MRNA_STEM-LOOP_AND_ITS_INTERACTION_WITH_THE_C_TO_U_EDITING_APOBEC1_COMPLEMENTARY_FACTOR_'_(PDB_00860)
GGAUAUAUGAUACAAUUUGAUCAGUAUAUCC
(((((((((((........)))).)))))))
>>__'NMR_STRUCTURE_OF_THE_APOB_MRNA_STEM-LOOP_AND_ITS_INTERACTION_WITH_THE_C_TO_U_EDITING_APOBEC1_COMPLEMENTARY_FACTOR_'_(PDB_00861)
GGAUAUAUGAUAUAAUUUGAUCAGUAUAUCC
((((((.((((........))))..))))))
>>__'NMR_STRUCTURE_OF_THE_APOB_MRNA_STEM-LOOP_AND_ITS_INTERACTION_WITH_THE_C_TO_U_EDITING_APOBEC1_COMPLEMENTARY_FACTOR_'_(PDB_00862)
GGAUAUAUGAUAUAAUUUGAUCAGUAUAUCC
((((((.((((........))))..))))))
>>__'SOLUTION_STRUCTURE_OF_THE_CENTRAL_REGION_OF_THE_HUMAN_GLUR-_B_R/G_PRE-MRNA_'_(PDB_00865)
GGUAACAAUAUGCUAAAUGUUGUUACC
((((((((((((...))))))))))))
>>__'STRUCTURAL_BASIS_FOR_RECOGNITION_OF_UUUOH_3\'-TERMINII_OF_NASCENT_RNA_POL_III_TRANSCRIPTS_BY_LA_AUTOANTIGEN_'_(PDB_00867)
UGCUGUUUUUGCUGUUUU
.((.((....)).))...
>>__'RO_AUTOANTIGEN_COMPLEXED_WITH_RNAS_'_(PDB_00868)
GCUGGUCCGAUUGACUAGCCGCUGGUCCGAUUGACUAGCCUCCGAGGUCCGA
(((((((.....))))))).(((((((.....))))))).............
>>__'HIV-1_DIS_RNA_SUBTYPE_F-_ZN_SOAKED_'_(PDB_00869)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'3\'-END_SPECIFIC_RECOGNITION_OF_HISTONE_MRNA_STEM-LOOP_BY_3\'-_EXONUCLEASE_'_(PDB_00883)
GGCUCUUUUCAGAGCCGGCUCUUUUCAGAGCCAAAA
((((((....))))))((((((....))))))....
>>__'SOLUTION_STRUCTURE_OF_BIV_TAR_HAIRPIN_COMPLEXED_TO_JDV_TAT_ARGININE-RICH_MOTIF_'_(PDB_00884)
GGCUCGUGUAGCUCAUUAGCUCCGAGCC
.(((((...((((....)))).))))).
>>__'HIV-1_DIS_RNA_SUBTYPE_F-_MONOCLINIC_FORM_'_(PDB_00886)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'MS2_COAT_PROTEIN/RNA_COMPLEX_'_(PDB_00887)
UGAGGAUCACCCAUGAGGAUCACCCA
((.((....))))((.((....))))
>>__'RNA_BACTERIOPHAGE_MS2_COAT_PROTEIN/RNA_COMPLEX_'_(PDB_00888)
AUGAGGAUUACCCAUGUGAGGAUUACCCA
(((.((....))))).((.((....))))
>>__'STRUCTURE_OF_BACTERIOPHAGE_COAT_PROTEIN-LOOP_RNA_COMPLEX_'_(PDB_00889)
GGAUCACCGGAUCACC
((....))((....))
>>__'STRUCTURE_OF_BACTERIOPHAGE_COAT_PROTEIN-LOOP_RNA_COMPLEX_'_(PDB_00890)
ACAUGAGGAUCACCCAUGUACAUGAGGAUCACCCAUGU
(((((.((....)))))))(((((.((....)))))))
>>__'CONFORMATIONAL_CHANGE_OF_PSEUDOURIDINE_55_SYNTHASE_UPON_ITS_ASSOCIATION_WITH_RNA_SUBSTRATE_'_(PDB_00891)
GGCCACGGUUCGAAUCCGUGGCGGCCACGGUUCGAAUCCGUGGC
((((((((.......))))))))(((((((.......)))))))
>>__'STRUCTURAL_BASIS_FOR_RECOGNITION_OF_UUUOH_3\'-TERMINII_OF_NASCENT_RNA_POL_III_TRANSCRIPTS_BY_LA_AUTOANTIGEN_'_(PDB_00896)
UGCUGUUUUUGCUGUUUU
.((.((....)).))...
>>__'GLUTAMINYL-TRNA_SYNTHETASE_COMPLEXED_TO_GLUTAMINE_AND_2\'DEOXY_A76_GLUTAMINE_TRNA_'_(PDB_00901)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..((((.......)))).(((((((...))))))).....(((((.......))))))))))).....
>>__'COUPLING_OF_ACTIVE_SITE_MOTIONS_AND_RNA_BINDING_'_(PDB_00902)
GGCAACGGUUCGAUCCCGUUGC
.(((((((.......)))))))
>>__'IF2,_IF1,_AND_TRNA_FITTED_TO_CRYO-EM_DATA_OF_E._COLI_70S_INITIATION_COMPLEX_'_(PDB_00903)
GCGGAUUUAGCUCAGUUGGGAGAGCGCCAGACUGAAGAUCUGGAGGUCCUGUGUUCGAUCCACAGAAUUCGCACCA
(((((((..((((........))))((((((.......))))))....(((((.......))))))))))))....
>>__'RNA_STEMLOOP_FROM_BACTERIOPHAGE_QBETA_COMPLEXED_WITH_AN_N87S_MUTANT_MS2_CAPSID_'_(PDB_00905)
UGUCUAAGACAG
((((...)))).
>>__'CRYSTAL_STRUCTURE_OF_A_LUTEOVIRAL_RNA_PSEUDOKNOT_AND_MODEL_FOR_A_MINIMAL_RIBOSOMAL_FRAMESHIFTING_MOTIF_'_(PDB_00918)
GCGGCACCGUCCGCUCAAACAAACGG
((((..[[[.)))).........]]]
>>__'TAR_RNA_RECOGNITION_BY_A_CYCLIC_PEPTIDOMIMETIC_OF_TAT_PROTEIN_'_(PDB_00921)
GGCUCGUGUAGCUCAUUAGCUCCGAGCC
((((((...((((....)))).))))))
>>__'DISSECTING_THE_ROLES_OF_A_STRICTLY_CONSERVED_TYROSINE_IN_SUBSTRATE_RECOGNITION_AND_CATALYSIS_BY_PSEUDOURIDINE_55_SYNTHASE_'_(PDB_00923)
CCACGGUUCGAAUCCGUGGC
((((((.......)))))).
>>__'STRUCTURE_OF_HUMAN_TRYPTOPHANYL-TRNA_SYNTHETASE_IN_COMPLEX_WITH_TRNA(TRP)_'_(PDB_00926)
GACCUCGUGGCGCAAUGGUAGCGCGUCUGACUCCAGAUCAGAAGGUUGCGUGUUCGAAUCACGUCGGGGUCA
((.((((..(((((.....)))))...((((.....)))).......(((((.......))))))))).)).
>>__'CRYSTAL_STRUCTURE_(I)_OF_NOVA-1_KH1/KH2_DOMAIN_TANDEM_WITH_25_NT_RNA_HAIRPIN_'_(PDB_00927)
CGCGGAUCAGUCACCCAAGCGCG
((((((.........))))))..
>>__'CRYSTAL_STRUCTURE_(II)_OF_NOVA-1_KH1/KH2_DOMAIN_TANDEM_WITH_25NT_RNA_HAIRPIN_'_(PDB_00928)
CUCGCGGAUCAGUCACCCAAGCGAG
((((((((.........))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_C27A_SCYLV_P1-P2_FRAMESHIFTING_PSEUDOKNOT,_20_LOWEST_ENERGY_STRUCTURES_'_(PDB_00930)
AGUGGCGCCGACCACUUAAAAACAACGG
(((((..[[[.))))).........]]]
>>__'SOLUTION_STRUCTURE_OF_THE_C27A_SCYLV_P1-P2_FRAMESHIFTING_PSEUDOKNOT,_AVERAGE_STRUCTURE_'_(PDB_00931)
AGUGGCGCCGACCACUUAAAAACAACGG
(((((..[[[.))))).........]]]
>>__'RNA_STEMLOOP_OPERATOR_FROM_BACTERIOPHAGE_QBETA_COMPLEXED_WITH_AN_N87S,E89K_MUTANT_MS2_CAPSID_'_(PDB_00940)
GUCUAAGACAAG
(((...)))...
>>__'RNA_STEMLOOP_FROM_BACTERIOPHAGE_MS2_COMPLEXED_WITH_AN_N87S,_E89K_MUTANT_MS2_CAPSID_'_(PDB_00941)
AUGAGGAUUACCCAUGUGAGGAUUACCCAU
(((.((....))))).((.((....)))).
>>__'MS2_WILD-TYPE_RNA_STEMLOOP_COMPLEXED_WITH_AN_N87S_MUTANT_MS2_CAPSID_'_(PDB_00942)
AUGAGGAUUACCCAUGAUGAGGAUUACCCAU
(((.((....))))).(((.((....)))))
>>__'CRYSTAL_STRUCTURE_OF_STAPHYLOCOCCUS_AUREUS_TRNA_ADENOSINE_DEAMINASE,_TADA,_IN_COMPLEX_WITH_RNA_'_(PDB_00943)
UUGACUACGGAUCAAUUGACUACGGAUCAAGACUACGGUUUGACUACGGAUCAA
(((((.....)))))(((((.....))))).........(((((.....)))))
>>__'GUANINE_RIBOSWITCH_C74U_MUTANT_BOUND_TO_2,6-DIAMINOPURINE_'_(PDB_00944)
GACAUAUAAUCGCGUGGAUAUGGCACGCAAGUUUCUACCGGGCACCGUAAAUGUCCGAUUAUGUC
((((((.....(((((.[[[.[[)))))..........((((((]]..]]]))))))..))))))
>>__'COMPLETE_RNA_POLYMERASE_II-RNA_INHIBITOR_COMPLEX_'_(PDB_00945)
CAGCACUGAUUGCGGUCGAGGUAGCUUGAUG
.((((.....))))((((((....)))))).
>>__'RNA_RECOGNITION_BY_THE_VTS1_SAM_DOMAIN_'_(PDB_00948)
GGAGGCUCUGGCAGCUUUC
(((((((.....)))))))
>>__'STRUCTURE_OF_THE_SMAUG_RECOGNITION_RNA_ELEMENT_'_(PDB_00949)
GGAGGCUCUGGCAGCUUUC
(((((((.....)))))))
>>__'STRUCTURE_OF_HIV-1(LAI)_GENOMIC_RNA_DIS_'_(PDB_00950)
CUUGCUGAAGCGCGCACGGCAAGCUUGCUGAAGCGCGCACGGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'STRUCTURE_OF_HIV-1(MAL)_GENOMIC_RNA_DIS_'_(PDB_00951)
CUUGCUGAGGUGCACACAGCAAGCUUGCUGAGGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'CRYSTAL_STRUCTURE_OF_E._COLI_5-METHYLURIDINE_METHYLTRANSFERASE_RUMA_IN_COMPLEX_WITH_RIBOSOMAL_RNA_SUBSTRATE_AND_S-ADENOSYLHOMOCYSTEINE._'_(PDB_00961)
AGCGAAAUUCCUUGUCGGGUAAGUUCCGACAGCGAAAUUCCUUGUCGGGUAAGUUCCGAC
.............(((((.......))))).............(((((.......)))))
>>__'MS2_(N87A_MUTANT)-_RNA_HAIRPIN_COMPLEX_'_(PDB_00963)
AUGAGGAUUACCCAUUGAGGAUUACCCA
(((.((....)))))((.((....))))
>>__'MS2_(N87AE89K_MUTANT)-_RNA_HAIRPIN_COMPLEX_'_(PDB_00964)
ACAUGAGGAUUACCCAUGUCAUGAGGAUUACCCAUG
(((((.((....)))))))..((.........))..
>>__'MS2_(N87AE89K_MUTANT)-_VARIANT_QBETA_RNA_HAIRPIN_COMPLEX_'_(PDB_00965)
UGUCUAAGACUGGUCUAAGAC
.(((...)))..(((...)))
>>__'MS2_(N87AE89K_MUTANT)-_QBETA_RNA_HAIRPIN_COMPLEX_'_(PDB_00966)
UGUCUAAGACAGUGUCUAAGACA
.(((...)))..((((...))))
>>__'MS2-RNA_HAIRPIN_(5BRU-5)_COMPLEX_'_(PDB_00968)
CAUGAGGAUUACCCAUGCAUGAGGAUUACCCAUG
((((.((....))))))((((.((....))))))
>>__'MS2-RNA_HAIRPIN_(2ONE-5)_COMPLEX_VIRUS_'_(PDB_00970)
CAUGAGGAUUACCCAUGCAUGAGGAUUACCCAUG
((((.((....))))))..((.((....))))..
>>__'MS2-RNA_HAIRPIN_(2THIOURACIL-5)_COMPLEX_'_(PDB_00971)
CAUGAGGAUUACCCAUGUGAGGAUUACCCA
((((.((....))))))((.((....))))
>>__'MS2-RNA_HAIRPIN_(2SU-5-6)_COMPLEX_'_(PDB_00972)
CAUGAGGAUUACCCAUGUGAGGAUUACCCA
((((.........))))((.........))
>>__'MS2-RNA_HAIRPIN_(A-5)_COMPLEX_'_(PDB_00973)
AUGAGGAUAACCCAUGAGGAUAACCCA
.((.((....))))((.((....))))
>>__'MS2-RNA_HAIRPIN_(G-5)_COMPLEX_'_(PDB_00974)
AUGAGGAUGACCCAUUGAGGAUGACCCA
(((.((....)))))((.((....))))
>>__'REFINEMENT_OF_P4_STEMLOOP_STRUCTURE_USING_RESIDUAL_DIPOLAR_COUPLING_DATA_'_(PDB_00975)
GGAAGUCCGGUCUUCGGACCGGCUUCC
.((((.(((((......))))))))).
>>__'REFINEMENT_OF_RNASE_P_P4_STEMLOOP_STRUCTURE_USING_RESIDUAL_DIPOLAR_COUPLINGS-_COBALT(III)_HEXAMMINE_COMPLEX_STRUCTURE_'_(PDB_00977)
GGAAGUCCGGUCUUCGGACCGGCUUCC
(((((.(((((......))))))))))
>>__'SOLUTION_RNA_STRUCTURE_OF_LOOP_REGION_OF_THE_HIV-1_DIMERIZATION_INITIATION_SITE_IN_THE_KISSING-LOOP_DIMER_'_(PDB_00988)
GCUGAAGUGCACACGGCGCUGAAGUGCACACGGC
((((..[[[[[[.))))((((..]]]]]].))))
>>__'SOLUTION_RNA_STRUCTURE_MODEL_OF_THE_HIV-1_DIMERIZATION_INITIATION_SITE_IN_THE_KISSING-LOOP_DIMER_'_(PDB_00990)
GGGUCGGCUUGCUGAAGUGCACACGGCAAGAGGCGACCCGGGUCGGCUUGCUGAAGUGCACACGGCAAGAGGCGACCC
(((((((((((((((.[[[[[[)))))))))..))))))((((((((((((((..]]]]]].))))))))..))))))
>>__'COCRYSTAL_STRUCTURE_OF_AN_RNA_SULFURATION_ENZYME_MNMA_AND_TRNA-GLU_IN_THE_PRE-REACTION_STATE_'_(PDB_00999)
GUCCCCUUCGUCUAGAGGCCCAGGACACCGCCCUUUCACGGCGGUAACAGGGGUUCGAAUCCCCUAGGGG
..((.....(((((.......)))))(((((((.....)))))))....((((.......))))...)).
>>__'STRUCTURE_OF_HUMAN_TRYPTOPHANYL-TRNA_SYNTHETASE_IN_COMPLEX_WITH_TRNA(TRP)_'_(PDB_01002)
GACCUCGUGGCGCAAUGGUAGCGCGUCUGACUCCAGAUCAGAAGGUUGCGUGUUCGAAUCACGUCGGGGUCACCA
(((((((....(((.....)))...((((((.....)))))).....(((((.......))))))))))))....
>>__'COMPLEX_STRUCTURE_OF_CCA_ADDING_ENZYME_WITH_MINI-HELIX_LACKING_CCA_'_(PDB_01003)
GGCCCGGGGCGGUUCGAUUCCGCCCUGGGCCA
(((((((..(((.......)))..))))))).
>>__'COMPLEX_STRUCTURE_OF_CCA-ADDING_ENZYME_WITH_TRNAMINIDC_'_(PDB_01004)
GGCCCGGGGCGGUUCGAUUCCGCCCUGGGCCAC
((((((((((((.......))))))))))))..
>>__'COMPLEX_STRUCTURE_OF_CCA-ADDING_ENZYME_WITH_TRNAMINIDC_AND_CTP_'_(PDB_01005)
GGCCCGGGGCGGUUCGAUUCCGCCCUGGGCCAC
((((((((((((.......))))))))))))..
>>__'COMPLEX_STRUCTURE_OF_CCA-ADDING_ENZYME_WITH_TRNAMINIDCC_'_(PDB_01006)
GGCCCGGGGCGGUUCGAUUCCGCCCUGGGCCACC
((((((((((((.......))))))))))))...
>>__'COMPLEX_STRUCTURE_OF_CCA-ADDING_ENZYME_WITH_TRNAMINIDCC_AND_ATP_'_(PDB_01007)
GGCCCGGGGCGGUUCGAUUCCGCCCUGGGCCACC
((((((((((((.......))))))))))))...
>>__'COMPLEX_STRUCTURE_OF_CCA-ADDING_ENZYME_WITH_TRNAMINICCA_'_(PDB_01008)
GGCCCGGGGCGGUUCGAUUCCGCCCUGGGCCACCA
((((((((((((.......))))))))))))....
>>__'CRYSTAL_STRUCTURE_OF_ARCHAEOGLOBUS_FULGIDUS_O-PHOSPHOSERYL-_TRNA_SYNTHETASE_COMPLEXED_WITH_TRNACYS_AND_O-PHOSPHOSERINE_'_(PDB_01009)
GCCAGGGUGGCAGAGGGGCUUUGCGGCGGACUGCAGAUCCGCUUUACCCCGGUUCGAAUCCGGGCCCUGGC
((((((([[(((]].......)))..((((.......))))......(((((.......))))))))))))
>>__'CRYSTAL_STRUCTURE_OF_ARCHAEOGLOBUS_FULGIDUS_O-PHOSPHOSERYL-_TRNA_SYNTHETASE_COMPLEXED_WITH_TRNACYS_'_(PDB_01010)
GCCAGGGUGGCAGAGGGGCUUUGCGGCGGACUGCAGAUCCGCUUUACCCCGGUUCGAAUCCGGGCCCUGGC
..((((([[(((]].......)))..(((((.....)))))......(((((.......))))))))))..
>>__'CRYSTAL_STRUCTURE_OF_ARCHAEOGLOBUS_FULGIDUS_O-PHOSPHOSERYL-_TRNA_SYNTHETASE_E418N/E420N_MUTANT_COMPLEXED_WITH_TRNAOPAL_AND_O-PHOSPHOSERINE_("OPAL_COMPLEX")_'_(PDB_01011)
GCCAGGGUGGCAGAGGGGCUUUGCGGCGGACUUCAGAUCCGCUUUACCCCGGUUCGAAUCCGGGCCCUGGC
(((((((..(((.........))).(((((.......))))).....(((((.......))))))))))))
>>__'CRYSTAL_STRUCTURE_OF_ARCHAEOGLOBUS_FULGIDUS_O-PHOSPHOSERYL-_TRNA_SYNTHETASE_E418N/E420N_MUTANT_COMPLEXED_WITH_TRNAAMBER_AND_O-PHOSPHOSERINE_("AMBER_COMPLEX")_'_(PDB_01012)
GCCAGGGUGGCAGAGGGGCUUUGCGGCGGACUCUAGAUCCGCUUUACCCCGGUUCGAAUCCGGGCCCUGGC
(((((((..(((.........))).(((((.......))))).....(((((.......))))))))))))
>>__'COMPLEX_STRUCTURE_OF_CCA-ADDING_ENZYME,_MINI-DCC_AND_CTP_'_(PDB_01013)
GGCCCGGGGCGGUUCGAUUCCGCCCUGGGCCACC
((((((((((((.......))))))))))))...
>>__'GUANINE_RIBOSWITCH_A21U,_U75A_MUTANT_BOUND_TO_HYPOXANTHINE_'_(PDB_01020)
GGACAUUUAAUCGCGUGGAUAUGGCACGCAAGUUUCUACCGGGCACCGUAAAUGUCCGACAAUGUCCA
.((((((...(((((((.[[..[[)))))))........((((((]]...]]))))))..))))))..
>>__'GUANINE_RIBOSWITCH_A21G,_U75C_MUTANT_BOUND_TO_HYPOXANTHINE_'_(PDB_01021)
GGACAUGUAAUCGCGUGGAUAUGGCACGCAAGUUUCUACCGGGCACCGUAAAUGUCCGACCAUGUCCA
.((((((...(((((((.[[..[[)))))))........((((((]]...]]))))))..))))))..
>>__'GUANINE_RIBOSWITCH_U22A,_A52U_MUTANT_BOUND_TO_HYPOXANTHINE_'_(PDB_01022)
GGACAUAAAAUCGCGUGGAUAUGGCACGCAAGUUUCUUCCGGGCACCGUAAAUGUCCGACUAUGUCCA
(((((((.....(((((.[[..[[)))))..........((((((]]...]]))))))..))))))).
>>__'GUANINE_RIBOSWITCH_U22C,_A52G_MUTANT_BOUND_TO_HYPOXANTHINE_'_(PDB_01023)
GGACAUACAAUCGCGUGGAUAUGGCACGCAAGUUUCUGCCGGGCACCGUAAAUGUCCGACUAUGUCCA
(((((((...(((((((.[[..[[)))))))........((((((]]...]]))))))..))))))).
>>__'GUANINE_RIBOSWITCH_U47C_MUTANT_BOUND_TO_HYPOXANTHINE_'_(PDB_01024)
GGACAUAUAAUCGCGUGGAUAUGGCACGCAAGCUUCUACCGGGCACCGUAAAUGUCCGACUAUGUCCA
(((((((.....(((((.[[..[[)))))..........((((((]]...]]))))))..))))))).
>>__'STRUCTURE_OF_THE_SRE_RNA_'_(PDB_01025)
GGAGAGGCUCUGGCAGCUUUUCC
(((((((((.....)))))))))
>>__'STRUCTURE_OF_THE_SAM_DOMAIN_OF_VTS1P_IN_COMPLEX_WITH_RNA_'_(PDB_01026)
GGAGAGGCUCUGGCAGCUUUUCC
(((((((((.....)))))))))
>>__'NMR_SOLUTION_OF_HIV-1_LAI_KISSING_COMPLEX_'_(PDB_01040)
GGUUGCUGAAGCGCGCACGGCAACGGUUGCUGAAGCGCGCACGGCAAC
.(((((((..[[[[[[.))))))).(((((((..]]]]]].)))))))
>>__'SOLUTION_NMR_STRUCTURE_OF_DOMAIN_5_FROM_THE_PYAIELLA_LITTORALIS_(PL)_GROUP_II_INTRON_'_(PDB_01042)
GAGCCGUGUGCGAUGAAAGUCGCAAGCACGGUUC
((((((((.(((((....)))))...))))))))
>>__'CRYSTAL_STRUCTURE_OF_AA-AGO_WITH_EXTERNALLY-BOUND_SIRNA_'_(PDB_01044)
AGACAGCAUAUAUGCUGUCUUUAGACAGCAUAUAUGCUGUCUUU
.((((((((((.((((((......)))))).))))))))))...
>>__'HIV-1_DIS_KISSING-LOOP_IN_COMPLEX_WITH_NEAMINE_'_(PDB_01046)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'HIV-1_DIS_KISSING-LOOP_IN_COMPLEX_WITH_NEOMYCIN_'_(PDB_01047)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'HIV-1_DIS_KISSING-LOOP_IN_COMPLEX_WITH_RIBOSTAMYCIN_'_(PDB_01048)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'HIV-1_DIS_KISSING-LOOP_IN_COMPLEX_WITH_LIVIDOMYCIN_'_(PDB_01049)
CUUGCUGAAGUGCACACAGCAAGCUUGCUGAAGUGCACACAGCAAG
(((((((..[[[[[[.)))))))(((((((..]]]]]].)))))))
>>__'SOLUTION_STRUCTURE_OF_A_CONSERVED_RNA_HAIRPIN_OF_EEL_LINE_UNAL2_'_(PDB_01050)
GGUUGUACGUCGCUUUGGAUAAAAGCGUCUGCGACC
((((((..(((((((.......))))))).))))))
>>__'THE_STRUCTURE_OF_STEM_LOOP_IV_OF_TETRAHYMENA_TELOMERASE_RNA_'_(PDB_01051)
GAGACUAUCGACAUUUGAUACACUAUUUAUCAAUGGAUGUCUC
(((((......(((..(((((.....))))).)))...)))))
>>__'CRYSTAL_STRUCTURE_OF_RNASE_Z/TRNA(THR)_COMPLEX_'_(PDB_01053)
GCUUCCAUAGCUCAGCAGGUAGAGCGUCAGCGGUUCGAGCCCGCUUGGAAGCU
(((((((..((((........))))...(((((.......)))))))))))).
>>__'SOLUTION_STRUCTURE_OF_THE_HELIX_II_TEMPLATE_BOUNDARY_ELEMENT_FROM_TETRAHYMENA_TELOMERASE_RNA_'_(PDB_01056)
GGCAGAUCUGUAAUAGAACUGCC
(((((((((.....)))))))))
>>__'A_DUAL_MODE_OF_RNA_RECOGNITION_BY_THE_RBMY_PROTEIN_'_(PDB_01057)
GGACUGUCCACAAGACAGUCC
((((((((.....))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_ANTICODON_LOOP_OF_S._POMBE_TRNAI_INCLUDING_THE_NATURALLY_OCCURRING_N6-THREONYL_ADENINE_'_(PDB_01058)
ACGGGCUCAUAACCCGU
(((((((...)))))))
>>__'NMR_STRUCTURE_OF_THE_AQUIFEX_AEOLICUS_TMRNA_PSEUDOKNOT_PK1_'_(PDB_01059)
GGGGUGGCUCCCCUAACAGCCG
((((.[[[.)))).....]]].
>>__'MODIFIED_PYRIMIDINES_SPECIFICALLY_BIND_THE_PURINE_RIBOSWITCH_'_(PDB_01066)
GGACAUAUAAUCGCGUGGAUAUGGCACGCAAGUUUCUACCGGGCACCGUAAAUGUCCGAUUAUGUCCU
(((((((...(((((((.[[..[[)))))))........((((((]]...]]))))))..))))))).
>>__'RNA_RECOGNITION_AND_CLEAVAGE_BY_AN_SPLICING_ENDONUCLEASE_'_(PDB_01074)
GCGACCGACCAUAGCUGCUGCAGCGGUCAAAGGUCGCGCGACCGACCAUAGCUGCAUGCAGCGGUCAAAGGUCGC
.(((((((((...((((...))))))))...))))).((((((((((...((........))))))...))))))
>>__'TRANSLOCATION_OF_A_TRNA_WITH_AN_EXTENDED_ANTICODON_THROUGH_THE_RIBOSOME_'_(PDB_01084)
GGCCAGACUCCCGAAUCUGGCC
(((((((........)))))))
>>__'SOLUTION_STRUCTURE_OF_A_PURINE_RICH_HEXALOOP_HAIRPIN_BELONGING_TO_PGY/MDR1_MRNA_AND_TARGETED_BY_ANTISENSE_OLIGONUCLEOTIDES_'_(PDB_01086)
GAGGUCGGGAUGGAUCUC
((((((......))))))
>>__'SOLUTION_STRUCTURE_OF_THE_TETRAHYMENA_TELOMERASE_RNA_STEM_IV_TERMINAL_LOOP_'_(PDB_01097)
GGCGAUACACUAUUUAUCGCC
((((((((.....))))))))
>>__'STRUCTURE_OF_THE_AAGU_TETRALOOP_'_(PDB_01108)
GGCGUGAUCAAGUGAUCGCGCC
(((((((((....)))))))))
>>__'CRYSTAL_STRUCTURE_OF_AN_E._COLI_THI-BOX_RIBOSWITCH_BOUND_TO_THIAMINE_PYROPHOSPHATE,_MANGANESE_IONS_'_(PDB_01111)
GCGACUCGGGGUGCCCUCGUGAAGGCUGAGAAAACCCGUAACCUGAUCUGGAUAAUGCCAGCGAGGGAAGUCGCA
((((((((((((((((......))))......)))))).(((((((.((((......))))))))))))))))).
>>__'CRYSTAL_STRUCTURE_OF_AN_E._COLI_THI-BOX_RIBOSWITCH_BOUND_TO_THIAMINE_PYROPHOSPHATE,_CALCIUM_IONS_'_(PDB_01112)
GCGACUCGGGGUGCCCUGCGUGAAGGCUGAGAAAACCCGUAACCUGAUCUGGAUAAUCCAGCGAGGGAAGUCGCA
((((((((((((((((.......))))......)))))).(((((((.((((.....))))))))))))))))).
>>__'CRYSTAL_STRUCTURE_OF_AN_E._COLI_THI-BOX_RIBOSWITCH_BOUND_TO_THIAMINE_PYROPHOSPHATE,_BARIUM_IONS_'_(PDB_01113)
GCGACUCGGGGUGCCCUCGUGAAGGCUGAGAAAACCCGUAACCUGAUCUGGAUAAUGCCAGCGAGGGAAGUCGCA
((((((((((((((((......))))......)))))).(((((((.((((......))))))))))))))))).
>>__'CRYSTAL_STRUCTURE_OF_AN_E._COLI_THI-BOX_RIBOSWITCH_BOUND_TO_THIAMINE_MONOPHOSPHATE_'_(PDB_01114)
GCGACUCGGGGUGCCCUGCGUGAAGGCUGAGAAAACCCGUAACCUGAUCUGGAUAAUGCCAGCGAGGGAAGUCGCA
((((((((((((((((.......))))......)))))).(((((((.((((......))))))))))))))))).
>>__'CRYSTAL_STRUCTURE_OF_AN_E._COLI_THI-BOX_RIBOSWITCH_BOUND_TO_BENFOTIAMINE_'_(PDB_01115)
GCGACUCGGGGUGCCCUGCAAGGCUGAGAAAACCCGUAUACCUGACUGGAUAAUGCCAGCGUAGGGAAGUCGCA
((((((((((((((((....))))......))))))...((((((((((......)))))).)))).)))))).
>>__'CRYSTAL_STRUCTURE_OF_AN_E._COLI_THI-BOX_RIBOSWITCH_BOUND_TO_PYRITHIAMINE_'_(PDB_01116)
GCGACUCGGGGUGCCCGCGUAAGGCUGAGAAAACCCGUAACCUGAUGGAUAAUCCAGAGGGAAGUCGCA
((((((((((((((((.....))))......)))))).(((((..............))))))))))).
>>__'CRYSTAL_STRUCTURE_OF_AN_H/ACA_BOX_RNP_FROM_PYROCOCCUS_FURIOSUS_'_(PDB_01118)
GGGUCCGCCUUGAUGCCCGGGUGAAAGCAUGAUCCCGGGUAAUAUGGCGGACCCACA
(((((((((.....((((((((((......)))))))))).....)))))))))...
>>__'CRYSTAL_STRUCTURE_OF_PSEUDOURIDINE_SYNTHASE_RLUA:_INDIRECT_SEQUENCE_READOUT_THROUGH_PROTEIN-INDUCED_RNA_STRUCTURE_'_(PDB_01126)
GAGGGGAUGAAAAUCCCCUCGAGGGGAUGAAAAUCCCCUCGAGGGGAUGAAAAUCCCCUCGAGGGGAUGAAAUCCCCUC
(((((((......)))))))(((((((......)))))))(((((((......)))))))(((((((.....)))))))
>>__'CRYSTAL_STRUCTURE_OF_IRON_REGULATORY_PROTEIN_1_IN_COMPLEX_WITH_FERRITIN_H_IRE-RNA_'_(PDB_01130)
GUUCUUGCUUCAACAGUGUUUGAACGGAACGUUCUUGCUUCAACAGUGUUUGAACGGAAC
(((((...(((((......))))).)))))(((((...(((((......))))).)))))
>>__'SOLUTION_STRUCTURE_OF_THE_APICAL_STEM-LOOP_OF_THE_HUMAN_HEPATITIS_B_VIRUS_ENCAPSIDATION_SIGNAL_'_(PDB_01133)
GGCCUCCAAGCUGUGCCUUGGGUGGCC
((((((((((......)))))).))))
>>__'PHENYLALANYL-TRNA_SYNTHETASE_FROM_THERMUS_THERMOPHILUS_COMPLEXED_WITH_TRNA_AND_A_PHENYLALANYL-ADENYLATE_ANALOG_'_(PDB_01134)
GCCGAGGUAGCUCAGUUGGUAGAGCAUGCGACUGAAAAUCGCAGUGUCCGCGGUUCGAUUCCGCGCCUCGGCACCA
(((((((....((........))...((((((.....)))))).....((((.........)))))))))))....
>>__'MS2-RNA_HAIRPIN_(C-7)_COMPLEX_'_(PDB_01135)
AUGAGGCUCACCCAUGUGAGGCUCACCCA
(((.((....))))).((.((....))))
>>__'MS2-RNA_HAIRPIN_(4ONE-5)_COMPLEX_'_(PDB_01136)
AUGAGGAUUACCCAUAUGAGGAUUACCCAU
.((.((....))))..((.((....)))).
>>__'MS2-RNA_HAIRPIN_(C-10)_COMPLEX_'_(PDB_01137)
UGCGGAUCACCCAUGCGGAUCACCCA
((.((....))))((.((....))))
>>__'MS2-RNA_HAIRPIN_(G-10)_COMPLEX_'_(PDB_01138)
AUCGCGAUUACGGAUCGCGAUUACGG
(((.((....)))))..((....)).
>>__'STRUCTURAL_BASIS_OF_RSMA/CSRA_RNA_RECOGNITION:_STRUCTURE_OF_RSME_BOUND_TO_THE_SHINE-DALGARNO_SEQUENCE_OF_HCNA_MRNA_'_(PDB_01145)
GGGCUUCACGGAUGAAGCCCGGGCUUCACGGAUGAAGCCC
(((((((......)))))))(((((((......)))))))
>>__'MODEL_FOR_THIOSTREPTON_BINDING_TO_THE_RIBOSOMAL_L11-RNA_'_(PDB_01146)
GCUGGGAUGUUGGCUUAGAAGCAGCCAUCAUUUAAAGAGUGCGUAACAGCUCACCAGC
((((((.((..(((.........)))..)).........(((......))).))))))
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_ANTICODON_OF_E.COLI_TRNA-VAL3_WITH_NO_MODIFICATIONS_'_(PDB_01147)
CCUCCCUUACAAGGAGG
((((((.....))))))
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_ANTICODON_OF_E._COLI_TRNA-_VAL3_WITH_2_MODIFICATIONS_(CMO5U34_M6A37)_'_(PDB_01148)
CCUCCCUUACAAGGAGG
(((((.......)))))
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_ANTICODON_OF_E._COLI_TRNA-_VAL3_WITH_1_MODIFICATION_(CMO5U34)_'_(PDB_01149)
CCUCCCUUACAAGGAGG
((((((.....))))))
>>__'NMR_SOLUTION_STRUCTURE_OF_THE_ANTICODON_OF_E.COLI_TRNA-VAL3_WITH_1_MODIFICATION_(M6A37)_'_(PDB_01151)
CCUCCCUUACAAGGAGG
((((((.....))))))
>>__'SOLUTION_STRUCTURE_OF_THE_FRAMESHIFT-INDUCING_RNA_STEM-LOOP_IN_SIV_'_(PDB_01152)
GGAUGGGGAAAGAAGCCCCGCAAUUUCCCCAUCC
((((((((((((..((...)).))))))))))))
>>__'CRYSTAL_STRUCTURE_OF_RNASE_III_FROM_AQUIFEX_AEOLICUS_COMPLEXED_WITH_DS-RNA_AT_1.7-ANGSTROM_RESOLUTION_'_(PDB_01165)
AAGGUCAUUCGAGUGGCCUUGCAAGGUCAUUCGAGUGGCCUUGC
((((((((([[)))))))))..(((((((((]])))))))))..
>>__'SOLUTION_STRUCTURE_OF_U2_SNRNA_STEM_I_FROM_S._CEREVISIAE_'_(PDB_01168)
GGUUUGCCUUUUGGCUUACC
((((((((....))))))))
>>__'HEPATITIS_DELTA_VIRUS_GEMONIC_RIBOZYME_PRECURSOR_WITH_C75U_MUTATION_AND_BOUND_TO_MONOVALENT_CATION_TL+_'_(PDB_01185)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
.(((((((...[[[[[[(((.[[.....))))))))))]]...(((((..........)))))....]]]]]]
>>__'HEPATITIS_DELTA_VIRUS_RIBOZYME_PRECURSOR_STRUCTURE,_WITH_C75U_MUTATION,_BOUND_TO_TL+_AND_COBALT_HEXAMMINE_(CO(NH3)_63+)_'_(PDB_01190)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACACCAUUGCACUCCGGUGGUGAAUGGGAC
..((((((...[[[[[[(((.[[.....))))))))).]]...(((((..........)))))....]]]]]]
>>__'NMR_STRUCTURE_OF_A_KISSING_COMPLEX_FORMED_BETWEEN_THE_TAR_RNA_ELEMENT_OF_HIV-1_AND_A_LNA/RNA_APTAMER_'_(PDB_01194)
GGAGCCUGGGAGCUCCCACGGUCCCAGACGUG
((((([[[[[.)))))(((((.]]]]])))))
>>__'STRUCTURE_OF_A_HUMAN_PRP31-15.5K-U4_SNRNA_COMPLEX_'_(PDB_01199)
AUCGUAGCCAAUGAGGUUUAUCCGAGGCGCGAUAUCGUAGCCAAUGAGGUUUAUCCGAGGCGCGAU
(((((.(((...((((.....))))))))))))(((((.(((...((((.....))))))))))))
>>__'SOLUTION_STRUCTURE_OF_AN_RRNA_SUBSTRATE_BOUND_TO_THE_PSEUDOURIDYLATION_POCKET_OF_A_BOX_H/ACA_SNORNA_'_(PDB_01202)
GGACCCGCCACUGCAGAGAUGCAAUCCAGUGGUCC
(((((......((((....)))).......)))))
>>__'STRUCTURE_OF_THE_MRNA_BINDING_FRAGMENT_OF_ELONGATION_FACTOR_SELB_IN_COMPLEX_WITH_SECIS_RNA._'_(PDB_01205)
GGCGUUGCCGGUCUGGCAACGCCGGCGUUGCCGGUCUGGCAACGCC
(((((((((.....)))))))))(((((((((.....)))))))))
>>__'NMR_STRUCTURE_OF_A_KISSING_COMPLEX_FORMED_BETWEEN_THE_TAR_RNA_ELEMENT_OF_HIV-1_AND_A_LNA_MODIFIED_APTAMER_'_(PDB_01206)
GGAGCCUGGGAGCUCCCACGGUCCCAGACGUG
((((([[[[[[)))))(((((]]]]]])))))
>>__'SOLUTION_STRUCTURE_OF_THE_CR7_TERMINAL_HAIRPIN_LOOP_FROM_HUMAN_TELOMERASE_RNA_'_(PDB_01237)
GGAGUGCCUGAGCUGUGGCACUCC
((((((((........))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_U64_H/ACA_SNORNA_3\'_TERMINAL_HAIRPIN_LOOP_'_(PDB_01238)
GGAGUGCCUUACUGUGGCACUCC
((((((((.......))))))))
>>__'SOLUTION_STRUCTURE_OF_THE_U85_C/D-H/ACA_SCARNA_5\'_TERMINAL_HAIRPIN_LOOP_'_(PDB_01239)
GGCACAGAGUUAUGUGCC
(((((((....)))))))
>>__'GLUTAMINYL-TRNA_SYNTHETASE_MUTANT_C229R_WITH_BOUND_ANALOG_5\'-O-[N-(L-GLUTAMINYL)-SULFAMOYL]ADENOSINE_'_(PDB_01258)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..((((.......)))).(((((((...))))))).....(((((.......))))))))))).....
>>__'GLUTAMINYL-TRNA_SYNTHETASE_MUTANT_C229R_WITH_BOUND_ANALOG_5\'-O-[N-(L-GLUTAMYL)-SULFAMOYL]ADENOSINE_'_(PDB_01259)
GGGGUAUCGCCAAGCGGUAAGGCACCGGAUUCUGAUUCCGGCAUUCCGAGGUUCGAAUCCUCGUACCCCAGCCA
((((((..((((.......))))((((((((...))))))))....(((((.......))))))))))).....
>>__'SOLUTION_STRUCTURE_OF_THE_TOBRAMYCIN-RNA_APTAMER_COMPLEX,_NMR,_13_STRUCTURES_'_(PDB_01262)
ACUUGGUUUAGGUAAUGAGU
((((((((....))))))))
>>__'C-TERMINAL_DOMAIN(WH2-WH4)_OF_ELONGATION_FACTOR_SELB_IN_COMPLEX_WITH_SECIS_RNA_'_(PDB_01270)
GGCGUUGCCGGUCUGGCAACGCCGGCGUUGCCGGUCUGGCAACGCC
(((((((((.....)))))))))(((((((((.....)))))))))
>>__'CRYSTAL_STRUCTURE_OF_AN_ESCHERICHIA_COLI_TRNAGLY_MICROHELIX_AT_2.0_ANGSTROM_RESOLUTION_'_(PDB_01281)
GCGGGAAGCGGGAAUUCCCGCUUCCCGC
((((((([[[[[[[)))))))]]]]]]]
>>__'CRYSTAL_STRUCTURE_OF_DOMAIN_III_OF_THE_CRICKET_PARALYSIS_VIRUS_IRES_RNA_'_(PDB_01299)
GGUUAUUCAGAUUAGGUAGUCGAAUGACCUAAGAAAUUUACCU
((((((((.((..[[[[[.)))))))))).........]]]]]
>>__'5\'-R(*GP*AP*UP*CP*AP*CP*UP*UP*CP*GP*GP*U)-3\'_'_(PDB_01313)
GAUCACUUCGGUGAUCACUUCGGU
....((((((((....))))))))
>>__'SOLUTION_STRUCTURE_OF_HIV-1_REV_PEPTIDE-RNA_APTAMER_COMPLEX_'_(PDB_01332)
GGUGUCUUGGAGUGCUGAUCGGACACC
(((((((..((.......)))))))))
>>__'MS2_PROTEIN_CAPSID/RNA_COMPLEX_'_(PDB_01337)
CCGGAGGAUCACCACGGGCGGAGGAUCACCACGG
((((.((....)))))).(((.((....))))).
>>__'F6_APTAMER_MS2_COAT_PROTEIN_COMPLEX_'_(PDB_01338)
CCACAGUCACUGGGCAGUCACUGG
((.(((...)))))(((...))).
>>__'MS2_PROTEIN_CAPSID/RNA_COMPLEX_'_(PDB_01340)
UCGCCAACAGGCGGGCCAACAGGCG
(((((....)))))(((....))).
>>_PKB1:_Bovine_Leukemia_Virus_(BLV)
AAAAAACUAAUAGAGGGGGGACUUAGCGCCCCCCAAACCGUAACCCC
..............[[[[[[.....(((]]]]]]....)))......
>>_PKB2:_Beet_Western-Yellows_Virus_(BWYV)
GGGAAACGGAGUGCGCGGCACCGUCCGCGGAACAAACGGAGAAGGCAGCU
.............[[[[[..((((]]]]]......))))...........
>>_PKB3:_Equine_Infectious_Anemic_Virus_(EIAV)
AAAAAACGGGAAGCAAGGGGCUCAAGGGAGGCCCCAGAAACAAACUUUCCCGAU
................[[[[[[...((((]]]]]]............))))...
>>_PKB4:_Feline_Immunodeficiency_Virus_(FIV)
GGGAAACUGGAAGGCGGGGCGAGCUGCAGCCCCAGUGAAUCAAAUGCAGC
...............[[[[[..((((((]]]]]...........))))))
>>_PKB5:_turnip_yellow_mosaic_virus_(TYMV)
CGGGUGCAACUCCCGCCCCUCUUCCGAGGGUCAUCGGAACC
...............(((....[[[[[)))...]]]]]...
>>_PKB6:_kennedya_yellow_mosaic_virus_(KYMV-BP)
GGGGUGCAACUCCCCCGUCUAUCCUGGACGUCACCAGGACCA
...............(((...[[[[[[)))...]]]]]]...
>>_PKB7:_cacao_yellow_mosaic_virus_(CaYMV)
GGUGGUGCAACUCCCCCGUCCUCCCGAACGUCAUCGGGACCA
................(((..[[[[[[)))...]]]]]]...
>>_PKB8:_physalis_mottle_virus_(PhyMV)
UGGGUGCAACUCCCCCCCCUUCCGUGGGUAACGGAAACCA
..............(((..[[[[[[)))..]]]]]]....
>>_PKB9:_desmodium_yellow_mottle_virus_(DYMV)
GGGGUGCAACUCCCCCGUCUAUCCUGGACGUCACCAGGACCA
...............(((...[[[[[[)))...]]]]]]...
>>_PKB10:_ononis_yellow_mosaic_virus_(OYMV)
UGGGUUCAACUCCCCCCCUUUUCCGAGGGUAUCGGAAACC
..............(((...[[[[[[)))..]]]]]]...
>>_PKB11:_clitoria_yellow_vein_virus_(CYVV)
UGGGUGCAACCCCCCCGUCCAUCUCGAACGUCAUCGAGACCA
...............(((...[[[[[[)))...]]]]]]...
>>_PKB12:_wild_cucumber_mosaic_virus_(WCMV)
CGGGUGCAACCCCCCCUCCCCCCGUAGGUUAACGGGACCA
..............(((...[[[[[)))...]]]]]....
>>_PKB13:_calopogonium_yellow_vein_virus_(CaYVV)
GGGGUGCGACUCCCCCGUCUAUCCUGAACGUCAUCAGGACCA
...............(((...[[[[[[)))...]]]]]]...
>>_PKB14:_andean_potato_latent_virus_(APLV)
CGGGUGCGACUCCCCCCCCUCCUGUGGGCUACAGGAACCA
..............(((..[[[[[[)))..]]]]]]....
>>_PKB15:_eggplant_mosaic_virus_(EMV)
UGGGUGCGACUCCCCCCCCUCCCGUGGGUCAACGGGAACCA
..............(((..[[[[[[)))...]]]]]]....
>>_PKB16:_okra_mosaic_virus_(OMV)
GGGGUGCAACUCCCCCGCCCAUCUCGAGCGUCAUCGAGACCA
...............(((...[[[[[[)))...]]]]]]...
>>_PKB17:_tobacco_mosaic_virus_(CcTMV)
GGGGAGCAUUACCCCCCCAAAACCCUGGGGAUACAGGGCCCA
...............(((....[[[[[)))...]]]]]....
>>_PKB18:_tobacco_mosaic_virus_(TMV)
GGGGUUCGAAUCCCCCCGUUACCCCCGGUAGGGGCCCA
...............(((...[[[[)))..]]]]....
>>_PKB19:_pepper_mild_mottle_virus_(PMMV-I)
GGGGUUCGAAUCCCCCCCGAACCGCGGGUAGCGGCCCA
...............(((...[[[[)))..]]]]....
>>_PKB20:_cucumber_green_mottle_mosaic_virus_(CGMMV)
GGGGUUCGAAUCCCCCCUUUUCCCCGGGUAGGGGCCCA
...............(((...[[[[)))..]]]]....
>>_PKB21:_tobacco_mosaic_virus_(TMV-L)
GGGAUUCGAAUUCCCCCGGAACCCCCGGUUGGGGCCCA
...............(((...[[[[)))..]]]]....
>>_PKB22:_satellite_tobacco_mosaic_virus_(STMV)
GGGGUUCGAAUCCCUCCCUAACCGCGGGUAAGCGGCCCA
...............(((...[[[[)))...]]]]....
>>_PKB23:_tobacco_mild_green_mosaic_virus_(TMGMV)
GAGGUUCGAAUCCUCCCGUAACCGCCGGUAGCGGCCCA
...............(((...[[[[)))..]]]]....
>>_PKB24:_paprika_mild_mottle_virus_(PaMMV)
GGGGUUCGAAUCCCCCCUUUACCCCGGGUAUGGGGCCCA
...............(((...[[[[)))...]]]]....
>>_PKB25:_turnip_vein-clearing_virus_(TVCV)
GAGGUUCGAAUCCUCCCUAACCCCGGGUAGGGGCCCA
...............(((..[[[[)))..]]]]....
>>_PKB26:_oilseed_rape_mosaic_virus_(ORMV)
GAGGUUCGAAUCCUCCCUAACCCCGGGUAGGGGCCCA
...............(((..[[[[)))..]]]]....
>>_PKB27:_pepper_mild_mottle_virus_(PMMV-S)
GGGGUUCGAAUCCCCCCCGAACCGCGGGUAGCGGCCCA
...............(((...[[[[)))..]]]]....
>>_PKB28:_odontoglossum_ringspot_virus_(ORSV-S1)
GGGAUUCGAAUUCCCCCUUACCUCGGGUAGAGGCCCA
...............(((..[[[[)))..]]]]....
>>_PKB29:_tobacco_mosaic_virus_(TMVcg)
GAGGUUCGAAUCCUCCCUAACCCCGGGUAGGGGCCCA
...............(((..[[[[)))..]]]]....
>>_PKB30:_soil-borne_wheat_mosaic_virus_(SBWMV1)
GGGGUUCAAAUCCCCCCCGAACCGGAGGGUUAUCCGGCCCA
...............(((...[[[[[)))...]]]]]....
>>_PKB31:_soil-borne_wheat_mosaic_virus_(SBWMV2)
GGGGUUCAAUUCCCCCCCCAUCCGGAGGGUUAUCCGGCCC
...............(((...[[[[[)))...]]]]]...
>>_PKB32:_potato_mop-top_virus_(PMTV2)
GGGUGCAACUCCCCCCCCCUUGGAGGGUAUCCAAGACC
.............(((..[[[[[[)))..]]]]]]...
>>_PKB33:_peanut_clump_virus_(PCV1)
GGUGCAAAUCCCCCGCUGAAACGGAGCGAUAUCCGUCCCA
.............(((....[[[[[)))...]]]]]....
>>_PKB34:_peanut_clump_virus_(PCV2)
GGUGCAAAUCCCCCGCUGAAACGGAGCGAUAUCCGUCCCA
.............(((....[[[[[)))...]]]]]....
>>_PKB35:_Indian_peanut_clump_virus_(IPCV1)
GGUGCAAAUCCCCCGCCGAUACGGAGCGAUAUCCGUCCCA
.............(((....[[[[[)))...]]]]]....
>>_PKB36:_beet_soil-borne_virus_(BSBV1)
GGGGUGCAAAUCCCCCCCUUUACUUGAGGGAAAUCAAGCCC
...............(((....[[[[[)))...]]]]]...
>>_PKB37:_beet_soil-borne_virus_(BSBV2)
GGGGUGCAAAUCCCCCCCUUAACUUGAGGGAAAUCAAGCCC
...............(((....[[[[[)))...]]]]]...
>>_PKB38:_beet_soil-borne_virus_(BSBV3)
GGGGUGCAACUCCCCCCCUUAACUAGAGGGAAAUCUAGCCC
...............(((....[[[[[)))...]]]]]...
>>_PKB39:_beet_virus_Q_(BVQ1)
GGGGUGCAAAUCCCCCCCUAACUUGAGGGAAAUCAAGCCCC
...............(((...[[[[[)))...]]]]]....
>>_PKB40:_beet_virus_Q_(BVQ2)
GGGGUGCAAAUCCCCCCCUAACUUGAGGGAAAUCAAGCCC
...............(((...[[[[[)))...]]]]]...
>>_PKB41:_beet_virus_Q_(BVQ3)
GGGGUGCAAAUCCCCCCCUAACUUGAGGGAAAUCAAGCCCC
...............(((...[[[[[)))...]]]]]....
>>_PKB42:_potato_leafroll_virus_(PLRV-W)
UUUAAAUGGGCGAGCGGCACCGCCCGCCAAAACAAACGG
.............((((..[[[.)))).........]]]
>>_PKB43:_potato_leafroll_virus_(PLRV-S)
UUUAAAUGGGCAAGCGGCACCGUCCGCCAAAACAAACGG
.............((((..[[[[))))........]]]]
>>_PKB44:_cucurbit_aphid-borne_yellows_virus_(CABYV)
GGGAAACGGGCAGGCGGCGGCGACCGCCGAAACAACCGC
............(((((..[[[.)))))........]]]
>>_PKB45:_pea_enation_mosaic_virus_(PEMV)
GGGAAACGGAUUAUUCCGGUCGACUCCGGAGAAACAAAGUC
.............((((((..[[[[))))))......]]]]
>>_PKB46:_barley_yellow_dwarf_virus_(BYDV-NY-RPV)
GGGAAACGGGAAGGCGGCGGCGUCCGCCGUAACAAACGC
............(((((..[[[[))))).......]]]]
>>_PKB47:_Moloney_murine_leukemia_virus_(Mo-MuLV)
UAGGGAGGUCAGGGUCAGGAGCCCCCCCCUGAACCCAGGAUAACCCUCAAAGUCGGGGGGC
...........((((((((.[[[[[[[)))).))))..................]]]]]]]
>>_PKB48:_spleen_necrosis_virus_(SNV)
UAGGGCCGUCAGGGUUCUCCCGCCCUCCGUGAACCCAGGCUAAAAGUUAAGGUAGGGGGGC
...........((((((.(..[[[[[[[).))))))..................]]]]]]]
>>_PKB49:_E.coli_(Ec_PK1)
CGAGGGGCGGUUGGCCUCGUAAAAAGCCGC
(((((.[[[[[[..))))).....]]]]]]
>>_PKB50:_E.coli_(Ec_PK2)
CCUCUCUCCCUAGCCUCCGCUCUUAGGACGGGGAUCAAGAGAGGUCAAACCCAAAAGAG
(((((((((((..(((...[[[[[)))..))))....)))))))..........]]]]]
>>_PKB51:_E.coli_(Ec_PK3)
GCGUGGAAGCCCUGCCUGGGGUUGAAGCGUUAAAACUUAAUCAGGC
((((...(((((.[[[[[)))))...))))...........]]]]]
>>_PKB52:_E.coli_(Ec_PK4)
GUUUGUUAGUGGCGUGUCCGUCCGCAGCUGGCAAGCGAAUGUAAAGACUGAC
((((((((((.(((.[[[.[[[))).)))))))))).........]]].]]]
>>_PKB53:_tobacco_mosaic_virus_(TMV_UPD-PK1)
ACGGAUUGUGUCCGUAAUCACA
..(((.[[[[))).....]]]]
>>_PKB54:_tobacco_mosaic_virus_(TMV_UPD-PK2)
CGUGGUGCGUACGAUAACGCAU
(((.[[[[[[)))...]]]]]]
>>_PKB55:_tobacco_mosaic_virus_(TMV_UPD-PK3)
AGUGUUUUUCCCUCCACUUAAAUCGAAGGG
((((.....[[[[[))))......].]]]]
>>_PKB56:_odontoglossum_ringspot_virus_(ORSV-S1_UPD3-PK1)
UAACGUUGAUAGUGUUGAACUAUC
((((((.[[[[))))))...]]]]
>>_PKB57:_tobacco_mosaic_virus_(TMV_PKbulge)
UGUGUCUUGGAUCGCGCGGGUCAAAUGUAUAUGGUUCAUAUACAUCCGCAGGCACGUAAUAAAGCGA
(((((((....[[[[((((.....((((((((.....))))))))))))))))))).......]]]]
>>_PKB58:_odontoglossum_ringspot_virus_(ORSV-S1_UPD1-PK3)
AGUGUUUGUCCCUCCACUUAAAUCGAAGGG
((((.....[[[[[))))......].]]]]
>>_PKB59:_odontoglossum_ringspot_virus_(ORSV-S1_UPD1-PK2)
CGUGGUGCAUACGAUAAUGCAU
(((.[[[[[[)))...]]]]]]
>>_PKB60:_odontoglossum_ringspot_virus_(ORSV-S1_UPD2-PK3)
AGUGUUUAUCCCUCCACUUGAAUCGAAGGG
((((.....[[[[[))))......].]]]]
>>_PKB61:_odontoglossum_ringspot_virus_(ORSV-S1_UPD2-PK2)
CGUUGUGUACACGAUAGUACAU
(((.[[[[[[)))...]]]]]]
>>_PKB62:_odontoglossum_ringspot_virus_(ORSV-S1_UPD3-PK3)
AGUGGUUAUCCCUCCACUUAAAUCGAAGGG
((((.....[[[[[))))......].]]]]
>>_PKB63:_odontoglossum_ringspot_virus_(ORSV-S1_UPD3-PK2)
CGUGGUGCAUACGAUAAUGCAU
(((.[[[[[[)))...]]]]]]
>>_PKB65:_E.coli_(Ec_16S-PK505/526)
GCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGC
((((((((...[[[[[[[......))).......]]]]]]])))))
>>_PKB66:__(TPK-70.28)
CAAGAACCGGACGGGUGAGAACCGAGACAAACACCCACCA
.......(((..[[[[[....))).......]]]]]....
>>_PKB67:_Legionella_pneumophila_(Lp_PK1)
CGAGAAGGAGAUCUCUCGUAAAUAAGACUC
(((((..[[[.[[))))).......]]]]]
>>_PKB68:_Legionella_pneumophila_(Lp_PK2)
GUUAAACCAUCACUGUGUACUGGCCAAUAAACCCAGUAUCCCGUUCGACCGAGCCCGCUUAUCGGUAU
(((.(((....((((.[[[[[[[..........)))).....))).)))............]]]]]]]
>>_PKB69:_Legionella_pneumophila_(Lp_PK3)
CGGUCAUAAGAGAUAAGCUAGCGUCCUAAUCUAUCCCGGGUUAUGGCGCGAAACUCAGGGA
(((((((((........................[[[[[[[))))))).))...]]].]]]]
>>_PKB70:_Legionella_pneumophila_(Lp_PK4)
GCUGUGUAUCAUCCUGCCCGUCGGAGGAGCCACAGUUAAAUUCAAAAGACAAGGC
((((((..((.(((.[[[.[[[))).))..))))))...........]]]..]]]
>>_PKB72:_E.coli_(Ec_S15)
GGGAUCGCUGAAUUAGAGAUCGGCGUCCUUUCAUUCUAUAUACUUUGGAGUUUUAAAAUGUCUCUAA
((((.((((((.[[[[[[[))))))))))...............................]]]]]]]
>>_PKB73:_T2_bacteriophage_(T2_gene32)
CUGACCAGCUAUGAGGUCAUACAUCGUCAUAGC
.(((((.[[[[[[[))))).......]]]]]]]
>>_PKB74:_bacteriophage_T4_(T4_gene32)
UGCCAGCUAUGAGGUAAAGUGUCAUAGC
((((.[[[[[[[)))).....]]]]]]]
>>_PKB75:_hepatitis_delta_virus_("Italy"_variant)_(HDV-It_g)
UGGCCGGCAUGGUCCCAGCCUCCUCGCUGGCGCCGGCUGGGCAACAUUCCGAGGGGACCGUCCCCUCGGUAAUGGCGAAUGGGACCCA
.(((((((..[[[[[[[{{{.[[.....}}})))))))]]....(((((((((((((...))))))))).)))).....]]]]]]]..
>>_PKB76:_hepatitis_delta_virus_("Italy"_variant)_(HDV-It_ag)
GGGUCGGCAUGGCAUCUCCACCUCCUCGCGGUCCGACCUGGGCAUCCGAAGGAGGACGCACGUCCACUCGGAUGGCUAAGGGAGAGCCA
(((((((........[[[[(((.......))))))))))...(((((((....((((....))))..)))))))......]]]].....
>>_PKB78:_AKV_murine_leukemia_virus_(AKV-MuLV)
UAGGGGGGUCAGGGUCAGGAGCCCCCCCCUGAACCCAGGAUAACCCUCACUGUCGGGGGGCA
...........((((((((.[[[[[[[)))).))))..................]]]]]]].
>>_PKB79:_gibbon_ape_leukemia_virus_(GaLV)
UAGGGGAGUCAGGGUUCGGACCCCCUCCCCGAACCUAGGGUAACACUGACUGUGGAGGGGA
...........((((((((..[[[[[[[)))))))).................]]]]]]].
>>_PKB80:_mouse_mammary_tumor_virus_(MMTV_gag/pro)
AAAAAACUUGUAAAGGGGCAGUCCCCUAGCCCCGCUCAAAAGGGGGAUG
..............(((((.[[[[[[[.)))))........]]]]]]].
>>_PKB81:__(oligo_PK5)
GCGAUUUCUGACCGCUUUUUUGUCAG
(((....[[[[[)))......]]]]]
>>_PKB82:_tobacco_mosaic_virus_(TMV-L_UPD-PK1)
AUAAAGUUUGUGUUUCUAAAACACAC
..(((...[[[[)))......]]]].
>>_PKB83:_tobacco_mosaic_virus_(TMV-L_UPD-PK2)
ACGUGGUACGUACGAUAACGUACA
.(((.[[[[[[)))...]]]]]].
>>_PKB84:_tobacco_mosaic_virus_(TMV-L_UPD-PK3)
CAGUGUUUUUCCCUCCACUUAAAUCGAAGGGU
.((((.....[[[[[))))......].]]]].
>>_PKB85:_tobacco_mosaic_virus_(CcTMV_UPD-PK1)
AAGUUUGGUCGUACUUAACGACCU
.(((..[[[[[[)))..]]]]]].
>>_PKB86:_tobacco_mosaic_virus_(CcTMV_UPD-PK2)
UAGGGGCUUACCGAAAUAAGCC
.(((.[[[[[)))...]]]]].
>>_PKB87:_tobacco_mosaic_virus_(CcTMV_UPD-PK3)
CCGUGUUUAAGAGUCCACGCAAAUCGAACUCU
.((((.....[[[[[))))......].]]]].
>>_PKB88:_Feline_leukemia_virus_(FeLV)
UAGGAGAGUCAGGGCCAGGACCCCCCCCCCUGAGCCCAGGAUAACCUUAAGAAUAGGGGGGC
...........((((((((...[[[[[[)))).))))..................]]]]]].
>>_PKB89:_cucumber_green_mottle_mosaic_virus_(CGMMV_UPD-PK1)
ACCUCGAAAGCUUAGUUUCGAGGGUCUUCUGAU
.((((((((..[[[[)))))))).....]]]].
>>_PKB90:_cucumber_green_mottle_mosaic_virus_(CGMMV_UPD-PK2)
UGGUGGUGCACACCAAAGUGCAUA
.(((.[[[[[[)))...]]]]]].
>>_PKB91:_cucumber_green_mottle_mosaic_virus_(CGMMV_UPD-PK3)
UAGUGCUUUCCCGUUCACUUAAAUCGAACGGUU
.((((.....[[[[[))))......].]]]]..
>>_PKB92:_tobacco_mild_green_mosaic_virus_(TMGMV_UPD-PK1)
AAAGUCGCUGAAGACUUAAAAUUCAGG
.(((((.[[[[[)))))....]]]]].
>>_PKB93:_tobacco_mild_green_mosaic_virus_(TMGMV_UPD-PK2)
GGGUGGCUGAUACCAAAAUCAGCA
.(((.[[[[[[)))...]]]]]].
>>_PKB94:_tobacco_mild_green_mosaic_virus_(TMGMV_UPD-PK3)
CAGUGGUUGUUCGUCCACUUAAAUAUAACGAUU
.((((.....[[[[.))))........]]]]..
>>_PKB95:_pepper_mild_mottle_virus_(PMMV-S_UPD-PK1)
AGUUGGACGAACAUUAAACGUCC
.(((.[[[[)))......]]]].
>>_PKB96:_pepper_mild_mottle_virus_(PMMV-S_UPD-PK2)
CCGUGGCGAGUACGAUAACUCGUA
.(((.[[[[[[)))...]]]]]].
>>_PKB97:_pepper_mild_mottle_virus_(PMMV-S_UPD-PK3)
UAGUGUUUUUCCCUCCACUUAAAUCGAAGGGU
.((((.....[[[[[))))......].]]]].
>>_PKB98:_baboon_endogenous_virus_(BaEV)
UAGGGGUGUCAGGGCUCUGGAGCCCCCCCCGAGCCCCGGCUAACUCUAUCUGUAGGGGGGCA
...........((((((.((.[[[[[[[))))))))..................]]]]]]].
>>_PKB99:_Cas-Br-E_murine_leukemia_virus_(Cas-Br-E-MuLV)
UAGGGGGGUCGGGGUCAGGAGCCCCCCCCUGAACCCAGGAUAACCCUCAAAGUCGGGGGGCAA
...........((((((((.[[[[[[[)))).))))..................]]]]]]]..
>>_PKB100:_satellite_tobacco_mosaic_virus_(STMV_UPD2-PK1)
AAGCCUUUUGGAUCGAAGGUUAAACGAUCCG
.((((((..[[[[[[))))))...]]]]]].
>>_PKB101:_satellite_tobacco_mosaic_virus_(STMV_UPD2-PK2)
CGCUCCUCGCUUGAGCUUGAGGCGGC
.((((.[[[[[[))))...]]]]]].
>>_PKB102:_satellite_tobacco_mosaic_virus_(STMV_UPD2-PK3)
GCGUAUCUCUUAUGUCAACAGAGA
.((((.[[[[)))).....]]]].
>>_PKB103:_satellite_tobacco_mosaic_virus_(STMV_UPD1-PK1)
CGCCGACGUGGCUGUAUAAUACGUC
.(((.[[[[)))........]]]].
>>_PKB104:_satellite_tobacco_mosaic_virus_(STMV_UPD1-PK2)
UCGUUGACAAGUACGAAAUCUUGUUA
.(((.[[[[[[.)))....]]]]]].
>>_PKB105:_satellite_tobacco_mosaic_virus_(STMV_UPD1-PK3)
UAGUGUUUUUCCCUCCACUUAAAUCGAAGGGU
.((((.....[[[[[))))......].]]]].
>>_PKB107:_simian_retrovirus-1_(SRV1_gag/pro)
GGGAAACGGACUGAGGGGCCAGCCCCAGGCCCCGAAACAAGCUUAUGGGGCG
..............((((((.[[[[[[))))))............]]]]]].
>>_PKB108:_Tetrahymena_thermophila_(T.the_telo)
UAUAACCUUCACCAAUUAGGUUCAAAUAAGUGGUA
...((((...[[[[[[[[))))....]]]]]]]].
>>_PKB109:_beet_virus_Q_(BVQ1_UPD-PKc)
UUGUGGUGCAUACAAUAAUGCAUA
.(((.[[[[[[)))...]]]]]].
>>_PKB110:_beet_virus_Q_(BVQ1_UPD-PKb)
UAGUGUUUGCCGUUCCACUUAAAUCGAAACGGA
.((((....[[[[[[))))......].]]]]].
>>_PKB111:_beet_virus_Q_(BVQ2_UPD-PKc)
ACGUGGUGCAUACGUUAAUGCAUA
.(((.[[[[[[)))...]]]]]].
>>_PKB112:_beet_virus_Q_(BVQ2_UPD-PKb)
UAGUGUUUUUCGUUCCACUUAAAUCGAAACGAU
.((((....[[[[[[))))......].]]]]].
>>_PKB113:_beet_virus_Q_(BVQ3_UPD-PKc)
UCGUGGUGCAUACGAAAAUGCAUA
.(((.[[[[[[)))...]]]]]].
>>_PKB114:_beet_virus_Q_(BVQ3_UPD-PKb)
UAGUGUUUACCGUUCCACUUAAAUCGAAACGGA
.((((....[[[[[[))))......].]]]]].
>>_PKB115:_beet_soil-borne_virus_(BSBV1_UPD-PKc)
CGGUAGCGCGAACCUUAUCGCGCA
.(((.[[[[[[)))...]]]]]].
>>_PKB116:_beet_soil-borne_virus_(BSBV1_UPD-PKb)
CAGUGUUUUGAAGUCCACUUAAAUAGAACUUCU
.((((....[[[[[[))))......].]]]]].
>>_PKB117:_beet_soil-borne_virus_(BSBV2_UPD-PKc)
ACGUGGGUUAUACGAUAAUAACCG
.(((.[[[[[[)))...]]]]]].
>>_PKB118:_beet_soil-borne_virus_(BSBV2_UPD-PKb)
CGGUGCUUUUAUGUUCACCGAAAUCGAACAUAC
.((((....[[[[[[))))......].]]]]].
>>_PKB119:_beet_soil-borne_virus_(BSBV3_UPD-PKc)
ACGUGGCGAAUACGAUAAUUCGUA
.(((.[[[[[[)))...]]]]]].
>>_PKB120:_beet_soil-borne_virus_(BSBV3_UPD-PKb)
UAGUGUUCGUGGAUAACACUUUAAUUAAGAUUCAUA
.((((((.[[[[[[)))))).........]]]]]].
>>_PKB121:_satellite_tobacco_necrosis_virus_1_(STNV1_PK1)
AAGCAGUCCCAGCUCUGCAUUGGGAA
.(((..[[[[[)))......]]]]].
>>_PKB122:_satellite_tobacco_necrosis_virus_1_(STNV1_PK2)
UACUACUUGCUCAUUUGUAGUCUAAAUGAGA
.(((((...[[[[[[[)))))..]]]]]]].
>>_PKB123:_satellite_tobacco_necrosis_virus_1_(STNV1_PK3)
GACGUUGGCCUCGACGUGUCGAGGUG
.((((..[[[[[[))))..]]]]]].
>>_PKB124:_satellite_tobacco_necrosis_virus_2_(STNV2_PK1)
CAGUAGUCCUGAACUAGUAAAUCAGGACC
.(((.[[[[[[[)))......]]]]]]].
>>_PKB125:_satellite_tobacco_necrosis_virus_2_(STNV2_PK2)
CCAUUCCCACUAGUGUAUUAGUGGA
.(((..[[[[[[)))...]]]]]].
>>_PKB126:_satellite_tobacco_necrosis_virus_2_(STNV2_PK3)
GAACGAGGCCCCGCGUGAAUUGGGGUG
..(((..[[[[[[)))....]]]]]].
>>_PKB130:_tobacco_rattle_virus_(TRV-PSG)
AGGGGUAAAACCCCUCGCCUACGUAAGCGUUAUUACGCCC
...............(((...[[[[[)))...]]]]]...
>>_PKB131:__(NGF-H1)
CGCUCAACUCAUGGAGCGCAAGACGAAUAGCUACAUAUUCGACAUGAG
(((((..[[[[[[))))).....((((((......)))))).]]]]]]
>>_PKB132:__(NGF-L2)
CGCUCAACCUCAGAGCGCAAGAGUCGAACGAAUACAGUUCGACAUGAGG
(((((..[[[[[))))).....(((((((.......))))))).]]]]]
>>_PKB133:__(NGF-L6)
CGCUCAACUCAUGGAGCGCACGACGGAUCACCAUCGAUUCGACAUGAG
(((((..[[[[[[))))).....((((((......)))))).]]]]]]
>>_PKB138:_barley_stripe_mosaic_virus_(BSMVbeta)
AUUGGUAUGUAAGCUACAACUUCCGGUAGCUGCGUCACACUUUAAGAGUGUGCAUACUGAGCCGAAGCUCAGCUUCGGUCCCCCAAGGGAAGACCA
.((((((((..((((((..[[[[[.))))))....((((((.....)))))))))))))).((((((.....)))))).........]]]]]....
>>_PKB139:_tobacco_mosaic_virus_(TMV-L_PKbulge)
UAGUGUCUUGGAGCGCGCGGAGUAAACAUAUAUGGUUCAUAUAUGUCCGUAGGCACGUAAAAAAAGCGAG
..((((((....[[[[((((.....((((((((.....)))))))))))))))))).........]]]].
>>_PKB140:_cucumber_green_mottle_mosaic_virus_(CGMMV_PKbulge)
UUUGCUCAUUGGUUUGCGGAAACCUCUCACGUGUGACGUUGAAGUUUCUAUGGGCAGUAAUUCUGCAAG
.((((((((....[[[[((((((.((..(((.....))).)).)))))))))))))).......]]]].
>>_PKB141:_tobacco_mild_green_mosaic_virus_(TMGMV_PKbulge)
UUGUCAUAUCUGGAUCCAACAGUUAAACCAUGUGAUGGUGUAUACUGUGGUAUGGCGUAAAACAUCGGAG
.(((((((((....[[[.(((((...((((.....))))....)))))))))))))).........]]].
>>_PKB142:_satellite_tobacco_mosaic_virus_(STMV_PKbulge)
UUUUGUUUUGGUCUUCCCGAACGCAUACGUUAGUGUGACUACCGUUGUUCGAAACAAGUAAAACAGGAAGG
.(((((((....[[[[[((((((...(((.(((.....))).)))))))))))))))).......]]]]].
>>_PKB143:_pepper_mild_mottle_virus_(PMMV-S_PKbulge)
UUGUCGUUGGGAUGGAACGCAAUUAAAUACAUGUGUGACGUGUAUUUGCGAACGACGUAAUUAUUUUUCAG
.(((((((....[[[[[(((....(((((((((.....)))))))))))))))))))........]]]]].
>>_PKB144:_odontoglossum_ringspot_virus_(ORSV-S1_PKbulge1)
UUGUGUAUAUGGAUCAUGCGGAUAAAGUUAUACUGGUGCAGUAUAACCCGUUAUACACAUAAAAUUAUGAG
.((((((((....[[[[((((.....((((((((.....)))))))))))))))))))).......]]]].
>>_PKB145:_odontoglossum_ringspot_virus_(ORSV-S1_PKbulge2)
UUGUGUCAGACGCGUGUAAGGAGUGGUCAACCUUACGACACAUUUAAAUAAUGCGUCC
.(((((..[[[[[[(((((((.........)))))))))))).........]]]]]].
>>_PKB146:_odontoglossum_ringspot_virus_(ORSV-S1_PKbulge3)
UUUCACUGCGGAUAUGUAGGUUUCCUCGGUGAAUAUAAAACUUAUAUCCC
.(((((...[[[[[((.(((...))))))))))...........]]]]].
>>_PKB147:_Saccharomyces_cerevisiae_(Sc_18S-PKE21-7/8)
AUAAUAGAAUAGGACGUUUGGUUCUAUUUUGUUGGUUUCUAGGACCAUCGU
.((((((((((...[[..[[[[[[)))))))))).......]]]]]].]].
>>_PKB151:_barley_stripe_mosaic_virus_(BSMVbeta_UPD-PK1)
AAAUGUUUGAUCAGAUCAUUCAAAUCUGAUGG
.((((....[[[[[[[))))...]]]]]]]..
>>_PKB152:_barley_stripe_mosaic_virus_(BSMVbeta_UPD-PK2)
UGGUGCCCAUCAACCAUAUGAUGGGA
.(((.[[[[[[[)))...]]]]]]].
>>_PKB153:_barley_stripe_mosaic_virus_(BSMVbeta_UPD-PK3)
GAGUGUUUGCAAGUCCACUAUAAUCGAACUUGA
.((((....[[[[[[))))......].]]]]].
>>_PKB154:_brome_mosaic_virus_(BMV3_UPD-PK1)
GAGCCCCUGACUGGGUUAAAGUCACA
.(((((.[[[[[)))))..]]]]]..
>>_PKB155:_brome_mosaic_virus_(BMV3_UPD-PK2)
CCCUUGUCUCAGGUAGAGACC
.(((.[[[[[)))..]]]]].
>>_PKB156:_brome_mosaic_virus_(BMV3_UPD-PK3)
ACUUUGGCUAAGGUUAAAAGCUU
.(((.[[[[)))......]]]].
>>_PKB157:_brome_mosaic_virus_(BMV3_UPD-PK4)
UUGUUGAAUCAGUACAAUAACUGAUA
.(((...[[[[[[)))...]]]]]].
>>_PKB158:_tobacco_rattle_virus,_strain_PSG_(TRV-PSG2_PK1)
CUUUAAGGGACCUUGUGAAAUUCAAGGG
.((((.....[[[[[))))...]]]]].
>>_PKB159:_tobacco_rattle_virus,_strain_PSG_(TRV-PSG2_PK2)
GGGCGGGUGUCGCCAGAAAUCACCG
.(((.[[[[[.)))....].]]]].
>>_PKB160:_tobacco_rattle_virus,_strain_PSG_(TRV-PSG2_PK3)
CGAUACUACUAGUUGUAUCAAAACAAAACUAA
.(((((...[[[[[))))).......]]]]].
>>_PKB161:_tobacco_rattle_virus,_strain_PSG_(TRV-PSG2_PK4)
AGGUGGAUGUUACCAUAAACAUUA
.(((.[[[[[[)))...]]]]]].
>>_PKB162:_tobacco_rattle_virus,_strain_PSG_(TRV-PSG2_PK5)
UAAUGUCGCAGGUGGCAUUUUAAAAUAAGACCUGA
.((((((.[[[[[))))))..........]]]]].
>>_PKB163:_Homo_sapiens_(Hs_SRP-pkn)
GCCGGGCGCGGUGGCGCGUGCCUGUAGUCCCAGCUACUCGGGAGGCU
(((.((((((.[[[[.)))))).....((((.]]]]...))))))).
>>_PKB164:_poa_semilatent_virus_(PSLVbeta)
AUUGGUAUGUAAGCUACUUCUUCCAGUAGCUGCGUCAUAACAUCAAGGUUAUGCAUACUGAGCCGAAGCUCAGCUUCGGUCCUCCAAGGAAGACCA
.((((((((..((((((..[[[[[.))))))....((((((......)))))))))))))).((((((.....))))))........]]]]]....
>>_PKB165:_poa_semilatent_virus_(PSLVbeta_UPD-PK1)
AUUGCCACUGUGGAAAUCAGUGA
.(((.[[[[[)))....]]]]].
>>_PKB166:_poa_semilatent_virus_(PSLVbeta_UPD-PK2)
CGGUUUUAUCUACCAUAAGAUAAA
.(((.[[[[[[)))...]]]]]].
>>_PKB167:_poa_semilatent_virus_(PSLVbeta_UPD-PK3)
AAGUGUUUUCAUGUCCACUUAAAUCGAACAUGAAC
.((((..[[[[[[[[))))......].]]]]]]].
>>_PKB169:_Coxsackie_B_virus_(CoxB3)
ACCCUACUGUGCUAACCGAACCAGAUAACGGUACAGUAGGGGUAAAUUCUCCGCAUUCGGUGCGGAAAAAAAA
.((((((((((((.[[[[[[.........)))))))))))).....((.(((((.]]]]]]))))).))....
>>_PKB172:_bamboo_mosaic_virus_(BaMV)
CUUUUGGUUUCUACAGUUUUUUCCAAAAAAAAAAAAAAA
.((((((.........[[[[[[))))))...]]]]]]..
>>_PKB173:_Satellite_cereal_yellow_dwarf_virus-RPV_RNA_(satRPV)
ACAGAGCGCGUACUGUCUGACGACGUAUCCGCGCGGACUAGAAGGCUGGUGCCUCGUCCAACAAAUAGAUACA
((((.[[[[[..))))........(((((]]]]]((((....((((....)))).))))........))))).
>>_PKB175:__(biotin-PK)
CACCGACCAUAGGCUCGGGUUGCCAGAGGUUCCACACUUUCAUCGAAAAGCCUAUGC
.(((((.[[[[[[[)))))..............................]]]]]]].
>>_PKB176:__(biotin-PK-AN69.1)
GGACCGUCAGAGGACACGGUUAAAAAGUCCUCU
..(((((..[[[[[[)))))......]]]]]].
>>_PKB177:_Rattus_rattus_(black_rat)_(Rr_ODCanti)
UGCUCCUGAUGUCCCUCACCCACCCCUGAAGAUCCCAGGUGGGCGAGGGAACAGUCAGCGGGAUCACAGU
............(((((.((((((......[[[[[[.)))))).)))))..........]]]]]].....
>>_PKB182:_soil-borne_rye_mosaic_virus_(SBRMV1-PKa)
GGGGUUCAAAUCCCCCCCCGAACCGGAGGGUUAUCCGGCCCA
...............(((....[[[[[)))...]]]]]....
>>_PKB183:_soil-borne_rye_mosaic_virus_(SBRMV1-UPD-PKb)
ACGUCGUGCAGUACGGUAAACUGCACA
.(((.[[[[[[[)))....]]]]]]].
>>_PKB184:_soil-borne_rye_mosaic_virus_(SBRMV1_UPD-PKc)
UUCUGUUUUUCGAACAGAUGUAAAUCGAAGA
.(((((.[[[[[[)))))......]]]]]].
>>_PKB185:_soil-borne_rye_mosaic_virus_(SBRMV1_UPD-PKd)
ACGUGGCCAUCACGAUAGAUGGUU
.(((.[[[[[[)))...]]]]]].
>>_PKB186:_soil-borne_rye_mosaic_virus_(SBRMV1_UPD-PKe)
AAGCCUAUUUGUACGGGUUGAGUACAAAC
.(((((.[[[[[..)))))....]]]]].
>>_PKB187:_soil-borne_rye_mosaic_virus_(SBRMV1_UPD-PKf)
GCCGCUGGGAUUGCGGAUUAUAAAUCG
.((((...[[[[))))......]]]].
>>_PKB188:_soil-borne_rye_mosaic_virus_(SBRMV1_UPD-PKg)
UCGUUGCCGUCACGAUAGACGGA
.(((..[[[[[)))...]]]]].
>>_PKB189:_soil-borne_rye_mosaic_virus_(SBRMV1_UPD-PKh)
AGUCUAACAUGUCGGGCUGAGACAUGUC
.((((.[[[[[[[))))...]]]]]]].
>>_PKB190:_Plautia_stali_intestine_virus_(PSIV_IRES)
CUCGCUCAAACAUUAAGUGGUGUUGUGCGAAAAGAAUCUCACUUCAA
.((((...(((((.[[[[[)))))..)))).........]]]]]...
>>_PKB194:_soil-borne_wheat_mosaic_virus_(SBWMV1_UPD-PKb)
UACGCUGUACAGUGCGUUAAACUGUACA
..(((.[[[[[[[)))....]]]]]]].
>>_PKB195:_soil-borne_wheat_mosaic_virus_(SBWMV1_UPD-PKc)
CUCUGUUGAUCAAACAGAAAUAAAUUGAUUA
.(((((.[[[[[[)))))......]]]]]].
>>_PKB196:_soil-borne_wheat_mosaic_virus_(SBWMV1_UPD-PKd)
ACGCGGUCAUUGCGAUAAAUGACU
.(((.[[[[[[)))...]]]]]].
>>_PKB197:_soil-borne_wheat_mosaic_virus_(SBWMV1_UPD-PKe)
GAACCUAUUUGCUCGGGUUGAGUGCAAAC
..((((.[[[[[..)))).....]]]]].
>>_PKB198:_soil-borne_wheat_mosaic_virus_(SBWMV1_UPD-PKf)
ACCGCCUGAUUAGCGGUCUACAAGUUAAUCGA
.((((..[[[[[)))).........]]]]]..
>>_PKB199:_soil-borne_wheat_mosaic_virus_(SBWMV1_UPD-PKg)
UCGUGGUCAGUACGAUAACUGAU
.(((..[[[[[)))...]]]]].
>>_PKB200:_soil-borne_wheat_mosaic_virus_(SBWMV1_UPD-PKh)
AGUCUAAUUUGUCGGGCUGAGACAAAUC
.((((.[[[[[[[))))...]]]]]]].
>>_PKB201:_soil-borne_wheat_mosaic_virus_(SBWMV2_UPD-PKb)
GGCGUUCUACAGUACGUUUAAACUGUAGG
..(((.[[[[[[[))).....]]]]]]].
>>_PKB202:_soil-borne_wheat_mosaic_virus_(SBWMV2_UPD-PKi)
UGGUGCUUGUUAUUUCACCUAAAUCGAAAUAACG
.((((...[[[[[[[)))).......]]]]]]].
>>_PKB203:_soil-borne_wheat_mosaic_virus_(SBWMV2_UPD-PKk)
ACGUGGUCUUCACGAUAGAAGAUG
.(((.[[[[[[)))...]]]]]].
>>_PKB204:_soil-borne_wheat_mosaic_virus_(SBWMV2_UPD-PKl)
CAGAGUUAUCAUACUCUAUAAACUAUGAC
.((((...[[[[[))))......]]]]].
>>_PKB205:_Palmaria_palmata_(Pp_18S-PKE23-9/12)
UUAGAGUGUUCAAAGCCAGGCGUUUGCCGUGAAUACAUUAGCAUGGAA
.((..((.[[[[..))(((((....))).))..))........]]]].
>>_PKB206:_Homo_sapiens_(Hs_PrP)
GCCUCAUGGUGGUGGCUGGGGGCAGCCUCAUGGUGGUGGCUGGGG
...((((((.............[[[[[))))))....]]]]]...
>>_PKB207:_Bos_Taurus_(cow)_(Bt_PrP)
GCCCCAUGGAGGUGGCUGGGGCCAGCCUCAUGGAGGUGGCUGGGG
...((((((............[[[[[[))))))....]]]]]]..
>>_PKB210:_Bordetella_pertussis_(Bp_PK2)
CCGCUGCACUGAUCUGUCCUUGGGUCAGGCGGGGGAAGGCAACUUCCCAGGGGGCAACCCCGAACCGCAGCAGCGACAUUCACAAGGAAU
.((((((..(((...[[[[[[[..))).((((((((((....)))))).((((....))))...)))).)))))).......]]]]]]].
>>_PKB212:_Plautia_stali_intestine_virus_(PSIV_IRES-PKIII)
AGGUCUUGUAUAUUUAUACUUACCACACAAGAUGGACCGGAGCAGCCCUCCAAUAUCUAGUGUA
.((((..((((....)))).....[[[[.[[[[[))))((((.....))))..]]]]].]]]].
>>_PKB213:_Himetobi_P_virus_(HiPV_IRES-PKI)
CAGCCUUGUAGUUUUAGUGGACUUUAGGCUAAAGAAUUUCACUAG
.(((((...((((.[[[[[))))..))))).........]]]]].
>>_PKB215:_Himetobi_P_virus_(HiPV_IRES-PKIII)
GACCCUUAGUUAUUUAGCUUUACCGCCCAGGAUGGGGUGCAGCGUUCCUGCAAUAUCCAGGGCA
.((((..((((....)))).....[[[[.[[[[[))))((((.....))))..]]]]].]]]].
>>_PKB216:_Drosophila_C_virus_(DCV_IRES-PKI)
CUUCUUAUAUGAUUAGGUUGUCAUUUAGAAUAAGAAAAUAACCUG
.((((...(((((.[[[[[)))))..)))).........]]]]].
>>_PKB218:_Porcine_reproductive_and_respiratory_syndrome_virus,_North_American_isolate_(16244B)_(PRRSV-16244B)
UUUAAACUGCUAGCCGCCAGCGGCUUGACCCGCUGUGGUCGCGGCGGCUUGGUUGUUACUGAGACAGCGGUA
............((((((.((((((....[[[[[[[))))))))))))...............]]]]]]]..
>>_PKB220:_Drosophila_C_virus_(DCV_IRES-PKIII)
UUAGGUUAACUAUUUAGUUUUACUGUUCAGGAUGCCUAUUGGCAGCCCCAUAAUAUCCAGGACA
.((((..((((....)))).....[[[[.[[[[[)))).(((.....)))...]]]]].]]]].
>>_PKB221:_Cricket_paralysis_virus_(CrPV_IRES-PKI)
CGGUUUUUCAGAUUAGGUAGUCGAAAAACCUAAGAAAUUUACCUG
.((((((...(((.[[[[[)))..)))))).........]]]]].
>>_PKB223:_Cricket_paralysis_virus_(CrPV_IRES-PKIII)
UUAGGUUAGCUAUUUAGCUUUACGUUCCAGGAUGCCUAGUGGCAGCCCCACAAUAUCCAGGAAG
.((((..((((....)))).....[[[[.[[[[[))))((((.....))))..]]]]].]]]].
>>_PKB224:_Triatoma_virus_(TrV_IRES-PKI)
UUUCCUAUACCUCGAGUCGGGUUUGGAAUCUAAGGUUGACUCG
.((((...((((.[[[[[))))..)))).........]]]]].
>>_PKB226:_Triatoma_virus_(TrV_IRES-PKIII)
UGCGCUUGCCUAUUUAGGCAUACUUCUCAGGAUGGCGCGUUGCAGUCCAACAAGAUCCAGGGAC
.((((..((((....)))).....[[[[.[[[[.))))((((.....))))...]]]].]]]].
>>_PKB227:_Black_queen_cell_virus_(BQCV_IRES-PKI)
AUGUUUAGAAGAUUAGGUAGUCUCUAAACAGAACAAUUUACCUG
.(((((...((((.[[[[[))))..)))))........]]]]].
>>_PKB229:_Black_queen_cell_virus_(BQCV_IRES-PKIII)
AUCACCGUACCUAUUUAGGUUUACGCUCCAAGAUCGGUGGAUAGCAGCCCUAUCAAUAUCUAGGAGA
..((((..((((....)))).....[[[[.[[[[.))))(((((.....)))))...]]]].]]]].
>>_PKB230:_Rhopalosiphum_padi_virus_(RhPV_IRES-PKI)
CAGGAGAGCAUACGCUAGGUCGCGUUGACUAUCCUUAUAUAUGACCUG
.((((.((((.((((.[[[[[)))))).)).)))).......]]]]].
>>_PKB232:_Rhopalosiphum_padi_virus_(RhPV_IRES-PKIII)
UUGGUUAGCUAUUUAGCUUUACUAAUCAAGACGCCGUCGUGCAGCCCACAAAAGUCUAGAUA
.(((..((((....))))......[[[.[[[[.)))..(((.....)))....]]]].]]].
>>_PKB233:_Porcine_reproductive_and_respiratory_syndrome_virus,_European_Lelystad_strain_(LV)_(PRRSV-LV)
UUUAAACUGUUAGCCGCCAGCGGCUUGACCCGCUGUGGCCGCGGCGGCCUAGUUGUGACUGAAACGGCGGU
............((((((.((((((....[[[[[[[))))))))))))...............]]]]]]].
>>_PKB234:_Variovorax_paradoxus_(Vp_PK2)
GCCUUGCAACAGUUGGCCGAUGGGCUGGGCAAGGGGGUCUGGAGCAAUCCUGACCUCCCGGCUGCAAGGAUAACUACAUGGGCU
.((((((..(((...[[[[[[[..))).(((((((((((((((....))))))))))))))).)))))).......]]]]]]].
>>_PKB235:_Giardiavirus_(GLV_IRES)
GGAGACCCAUGGAGAGUCUCCAGAGGUUCCUAAGGCCUCGAUCGCGCCUGCCGGGAGGCAGAAUGUCCCGGUUCUCC
((((((....[[[[[)))))).(((((.......)))))..........(((((((.........)))))))]]]]]
>>_PKB237:_West_Nile_virus_(WNV_PK3end)
ACCUGGGAUAGACUAGGGGAUCUUCUGCUCUGCACAACCAGCCACACGGCACAGUGCGCCGACAUAGGUGGCUGGUGGUGCUAGAACACAGGAUCU
.(((((..[[[[)))))......]]]].(((((((.(((((((((.((((.......))))......))))))))).)))).)))...........
>>_PKB238:_Dengue_virus_type_2_(DEN2_PK1)
AUGGGGGCCCAAGGUGAGAUGAAGCUGUAGUCUCACUGGAAGGACUAGAGGUUAGAGGAGACCCCCCCAAAACAAAAAACAGCA
.((((((((...((((((((...[[[[[.))))))))....))......((((......)))))))))).........]]]]].
>>_PKB240:_beet_chlorosis_virus_(BChV)
GGGAAAUGGACUGAGCGGCGCCGACCGCCAAACAACCGGCA
..............((((.[[[[.))))........]]]].
>>_PKB241:_Montana_Myotis_leukoencephalitis_virus_(MMLV_PKb)
AGAGAGUUAUUCGCUCCUCUCGAGAUUGAGCGGC
.(((((....[[[[[[)))))......]]]]]].
>>_PKB242:_Rio_Bravo_virus_(RBV_PKb)
UGAGGUUUUUCCCCUCCCUCAUGAUGAGGGGAAG
.((((...[[[[[[[[)))).....]]]]]]]].
>>_PKB244:_hepatitis_A_virus_(HAV)
UUAAACAAAUUUUCUUAAAAUUUCUGAGGUUUGUUUAUUUCUUUUAUCAGUAAAU
.((((((((((.........[[[[[[[)))))))))).........]]]].]]].
>>_PKB245:_Human_Parechovirus_1_(HPeV1)
CCCAGCCUUGGGGUGGCUGGUCAAUAAAAACCCCC
.((((((..[[[[[)))))).........]]]]].
>>_PKB247:_Nemesia_ring_necrosis_virus_(NeRNV_PKa)
CCCCUGUCCCGGGUAGGGAACC
.(((..[[[[)))..]]]]...
>>_PKB248:_Nemesia_ring_necrosis_virus_(NeRNV_PKb)
UGUUCCUUGGAUUGCUACGUUCACCAGAUUUGUGUAAUCUGGCCGUUAGGAACUUAAAAUUGCGCG
.((((((.....[[[((((....(((((((.....))))))).))))))))))........]]]..
>>_PKB249:_Nemesia_ring_necrosis_virus_(NeRNV_UPD-PK1)
UAGUGUUUCGGCUUCCACUUAAAUCGAAAGCCA
.((((....[[[[[[))))......].]]]]].
>>_PKB250:_Nemesia_ring_necrosis_virus_(NeRNV_UPD-PK2)
GGGUGGCGCACACCACAGUGCGUA
.(((.[[[[[[)))...]]]]]].
>>_PKB251:_Nemesia_ring_necrosis_virus_(NeRNV_UPD-PK3)
CAGCCUCUCACAGCUUCCUCGUGAGG
.(((..[[[[[.))).....]]]]].
>>_PKB253:_White_Bream_Virus_(WBV)
UUUAAACUGGUGGGGCAGUGUCUAGGAUUGACGUUAGACACUGCUUUUUGCCCGUUUCAAACAGGUGAAUACAAACCGUCAU
...........((((((((((((((...[[[[[)))))))))))))).............................]]]]].
>>_PKB254:_SARS_coronavirus_(SARS-CoV)
UUUAAACGGGUUUGCGGUGUAAGUGCAGCCCGUCUUACACCGUGCGGCACAGGCACUAGUACUGAUGUCGUCUACAGGGCUU
............(((((((((((...[[[[[[[)))))))))))((((((((.........))).)))))...]].]]]]].
>>_PKB255:_mouse_hepatitis_virus_(MHV)
CUCUCUAUCAGAAUGGAUGUCUUGCUGUCAUAACAGAUAGAGAAGGUUGUGGCAGA
.((((((((...............[[[[[[[[[[.))))))))..]]]]]]]]]].
>>_PKB256:_bovine_coronavirus_(BCV)
CUCUCUAUCAGAAUGGAUGUCUUGCUGCUAUAAUAGAUAGAGAAGGUUAUAGCAGA
.((((((((...............[[[[[[[[[[.))))))))..]]]]]]]]]].
>>_PKB257:_Mus_musculus_(mouse)_(Mm_Edr)
GGGAAACUCCCCGGCCCCGCUGUAGGGGGACCUUCAGCGACAGGGCCAGAACGAAUAAGGUCCCCA
............((((((((((...[[[[[[[[[)))))...))))).........]]]]]]]]].
>>_PKB258:_Homo_sapiens_(Hs_Ma3)
GGGAAACGGGAACUGGGCUUGGGACAAGAGCCAUCCCAAGUCCAAGGCCAAGUAGGCUCG
.............(((((((((((...[[[[[.)))))))))))..........]]]]].
>>_PKB259:_potato_yellow_vein_virus_(PYVV1)
CGGUAGAAAAGAUGGUUUAAACCACGCCUUCUACCAAGUUAGUAAAUAAAUAGGCGG
.((((((.....((((....))))[[[[[))))))................]]]]].
>>_PKB260:_potato_yellow_vein_virus_(PYVV2)
AGUAGAAAAGUUGGUGCUUAGACCACGCCCUCUACCGUAAUAAUAGAUAAAUAGGCG
.(((((.....((((......))))[[[[.)))))..................]]]]
>>_PKB261:_potato_yellow_vein_virus_(PYVV3)
CGGUAGAAAAGAUGGUUUGAAAACCACGCCUUCUACCAAUAUAGUAAAUAAAUAGGCGG
.((((((.....(((((....)))))[[[[[))))))................]]]]].
>>_PKB262:_cucumber_yellows_virus_(CuYV1)
CGUUUGGUCGAAUGCUACUAGAGCAGCCUGACCAAACUAGUAUUAGUAAAUAAAGG
.((((((((...((((.....)))).[[[))))))))................]]]
>>_PKB263:_cucurbit_yellow_stunting_disorder_virus_(CYSDV1)
CGACACUCUAAAGAGUUCCGUGAGGAACCACCUUGAGUGUCUAGUUAUAAAUAAACUAGGUC
.(((((((......(((((....))))).[[[[.)))))))................]]]].
>>_PKB264:_cucurbit_yellow_stunting_disorder_virus_(CYSDV2)
CGACACUCUAAAGUGUUCCAAGAGGAACCACCUUGAGUGUCUAGUUAUAAAUAAACUAGGUC
.(((((((......(((((....))))).[[[[.)))))))................]]]].
>>_PKB265:_sweet_potato_chlorotic_stunt_virus_(SPCSV1)
CGGUUUUCCUAAAUCGUCGUGAGACGGACCUUGGAAAACCUAGUAUUUAAAUAACUAGGUC
.((((((((.....((((....))))[[[[[.))))))))................]]]]]
>>_PKB266:_lettuce_infectious_yellows_virus_(LIYV1)
UGUCUUCCUAAAAUCCUUGGAAGACUGUAUAUAUAGAAUAAAGGUCG
.(((((((......[[[[)))))))...............]]]]...
>>_PKB267:_little_cherry_virus_1_(LChV-1)
AAUGCAACUUUUAAAUAGUUUAUCUGUUAAGAUAAACCACCUAGGUUGCAUAUAUAAAAAAUAAAAGGUGCC
.(((((((((.......((((((((....))))))))[[[[[)))))))))..............]]]]]..
>>_PKB268:_beet_yellows_virus_(BYV)
CUCCUAGCGAAGUCCCGCUAGGAAGAAAAAAUAAGGGCCG
.(((((((...[[[[.)))))))...........]]]]..
>>_PKB269:_citrus_tristeza_virus_(CTV)
AGUUCUCCUUAGAGUGUGUGUUGUUUACCCAACGCACUGUCCCUAUGGGGGGCCAACAUAGGUCCA
.(((((((.......((((((((......))))))))....[[[[[)))))))....]]]]]....
>>_PKB270:_Pineapple_mealybug_wilt_associated_virus_-_2_(PMWaV-2)
CAAAGUCCUAUAAACCUCAAUAAUCCCUCGUUAGGAGGGACACGCGAGGACUUUGGCGUGCC
.((((((((..............((((((.....))))))[[[[[.)))))))).]]]]]..
>>_PKB271:_Grapevine_leafroll-associated_virus_-_2_(GLRaV-3)
ACGCCAAAAUCCAAUUAAAGUUUGGGACCUAGGCGGGCCUCUUACGAGGCUAACUUAUCGACAAUAAGUUAGGUC
.((((.....((((.......))))[[[[[[))))((((((....))))))..................]]]]]]
>>_PKB272:_strawberry_chlorotic_fleck_associated_virus_(SCFaV)
ACUGUGAUUAUAAAAGUGGAGUACUAAAGUACCCACUACCUUUAAUCACAGACAAUAAAGGUCCAU
.((((((((.....(((((.((((....)))))))))[[[[[[)))))))).....]]]]]]....
>>_PKB273:_influenza_A_virus,_strain_A/PR/8/34_(IAV_PK_NS)
UUCCAGGACAUACUGCUGAGGAUGUCAAAAAUGCAGUUGGAGUCCUCA
.(((((...........[[[[[[.............)))))]]]]]].
>>_PKB274:_influenza_B_virus,_strain_B/Victoria/02/1987_(IBV_PK_NS)
ACUGAUGAUCUUACAGUGGAGGAUGAAGAAGAUGGCCAUCGGAUCCUCA
.((((((...........[[[[[[............))))))]]]]]].
>>_PKB275:_Bacillus_subtilis_(Bs_glmS_P3.1)
CCGGCUGAGUGUGCAGAUCACAGCCGUAAGAAUUUCUUCAAACCAAGGGGGUGACUCCUUGAACAAAGAGAAAUCACAUGAUCUU
.((((((.......[[[[[[)))))).....(((((((.....(((((((....)))))))......)))))))....]]]]]].
>>_PKB276:_Bacillus_subtilis_(Bs_glmS_P1.1)
CGCCCGAACUAAGCGCCCGGAAAAAGGCUUAGUUGACGAGGAUGGAGGUUAUCGAAUUUCGCGGAUCCUCCCG
.(((((((((((((............)))))))).........[[[[[....(((...))))))))]]]]]..
>>_PKB277:_tobacco_etch_virus_(TEV_PK1)
CGAAUCUCAAGCAAUCAAGCAUUCUACUUCUAUUGCA
.((((((...[[[[[..)).)))).......]]]]].
>>_PKB278:_tobacco_etch_virus_(TEV_PK2)
AUUUAAAUCAUUUCUUUUAAAGCAAAAGC
.((((((...[[[..))))))....]]].
>>_PKB279:_tobacco_etch_virus_(TEV_PK3)
CAAUUUUCUGAAAAUUUUCAC
.(((((..[[[))))).]]].
>>_PKB280:_Visna-Maedi_virus_(VMV)
GGGAAACAACAGGAGGGGGCCACGUGUGGUGCCGUCCGCGCCCCCUAUGUUGUAACAGAAGCACCACC
.............(((((((.....[[[[[[[.......)))))))..............]]]]]]].
>>_PKB281:_sugarcane_yellow_leaf_virus_(ScYLV)
GGGAAACGAGCCAAGUGGCGCCGACCACUUAAAAACACCGGAA
.............(((((..[[[.))))).........]]]..
>>_PKB282:_foot-and-mouth_disease_virus,_serotype_A_(FMDV-A_PKI)
CCGUCGUUUCCGACGUAAAAGGAAGCAA
.((((..[[[[)))).....]]]]....
>>_PKB283:_foot-and-mouth_disease_virus,_serotype_A_(FMDV-A_PKII)
CCGCCUGUCCCGGCGUUAAAGGGAAGUAA
.((((..[[[[)))).....]]]].....
>>_PKB284:_foot-and-mouth_disease_virus,_serotype_A_(FMDV-A_PKIII)
ACCGCCUACCCCGGCGUUAACGGGGAACAA
..((((..[[[[)))).....]]]].....
>>_PKB285:_foot-and-mouth_disease_virus,_serotype_O_(FMDV-O1K_PKI)
ACCGUCGUUCCCGACGUAAAAGGGAGG
..((((..[[[[)))).....]]]]..
>>_PKB286:_foot-and-mouth_disease_virus,_serotype_O_(FMDV-O1K_PKII)
ACCGUCCGGCCCGACGUAAAAGGGUGGUAA
..((((...[[[)))).....]]]......
>>_PKB287:_foot-and-mouth_disease_virus,_serotype_O_(FMDV-O1K_PKIII)
CCGUCUUUCCCGACGUUAAAGGGAUG
.((((..[[[[)))).....]]]]..
>>_PKB288:_foot-and-mouth_disease_virus,_serotype_O_(FMDV-O1K_PKIV)
CCUUCGCUCGGAAGUAAAACGACAA
.((((..[[[)))).....]]]...
>>_PKB289:_foot-and-mouth_disease_virus,_serotype_C_(FMDV-C_PKI)
ACCGUCGUUCCCGACGUAAAAGGGAUGU
..((((..[[[[)))).....]]]]...
>>_PKB290:_foot-and-mouth_disease_virus,_serotype_C_(FMDV-C_PKII)
ACCGUCUCUCCCGACGUUAAAGGGAUGUAA
..((((..[[[[)))).....]]]].....
>>_PKB291:_foot-and-mouth_disease_virus,_serotype_C_(FMDV-C_PKIII)
CCGCCUAUCCCGGCGUUAAUGGGAGG
.((((..[[[[)))).....]]]]..
>>_PKB292:_foot-and-mouth_disease_virus,_serotype_C_(FMDV-C_PKIV)
CCUUCACCUGGAAGUAAAACAGCAA
.((((..[[[)))).....]]]...
>>_PKB293:_encephalomyocarditis_virus_(EMCV-R_PKB)
ACGUGAAGGCUACGAUAGUGCCAG
.((((..[[[)))).....]]]..
>>_PKB294:_encephalomyocarditis_virus_(EMCV-R_PKC)
AGGGCGGGUACUGCCGUAAGUGCCA
..(((.[[[[[[)))...]]]]]].
>>_PKB295:_Mengovirus_(Mengo_PKB)
ACGUGAAGGCUACGAUAGUGCCAG
.((((..[[[)))).....]]]..
>>_PKB296:_Mengovirus_(Mengo_PKC)
AGGGCGGGUCCUGCCGAAAGUGCCAA
..(((.[[[.[[)))...]].]]]..
>>_PKB297:_hepatitis_A_virus_(HAV_PK1)
AAGUCCAUGGUGAGGGGACUUGAUACCUCACCG
.(((((..[[[[[[[))))).....]]]]]]].
>>_PKB298:_hepatitis_A_virus_(HAV_PK2)
CGCCGUUUGCCUAGGCUAUAGGCUAAAUU
.(((....[[[[[)))..]]]]]......
>>_PKB299:_Theiler's_murine_encephalomyelitis_virus_(TMEV)
ACGCGGGUACUGCGAUAGUGCCACC
.(((.[[[[[[)))..]]]]]]...
>>_PKB300:__(antiHIV1-RT_1.1)
UCAAGAAUUCCGUUUUCAGUCGGGAAAAACUGAACAA
.......(((((..[[[[[[)))))...]]]]]]...
>>_PKB301:__(antiHIV1-RT_1.3a)
GAAUAUCUUCCGAAGCCGAACGGGAAAACCGGCAUCU
.......(((((..[[[[..)))))....]]]]....
>>_PKB302:__(antiHIV1-NC_psi-50-1)
GCCAGUGGUUUGCAAUGCUGGUCCGGUGCGU
(((((((...[[[[.)))))))....]]]].
>>_PKB303:_Bombyx_mori_(R2_retroPK)
AGCCCCGAUGGACGGACCGCGAGGACCGUCAAGCCUAGCAGGUACCUUCGGGUGGGGCCUUGCGAUACCUGCGGGC
.(((((....(((((.((....)).)))))...[[[.[[[[[[(((....))))))))........]]]]]]]]].
>>_PKB304:_B._subtilis_(SBU)
AGAGGUUCUAGCUACACCCUCUAUAAAAAACUAA
(((((...[[[......)))))........]]].
@article{cruz2011sequence,
title={Sequence-based identification of 3D structural modules in RNA with RMDetect},
author={Cruz, Jos{\'e} Almeida and Westhof, Eric},
journal={Nature methods},
volume={8},
number={6},
pages={513},
year={2011},
publisher={Nature Publishing Group}
}
@article{djelloul_automated_2008,
title = {Automated motif extraction and classification in {RNA} tertiary structures},
volume = {14},
issn = {1355-8382, 1469-9001},
url = {http://rnajournal.cshlp.org/content/14/12/2489},
doi = {10.1261/rna.1061108},
abstract = {We used a novel graph-based approach to extract RNA tertiary motifs. We cataloged them all and clustered them using an innovative graph similarity measure. We applied our method to three widely studied structures: Haloarcula marismortui 50S (H.m 50S), Escherichia coli 50S (E. coli 50S), and Thermus thermophilus 16S (T.th 16S) RNAs. We identified 10 known motifs without any prior knowledge of their shapes or positions. We additionally identified four putative new motifs.},
language = {en},
number = {12},
urldate = {2018-10-04},
journal = {RNA},
author = {Djelloul, Mahassine and Denise, Alain},
month = jan,
year = {2008},
pmid = {18957493},
keywords = {clustering, graph similarity, RNA tertiary structure},
pages = {2489--2497},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/6PDZZRI6/Djelloul et Denise - 2008 - Automated motif extraction and classification in R.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/28T5ICXG/2489.html:text/html}
}
@article{roll_jar3d_2016,
title = {{JAR}3D {Webserver}: {Scoring} and aligning {RNA} loop sequences to known 3D motifs},
volume = {44},
issn = {0305-1048},
shorttitle = {{JAR}3D {Webserver}},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987954/},
doi = {10.1093/nar/gkw453},
abstract = {Many non-coding RNAs have been identified and may function by forming 2D and 3D structures. RNA hairpin and internal loops are often represented as unstructured on secondary structure diagrams, but RNA 3D structures show that most such loops are structured by non-Watson–Crick basepairs and base stacking. Moreover, different RNA sequences can form the same RNA 3D motif. JAR3D finds possible 3D geometries for hairpin and internal loops by matching loop sequences to motif groups from the RNA 3D Motif Atlas, by exact sequence match when possible, and by probabilistic scoring and edit distance for novel sequences. The scoring gauges the ability of the sequences to form the same pattern of interactions observed in 3D structures of the motif. The JAR3D webserver at http://rna.bgsu.edu/jar3d/ takes one or many sequences of a single loop as input, or else one or many sequences of longer RNAs with multiple loops. Each sequence is scored against all current motif groups. The output shows the ten best-matching motif groups. Users can align input sequences to each of the motif groups found by JAR3D. JAR3D will be updated with every release of the RNA 3D Motif Atlas, and so its performance is expected to improve over time.},
number = {Web Server issue},
urldate = {2018-10-04},
journal = {Nucleic Acids Research},
author = {Roll, James and Zirbel, Craig L. and Sweeney, Blake and Petrov, Anton I. and Leontis, Neocles},
month = jul,
year = {2016},
pmid = {27235417},
pmcid = {PMC4987954},
pages = {W320--W327},
file = {PubMed Central Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/KWD59J5I/Roll et al. - 2016 - JAR3D Webserver Scoring and aligning RNA loop seq.pdf:application/pdf}
}
@article{zhong_rnamotifscan:_2010,
title = {{RNAMotifScan}: automatic identification of {RNA} structural motifs using secondary structural alignment},
volume = {38},
issn = {0305-1048},
shorttitle = {{RNAMotifScan}},
url = {https://academic.oup.com/nar/article/38/18/e176/1069222},
doi = {10.1093/nar/gkq672},
abstract = {Abstract. Recent studies have shown that RNA structural motifs play essential roles in RNA folding and interaction with other molecules. Computational identifi},
language = {en},
number = {18},
urldate = {2018-10-04},
journal = {Nucleic Acids Research},
author = {Zhong, Cuncong and Tang, Haixu and Zhang, Shaojie},
month = oct,
year = {2010},
pages = {e176--e176},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/ESXL69Q6/Zhong et al. - 2010 - RNAMotifScan automatic identification of RNA stru.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/MWTNC94Z/1069222.html:text/html}
}
@inproceedings{tahi_fast_2003,
title = {A fast algorithm for {RNA} secondary structure prediction including pseudoknots},
doi = {10.1109/BIBE.2003.1188924},
abstract = {Many important RNA molecules contain pseudoknots, which are generally excluded by the definition of the secondary structure, mainly for computational reasons. Still, most existing algorithms for secondary structure prediction are not satisfactory in results and complexities, even when pseudoknots are not allowed. We present an algorithm, called P-DCFold, for the prediction of RNA secondary structures including all kinds of pseudoknots. It is based on the comparative approach. The helices are searched recursively, from more "likely" to less "likely", using the "Divide and Conquer" approach. This approach, which allows to limit the amount of searching, is possible when only non-interleaved helices are searched for. The pseudoknots are therefore searched in several steps, each helix of the pseudoknot being selected in a different step. P-DCFold has been applied to tmRNA and RnaseP sequences. In less than two seconds, their respective secondary structures, including their pseudoknots, have been recovered very efficiently.},
booktitle = {Third {IEEE} {Symposium} on {Bioinformatics} and {Bioengineering}, 2003. {Proceedings}.},
author = {Tahi, F. and Engelen, S. and Regnier, M.},
month = mar,
year = {2003},
keywords = {2 s, Bioinformatics, Biological control systems, computational methods, computational reasons, Context modeling, Databases, Evolution (biology), fast algorithm, macromolecules, molecular biophysics, molecular configurations, noninterleaved helices, Predictive models, pseudoknots, recursive searches, RNA, RNA secondary structure prediction, RnaseP, Robustness, secondary structures, spatial structures, Stochastic processes, Switches, tmRNA},
pages = {11--17},
file = {IEEE Xplore Abstract Record:/nhome/siniac/lbecquey/Zotero/storage/HTHXNSVF/1188924.html:text/html}
}
@article{tahi_p-dcfold_2005,
title = {P-dcfold or how to predict all kinds of pseudoknots in rna secondary structures},
volume = {14},
issn = {0218-2130},
url = {https://www.worldscientific.com/doi/abs/10.1142/S021821300500234X},
doi = {10.1142/S021821300500234X},
abstract = {Pseudoknots play important roles in many RNAs. But for computational reasons, pseudoknots are usually excluded from the definition of RNA secondary structures. Indeed, prediction of pseudoknots increase very highly the complexities in time of the algorithms, knowing that all existing algorithms for RNA secondary structure prediction have complexities at least of O(n3). Some algorithms have been developed for searching pseudoknots, but all of them have very high complexities, and consider generally particular kinds of pseudoknots.We present an algorithm, called P-DCFold based on the comparative approach, for the prediction of RNA secondary structures including all kinds of pseudoknots. The helices are searched recursively using the "Divide and Conquer" approach, searching the helices from the "most significant" to the "less significant". A selected helix subdivide the sequence into two sub-sequences, the internal one and a concatenation of the two externals. This approach is used to search non-interleaved helices and allows to limit the space of searching. To search for pseudoknots, the processing is reiterated. Therefore, each helix of the pseudoknot is selected in a different step.P-DCFold has been applied to several RNA sequences. In less than two seconds, their respective secondary structures, including their pseudoknots, have been recovered very efficiently.},
number = {05},
urldate = {2018-10-02},
journal = {International Journal on Artificial Intelligence Tools},
author = {Tahi, Fariza and Stefan, Engelen and Regnier, Mireille},
month = oct,
year = {2005},
pages = {703--716},
file = {Snapshot:/nhome/siniac/lbecquey/Zotero/storage/GEIBPMJ4/S021821300500234X.html:text/html}
}
@article{tempel_fast_2012,
title = {A fast ab-initio method for predicting {miRNA} precursors in genomes},
volume = {40},
issn = {0305-1048},
url = {https://academic.oup.com/nar/article/40/11/e80/2409259},
doi = {10.1093/nar/gks146},
abstract = {Abstract. miRNAs are small non coding RNA structures which play important roles in biological processes. Finding miRNA precursors in genomes is therefore an i},
language = {en},
number = {11},
urldate = {2018-10-02},
journal = {Nucleic Acids Research},
author = {Tempel, Sébastien and Tahi, Fariza},
month = jun,
year = {2012},
pages = {e80--e80},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/BSCSRRL2/Tempel et Tahi - 2012 - A fast ab-initio method for predicting miRNA precu.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/ZTG4GDDT/2409259.html:text/html}
}
@article{reinharz_towards_2012,
title = {Towards 3D structure prediction of large {RNA} molecules: an integer programming framework to insert local 3D motifs in {RNA} secondary structure},
volume = {28},
issn = {1367-4803},
shorttitle = {Towards 3D structure prediction of large {RNA} molecules},
url = {https://academic.oup.com/bioinformatics/article/28/12/i207/269345},
doi = {10.1093/bioinformatics/bts226},
abstract = {Abstract. Motivation: The prediction of RNA 3D structures from its sequence only is a milestone to RNA function analysis and prediction. In recent years, many},
language = {en},
number = {12},
urldate = {2018-10-01},
journal = {Bioinformatics},
author = {Reinharz, Vladimir and Major, François and Waldispühl, Jérôme},
month = jun,
year = {2012},
pages = {i207--i214},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/IAYRK53E/Reinharz et al. - 2012 - Towards 3D structure prediction of large RNA molec.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/SSMTN6YZ/269345.html:text/html}
}
@article{pan_predicting_nodate,
title = {Predicting {RNA}–protein binding sites and motifs through combining local and global deep convolutional neural networks},
url = {https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/bty364/4990826},
doi = {10.1093/bioinformatics/bty364},
abstract = {AbstractMotivation. RNA-binding proteins (RBPs) take over 5–10\% of the eukaryotic proteome and play key roles in many biological processes, e.g. gene regulatio},
language = {en},
urldate = {2018-06-12},
journal = {Bioinformatics},
author = {Pan, Xiaoyong and Shen, Hong-Bin and Valencia, Alfonso},
file = {10.1093@bioinformatics@bty364.pdf:/nhome/siniac/lbecquey/Zotero/storage/KUQZ2HNN/10.1093@bioinformatics@bty364.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/TLQUYHEU/4990826.html:text/html}
}
@article{yi_brief_2017,
title = {A {Brief} {Review} of {RNA}–{Protein} {Interaction} {Database} {Resources}},
volume = {3},
issn = {2311-553X},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5832006/},
doi = {10.3390/ncrna3010006},
abstract = {RNA–Protein interactions play critical roles in various biological processes. By collecting and analyzing the RNA–Protein interactions and binding sites from experiments and predictions, RNA–Protein interaction databases have become an essential resource for the exploration of the transcriptional and post-transcriptional regulatory network. Here, we briefly review several widely used RNA–Protein interaction database resources developed in recent years to provide a guide of these databases. The content and major functions in databases are presented. The brief description of database helps users to quickly choose the database containing information they interested. In short, these RNA–Protein interaction database resources are continually updated, but the current state shows the efforts to identify and analyze the large amount of RNA–Protein interactions.},
number = {1},
urldate = {2018-06-08},
journal = {Non-Coding RNA},
author = {Yi, Ying and Zhao, Yue and Huang, Yan and Wang, Dong},
month = jan,
year = {2017},
pmid = {29657278},
pmcid = {PMC5832006},
file = {PubMed Central Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/C3ZRG7MJ/Yi et al. - 2017 - A Brief Review of RNA–Protein Interaction Database.pdf:application/pdf}
}
@article{das_automated_2007,
title = {Automated de novo prediction of native-like {RNA} tertiary structures},
volume = {104},
copyright = {© 2007 by The National Academy of Sciences of the USA. Freely available online through the PNAS open access option.},
issn = {0027-8424, 1091-6490},
url = {http://www.pnas.org/content/104/37/14664},
doi = {10.1073/pnas.0703836104},
abstract = {RNA tertiary structure prediction has been based almost entirely on base-pairing constraints derived from phylogenetic covariation analysis. We describe here a complementary approach, inspired by the Rosetta low-resolution protein structure prediction method, that seeks the lowest energy tertiary structure for a given RNA sequence without using evolutionary information. In a benchmark test of 20 RNA sequences with known structure and lengths of ≈30 nt, the new method reproduces better than 90\% of Watson–Crick base pairs, comparable with the accuracy of secondary structure prediction methods. In more than half the cases, at least one of the top five models agrees with the native structure to better than 4 Å rmsd over the backbone. Most importantly, the method recapitulates more than one-third of non-Watson–Crick base pairs seen in the native structures. Tandem stacks of “sheared” base pairs, base triplets, and pseudoknots are among the noncanonical features reproduced in the models. In the cases in which none of the top five models were native-like, higher energy conformations similar to the native structures are still sampled frequently but not assigned low energies. These results suggest that modest improvements in the energy function, together with the incorporation of information from phylogenetic covariance, may allow confident and accurate structure prediction for larger and more complex RNA chains.},
language = {en},
number = {37},
urldate = {2018-06-04},
journal = {Proceedings of the National Academy of Sciences},
author = {Das, Rhiju and Baker, David},
month = sep,
year = {2007},
pmid = {17726102},
keywords = {ab initio, energy-based, fragment assembly, nucleic acid, Rosetta},
pages = {14664--14669},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/H79FEN6P/Das and Baker - 2007 - Automated de novo prediction of native-like RNA te.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/WH7PUGNW/14664.html:text/html}
}
@article{cao_physics-based_2011,
title = {Physics-based de novo prediction of {RNA} 3D structures},
volume = {115},
issn = {1520-6106},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3072456/},
doi = {10.1021/jp112059y},
abstract = {Current experiments on structural determination cannot keep up the pace with the steadily emerging RNA sequences and new functions. This underscores the request for an accurate model for RNA three-dimensional (3D) structural prediction. Although considerable progress has been made in mechanistic studies, accurate prediction for RNA tertiary folding from sequence remains an unsolved problem. The first and most important requirement for the prediction of RNA structure from physical principles is an accurate free energy model. A recently developed three-vector virtual bond-based RNA folding model (“Vfold”) has allowed us to compute the chain entropy and predict folding free energies and structures for RNA secondary structures and simple pseudoknots. Here we develop a free energy-based method to predict larger more complex RNA tertiary folds. The approach is based on a multiscaling strategy: from the nucleotide sequence, we predict the two-dimensional (2D) structures (defined by the base pairs and tertiary contacts); based on the 2D structure, we construct a 3D scaffold; with the 3D scaffold as the initial state, we combine AMBER energy minimization and PDB-based fragment search to predict the all-atom structure. A key advantage of the approach is the statistical mechanical calculation for the conformational entropy of RNA structures, including those with cross-linked loops. Benchmark tests show that the model leads to significant improvements in RNA 3D structure prediction.},
number = {14},
urldate = {2018-06-04},
journal = {The journal of physical chemistry. B},
author = {Cao, Song and Chen, Shi-Jie},
month = apr,
year = {2011},
pmid = {21413701},
pmcid = {PMC3072456},
pages = {4216--4226},
file = {PubMed Central Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/ZY98QT5K/Cao and Chen - 2011 - Physics-based de novo prediction of RNA 3D structu.pdf:application/pdf}
}
@article{bottaro_towards_2015,
title = {Towards de novo {RNA} 3D {Structure} {Prediction}},
volume = {2},
copyright = {Copyright (c) 2015 Sandro Bottaro, Francesco Di Palma, Giovanni Bussi},
issn = {2375-2467},
url = {http://www.smartscitech.com/index.php/RD/article/view/544},
doi = {10.14800/rd.544},
abstract = {RNA is a fundamental class of biomolecules that mediate a large variety of molecular processes within the cell. Computational algorithms can be of great help in the understanding of RNA structure-function relationship. One of the main challenges in this field is the development of structure-prediction algorithms, which aim at the prediction of the three-dimensional (3D) native fold from the sole knowledge of the sequence. In a recent paper, we have introduced a scoring function for RNA structure prediction. Here, we analyze in detail the performance of the method, we underline strengths and shortcomings, and we discuss the results with respect to state-of-the-art techniques. These observations provide a starting point for improving current methodologies, thus paving the way to the advances of more accurate approaches for RNA 3D structure prediction.},
language = {en},
number = {2},
urldate = {2018-06-04},
journal = {RNA \& DISEASE},
author = {Bottaro, Sandro and Palma, Francesco Di and Bussi, Giovanni},
month = jan,
year = {2015},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/SWAYZQEV/Bottaro et al. - 2015 - Towards de novo RNA 3D Structure Prediction.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/SQMMYVCU/544.html:text/html}
}
@article{bindewald_multistrand_2016,
title = {Multistrand {Structure} {Prediction} of {Nucleic} {Acid} {Assemblies} and {Design} of {RNA} {Switches}},
volume = {16},
issn = {1530-6984},
url = {https://doi.org/10.1021/acs.nanolett.5b04651},
doi = {10.1021/acs.nanolett.5b04651},
abstract = {RNA is an attractive material for the creation of molecular logic gates that release programmed functionalities only in the presence of specific molecular interaction partners. Here we present HyperFold, a multistrand RNA/DNA structure prediction approach for predicting nucleic acid complexes that can contain pseudoknots. We show that HyperFold also performs competitively compared to other published folding algorithms. We performed a large variety of RNA/DNA hybrid reassociation experiments for different concentrations, DNA toehold lengths, and G+C content and find that the observed tendencies for reassociation correspond well to computational predictions. Importantly, we apply this method to the design and experimental verification of a two-stranded RNA molecular switch that upon binding to a single-stranded RNA toehold disease-marker trigger mRNA changes its conformation releasing an shRNA-like Dicer substrate structure. To demonstrate the concept, connective tissue growth factor (CTGF) mRNA and enhanced green fluorescent protein (eGFP) mRNA were chosen as trigger and target sequences, respectively. In vitro experiments confirm the formation of an RNA switch and demonstrate that the functional unit is being released when the trigger RNA interacts with the switch toehold. The designed RNA switch is shown to be functional in MDA-MB-231 breast cancer cells. Several other switches were also designed and tested. We conclude that this approach has considerable potential because, in principle, it allows the release of an siRNA designed against a gene that differs from the gene that is utilized as a biomarker for a disease state.},
number = {3},
urldate = {2018-05-31},
journal = {Nano Letters},
author = {Bindewald, Eckart and Afonin, Kirill A. and Viard, Mathias and Zakrevsky, Paul and Kim, Taejin and Shapiro, Bruce A.},
month = mar,
year = {2016},
pages = {1726--1735},
file = {ACS Full Text Snapshot:/nhome/siniac/lbecquey/Zotero/storage/285MME3I/acs.nanolett.html:text/html}
}
@article{ge_novo_2018,
title = {De novo discovery of structural motifs in {RNA} 3D structures through clustering},
volume = {46},
issn = {0305-1048},
url = {https://academic.oup.com/nar/article/46/9/4783/4925243},
doi = {10.1093/nar/gky139},
abstract = {Abstract. As functional components in three-dimensional (3D) conformation of an RNA, the RNA structural motifs provide an easy way to associate the molecular a},
language = {en},
number = {9},
urldate = {2018-05-31},
journal = {Nucleic Acids Research},
author = {Ge, Ping and Islam, Shahidul and Zhong, Cuncong and Zhang, Shaojie},
month = may,
year = {2018},
pages = {4783--4793},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/8YS7LY6E/Ge et al. - 2018 - De novo discovery of structural motifs in RNA 3D s.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/4TLRV8ZT/4925243.html:text/html}
}
@article{wang_rna_2018,
title = {{RNA} 3-dimensional structural motifs as a critical constraint of viroid {RNA} evolution},
volume = {14},
issn = {1553-7374},
url = {http://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1006801},
doi = {10.1371/journal.ppat.1006801},
language = {en},
number = {2},
urldate = {2018-05-31},
journal = {PLOS Pathogens},
author = {Wang, Ying and Zirbel, Craig L. and Leontis, Neocles B. and Ding, Biao},
month = feb,
year = {2018},
keywords = {Non-coding RNA sequences, RNA structure, RNA viruses, Sequence motif analysis, Viral evolution, Viral replication, Viral structure, Viroids},
pages = {e1006801},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/M3P6GCA7/Wang et al. - 2018 - RNA 3-dimensional structural motifs as a critical .pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/3YRBKI96/article.html:text/html}
}
@article{lorenz_viennarna_2011,
title = {{ViennaRNA} {Package} 2.0},
volume = {6},
issn = {1748-7188},
url = {https://doi.org/10.1186/1748-7188-6-26},
doi = {10.1186/1748-7188-6-26},
abstract = {Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties.},
urldate = {2018-05-31},
journal = {Algorithms for Molecular Biology},
author = {Lorenz, Ronny and Bernhart, Stephan H. and Höner zu Siederdissen, Christian and Tafer, Hakim and Flamm, Christoph and Stadler, Peter F. and Hofacker, Ivo L.},
month = nov,
year = {2011},
keywords = {Consensus Structure, Folding Algorithm, Matthews Correlation Coefficient, Minimum Free Energy, Partition Function},
pages = {26},
annote = {Pages 26 in PDF},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/WFPBA2H8/Lorenz et al. - 2011 - ViennaRNA Package 2.0.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/ADNFF9EA/1748-7188-6-26.html:text/html}
}
@article{janssen_rna_2015,
title = {The {RNA} shapes studio},
volume = {31},
issn = {1367-4803},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4308662/},
doi = {10.1093/bioinformatics/btu649},
abstract = {Motivation: Abstract shape analysis, first proposed in 2004, allows one to extract several relevant structures from the folding space of an RNA sequence, preferable to focusing in a single structure of minimal free energy. We report recent extensions to this approach., Results: We have rebuilt the original RNAshapes as a repository of components that allows us to integrate several established tools for RNA structure analysis: RNAshapes, RNAalishapes and pknotsRG, including its recent extension pKiss. As a spin-off, we obtain heretofore unavailable functionality: e. g. with pKiss, we can now perform abstract shape analysis for structures holding pseudoknots up to the complexity of kissing hairpin motifs. The new tool pAliKiss can predict kissing hairpin motifs from aligned sequences. Along with the integration, the functionality of the tools was also extended in manifold ways., Availability and implementation: As before, the tool is available on the Bielefeld Bioinformatics server at http://bibiserv.cebitec.uni-bielefeld.de/rnashapesstudio., Contact: bibi-help@cebitec.uni-bielefeld.de},
number = {3},
urldate = {2018-05-31},
journal = {Bioinformatics},
author = {Janssen, Stefan and Giegerich, Robert},
month = feb,
year = {2015},
pmid = {25273103},
pmcid = {PMC4308662},
pages = {423--425},
file = {PubMed Central Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/KFQTVDR3/Janssen and Giegerich - 2015 - The RNA shapes studio.pdf:application/pdf}
}
@article{parlea_rna_2016,
series = {Advances in {RNA} {Structure} {Determination}},
title = {The {RNA} 3D {Motif} {Atlas}: {Computational} methods for extraction, organization and evaluation of {RNA} motifs},
volume = {103},
issn = {1046-2023},
shorttitle = {The {RNA} 3D {Motif} {Atlas}},
url = {http://www.sciencedirect.com/science/article/pii/S1046202316301049},
doi = {10.1016/j.ymeth.2016.04.025},
abstract = {RNA 3D motifs occupy places in structured RNA molecules that correspond to the hairpin, internal and multi-helix junction “loops” of their secondary structure representations. As many as 40\% of the nucleotides of an RNA molecule can belong to these structural elements, which are distinct from the regular double helical regions formed by contiguous AU, GC, and GU Watson-Crick basepairs. With the large number of atomic- or near atomic-resolution 3D structures appearing in a steady stream in the PDB/NDB structure databases, the automated identification, extraction, comparison, clustering and visualization of these structural elements presents an opportunity to enhance RNA science. Three broad applications are: (1) identification of modular, autonomous structural units for RNA nanotechnology, nanobiology and synthetic biology applications; (2) bioinformatic analysis to improve RNA 3D structure prediction from sequence; and (3) creation of searchable databases for exploring the binding specificities, structural flexibility, and dynamics of these RNA elements. In this contribution, we review methods developed for computational extraction of hairpin and internal loop motifs from a non-redundant set of high-quality RNA 3D structures. We provide a statistical summary of the extracted hairpin and internal loop motifs in the most recent version of the RNA 3D Motif Atlas. We also explore the reliability and accuracy of the extraction process by examining its performance in clustering recurrent motifs from homologous ribosomal RNA (rRNA) structures. We conclude with a summary of remaining challenges, especially with regard to extraction of multi-helix junction motifs.},
urldate = {2018-05-31},
journal = {Methods},
author = {Parlea, Lorena G. and Sweeney, Blake A. and Hosseini-Asanjan, Maryam and Zirbel, Craig L. and Leontis, Neocles B.},
month = jul,
year = {2016},
keywords = {Hairpin loop, Internal loop, Multi-helix junction loop, Non-Watson-Crick basepair, RNA 3D Motif, Structured RNA molecules},
pages = {99--119},
file = {ScienceDirect Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/HM9ZDD83/Parlea et al. - 2016 - The RNA 3D Motif Atlas Computational methods for .pdf:application/pdf;ScienceDirect Snapshot:/nhome/siniac/lbecquey/Zotero/storage/ANJRICVQ/S1046202316301049.html:text/html}
}
@article{legendre_bi-objective_2018,
title = {Bi-objective integer programming for {RNA} secondary structure prediction with pseudoknots},
volume = {19},
issn = {1471-2105},
url = {https://doi.org/10.1186/s12859-018-2007-7},
doi = {10.1186/s12859-018-2007-7},
abstract = {RNA structure prediction is an important field in bioinformatics, and numerous methods and tools have been proposed. Pseudoknots are specific motifs of RNA secondary structures that are difficult to predict. Almost all existing methods are based on a single model and return one solution, often missing the real structure. An alternative approach would be to combine different models and return a (small) set of solutions, maximizing its quality and diversity in order to increase the probability that it contains the real structure.},
urldate = {2018-05-24},
journal = {BMC Bioinformatics},
author = {Legendre, Audrey and Angel, Eric and Tahi, Fariza},
month = jan,
year = {2018},
keywords = {RNA, Bi-objective, Integer programming, Optimal solutions, Pseudoknot, Secondary structure, Sub-optimal solutions},
pages = {13},
annote = {Pages 13 in PDF},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/4YMW5M4S/Legendre et al. - 2018 - Bi-objective integer programming for RNA secondary.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/XP46BMHH/s12859-018-2007-7.html:text/html}
}
@article{sarver_fr3d:_2008,
title = {{FR}3D: finding local and composite recurrent structural motifs in {RNA} 3D structures},
volume = {56},
issn = {1432-1416},
shorttitle = {{FR}3D},
url = {https://doi.org/10.1007/s00285-007-0110-x},
doi = {10.1007/s00285-007-0110-x},
abstract = {New methods are described for finding recurrent three-dimensional (3D) motifs in RNA atomic-resolution structures. Recurrent RNA 3D motifs are sets of RNA nucleotides with similar spatial arrangements. They can be local or composite. Local motifs comprise nucleotides that occur in the same hairpin or internal loop. Composite motifs comprise nucleotides belonging to three or more different RNA strand segments or molecules. We use a base-centered approach to construct efficient, yet exhaustive search procedures using geometric, symbolic, or mixed representations of RNA structure that we implement in a suite of MATLAB programs, “Find RNA 3D” (FR3D). The first modules of FR3D preprocess structure files to classify base-pair and -stacking interactions. Each base is represented geometrically by the position of its glycosidic nitrogen in 3D space and by the rotation matrix that describes its orientation with respect to a common frame. Base-pairing and base-stacking interactions are calculated from the base geometries and are represented symbolically according to the Leontis/Westhof basepairing classification, extended to include base-stacking. These data are stored and used to organize motif searches. For geometric searches, the user supplies the 3D structure of a query motif which FR3D uses to find and score geometrically similar candidate motifs, without regard to the sequential position of their nucleotides in the RNA chain or the identity of their bases. To score and rank candidate motifs, FR3D calculates a geometric discrepancy by rigidly rotating candidates to align optimally with the query motif and then comparing the relative orientations of the corresponding bases in the query and candidate motifs. Given the growing size of the RNA structure database, it is impossible to explicitly compute the discrepancy for all conceivable candidate motifs, even for motifs with less than ten nucleotides. The screening algorithm that we describe finds all candidate motifs whose geometric discrepancy with respect to the query motif falls below a user-specified cutoff discrepancy. This technique can be applied to RMSD searches. Candidate motifs identified geometrically may be further screened symbolically to identify those that contain particular basepair types or base-stacking arrangements or that conform to sequence continuity or nucleotide identity constraints. Purely symbolic searches for motifs containing user-defined sequence, continuity and interaction constraints have also been implemented. We demonstrate that FR3D finds all occurrences, both local and composite and with nucleotide substitutions, of sarcin/ricin and kink-turn motifs in the 23S and 5S ribosomal RNA 3D structures of the H. marismortui 50S ribosomal subunit and assigns the lowest discrepancy scores to bona fide examples of these motifs. The search algorithms have been optimized for speed to allow users to search the non-redundant RNA 3D structure database on a personal computer in a matter of minutes.},
language = {en},
number = {1},
urldate = {2018-10-10},
journal = {Journal of Mathematical Biology},
author = {Sarver, Michael and Zirbel, Craig L. and Stombaugh, Jesse and Mokdad, Ali and Leontis, Neocles B.},
month = jan,
year = {2008},
keywords = {05C85, 92C40},
pages = {215--252}
}
@article{petrov_webfr3dserver_2011,
title = {{WebFR}3D—a server for finding, aligning and analyzing recurrent {RNA} 3D motifs},
volume = {39},
issn = {0305-1048},
url = {https://academic.oup.com/nar/article/39/suppl_2/W50/2505799},
doi = {10.1093/nar/gkr249},
abstract = {Abstract. WebFR3D is the on-line version of ‘Find RNA 3D’ (FR3D), a program for annotating atomic-resolution RNA 3D structure files and searching them efficie},
language = {en},
number = {suppl\_2},
urldate = {2018-10-10},
journal = {Nucleic Acids Research},
author = {Petrov, Anton I. and Zirbel, Craig L. and Leontis, Neocles B.},
month = jul,
year = {2011},
pages = {W50--W55},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/WVGVFLFH/Petrov et al. - 2011 - WebFR3D—a server for finding, aligning and analyzi.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/8NMZZLKV/2505799.html:text/html}
}
@article{petrov_automated_2013,
title = {Automated classification of {RNA} 3D motifs and the {RNA} 3D {Motif} {Atlas}},
volume = {19},
issn = {1355-8382, 1469-9001},
url = {http://rnajournal.cshlp.org/content/19/10/1327},
doi = {10.1261/rna.039438.113},
abstract = {A monthly journal publishing high-quality, peer-reviewed research on all topics related to RNA and its metabolism in all organisms},
language = {en},
number = {10},
urldate = {2018-10-10},
journal = {RNA},
author = {Petrov, Anton I. and Zirbel, Craig L. and Leontis, Neocles B.},
month = jan,
year = {2013},
pmid = {23970545},
pages = {1327--1340},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/GIC5F2CJ/Petrov et al. - 2013 - Automated classification of RNA 3D motifs and the .pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/UJFVEML3/1327.full.html:text/html}
}
@article{lu_dssr:_2015,
title = {{DSSR}: an integrated software tool for dissecting the spatial structure of {RNA}},
volume = {43},
issn = {0305-1048},
shorttitle = {{DSSR}},
url = {https://academic.oup.com/nar/article/43/21/e142/2468098},
doi = {10.1093/nar/gkv716},
abstract = {Abstract. Insight into the three-dimensional architecture of RNA is essential for understanding its cellular functions. However, even the classic transfer RNA},
language = {en},
number = {21},
urldate = {2018-10-09},
journal = {Nucleic Acids Research},
author = {Lu, Xiang-Jun and Bussemaker, Harmen J. and Olson, Wilma K.},
month = dec,
year = {2015},
pages = {e142--e142},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/NURMS9UY/Lu et al. - 2015 - DSSR an integrated software tool for dissecting t.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/BTZXBR6S/2468098.html:text/html}
}
@article{antczak_rnapdbeewebserver_2014,
title = {{RNApdbee}—a webserver to derive secondary structures from pdb files of knotted and unknotted {RNAs}},
volume = {42},
issn = {0305-1048},
url = {https://academic.oup.com/nar/article/42/W1/W368/2435287},
doi = {10.1093/nar/gku330},
abstract = {Abstract. In RNA structural biology and bioinformatics an access to correct RNA secondary structure and its proper representation is of crucial importance. Thi},
language = {en},
number = {W1},
urldate = {2018-10-09},
journal = {Nucleic Acids Research},
author = {Antczak, Maciej and Zok, Tomasz and Popenda, Mariusz and Lukasiak, Piotr and Adamiak, Ryszard W. and Blazewicz, Jacek and Szachniuk, Marta},
month = jul,
year = {2014},
pages = {W368--W372},
file = {Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/RWXNJQH6/Antczak et al. - 2014 - RNApdbee—a webserver to derive secondary structure.pdf:application/pdf;Snapshot:/nhome/siniac/lbecquey/Zotero/storage/H6CZVH4F/2435287.html:text/html}
}
@article{dirksAlgorithmComputingNucleic2004,
title = {An Algorithm for Computing Nucleic Acid Base-Pairing Probabilities Including Pseudoknots},
volume = {25},
copyright = {Copyright \textcopyright{} 2004 Wiley Periodicals, Inc.},
issn = {1096-987X},
doi = {10.1002/jcc.20057},
abstract = {Given a nucleic acid sequence, a recent algorithm allows the calculation of the partition function over secondary structure space including a class of physically relevant pseudoknots. Here, we present a method for computing base-pairing probabilities starting from the output of this partition function algorithm. The approach relies on the calculation of recursion probabilities that are computed by backtracking through the partition function algorithm, applying a particular transformation at each step. This transformation is applicable to any partition function algorithm that follows the same basic dynamic programming paradigm. Base-pairing probabilities are useful for analyzing the equilibrium ensemble properties of natural and engineered nucleic acids, as demonstrated for a human telomerase RNA and a synthetic DNA nanostructure. \textcopyright{} 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1295\textendash{}1304, 2004},
language = {en},
number = {10},
journal = {Journal of Computational Chemistry},
author = {Dirks, Robert M. and Pierce, Niles A.},
year = {2004},
keywords = {pseudoknots,RNA,DNA,base-pairing probabilities,partition function},
pages = {1295-1304},
file = {/nhome/siniac/lbecquey/Zotero/storage/LA8RHBVN/jcc.html}
}
@article{laing_computational_2010,
title = {Computational approaches to 3D modeling of {RNA}},
volume = {22},
issn = {0953-8984},
url = {http://stacks.iop.org/0953-8984/22/i=28/a=283101},
doi = {10.1088/0953-8984/22/28/283101},
abstract = {Many exciting discoveries have recently revealed the versatility of RNA and its importance in a variety of functions within the cell. Since the structural features of RNA are of major importance to their biological function, there is much interest in predicting RNA structure, either in free form or in interaction with various ligands, including proteins, metabolites and other molecules. In recent years, an increasing number of researchers have developed novel RNA algorithms for predicting RNA secondary and tertiary structures. In this review, we describe current experimental and computational advances and discuss recent ideas that are transforming the traditional view of RNA folding. To evaluate the performance of the most recent RNA 3D folding algorithms, we provide a comparative study in order to test the performance of available 3D structure prediction algorithms for an RNA data set of 43 structures of various lengths and motifs. We find that the algorithms vary widely in terms of prediction quality across different RNA lengths and topologies; most predictions have very large root mean square deviations from the experimental structure. We conclude by outlining some suggestions for future RNA folding research.},
language = {en},
number = {28},
urldate = {2018-10-09},
journal = {Journal of Physics: Condensed Matter},
author = {Laing, Christian and Schlick, Tamar},
year = {2010},
pages = {283101}
}
@article{dawson_computational_2016,
series = {Theory and simulation • {Macromolcular} machines},
title = {Computational modeling of {RNA} 3D structures and interactions},
volume = {37},
issn = {0959-440X},
url = {http://www.sciencedirect.com/science/article/pii/S0959440X15001700},
doi = {10.1016/j.sbi.2015.11.007},
abstract = {RNA molecules have key functions in cellular processes beyond being carriers of protein-coding information. These functions are often dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is difficult, which has prompted the development of computational methods for structure prediction from sequence. Recent progress in 3D structure modeling of RNA and emerging approaches for predicting RNA interactions with ions, ligands and proteins have been stimulated by successes in protein 3D structure modeling.},
urldate = {2018-10-09},
journal = {Current Opinion in Structural Biology},
author = {Dawson, Wayne K and Bujnicki, Janusz M},
month = apr,
year = {2016},
pages = {22--28},
file = {ScienceDirect Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/7V5SQ8PN/Dawson et Bujnicki - 2016 - Computational modeling of RNA 3D structures and in.pdf:application/pdf;ScienceDirect Snapshot:/nhome/siniac/lbecquey/Zotero/storage/CDMTYU7W/S0959440X15001700.html:text/html}
}
@article{laing_computational_2011,
title = {Computational approaches to {RNA} structure prediction, analysis, and design},
volume = {21},
issn = {0959-440X},
url = {http://www.sciencedirect.com/science/article/pii/S0959440X11000674},
doi = {10.1016/j.sbi.2011.03.015},
abstract = {RNA molecules are important cellular components involved in many fundamental biological processes. Understanding the mechanisms behind their functions requires RNA tertiary structure knowledge. Although modeling approaches for the study of RNA structures and dynamics lag behind efforts in protein folding, much progress has been achieved in the past two years. Here, we review recent advances in RNA folding algorithms, RNA tertiary motif discovery, applications of graph theory approaches to RNA structure and function, and in silico generation of RNA sequence pools for aptamer design. Advances within each area can be combined to impact many problems in RNA structure and function.},
number = {3},
urldate = {2018-10-09},
journal = {Current Opinion in Structural Biology},
author = {Laing, Christian and Schlick, Tamar},
month = jun,
year = {2011},
pages = {306--318},
file = {ScienceDirect Snapshot:/nhome/siniac/lbecquey/Zotero/storage/LWS5RU5Z/S0959440X11000674.html:text/html}
}
@article{reinharz2018mining,
title={Mining for recurrent long-range interactions in RNA structures reveals embedded hierarchies in network families},
author={Reinharz, Vladimir and Soul{\'e}, Antoine and Westhof, Eric and Waldisp{\"u}hl, J{\'e}r{\^o}me and Denise, Alain},
journal={Nucleic Acids Research},
volume={46},
number={8},
pages={3841--3851},
year={2018},
publisher={Oxford University Press}
}
@article{sato_ipknot:_2011,
title = {{IPknot}: fast and accurate prediction of {RNA} secondary structures with pseudoknots using integer programming},
volume = {27},
issn = {1367-4803},
shorttitle = {{IPknot}},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117384/},
doi = {10.1093/bioinformatics/btr215},
abstract = {Motivation: Pseudoknots found in secondary structures of a number of functional RNAs play various roles in biological processes. Recent methods for predicting RNA secondary structures cover certain classes of pseudoknotted structures, but only a few of them achieve satisfying predictions in terms of both speed and accuracy., Results: We propose IPknot, a novel computational method for predicting RNA secondary structures with pseudoknots based on maximizing expected accuracy of a predicted structure. IPknot decomposes a pseudoknotted structure into a set of pseudoknot-free substructures and approximates a base-pairing probability distribution that considers pseudoknots, leading to the capability of modeling a wide class of pseudoknots and running quite fast. In addition, we propose a heuristic algorithm for refining base-paring probabilities to improve the prediction accuracy of IPknot. The problem of maximizing expected accuracy is solved by using integer programming with threshold cut. We also extend IPknot so that it can predict the consensus secondary structure with pseudoknots when a multiple sequence alignment is given. IPknot is validated through extensive experiments on various datasets, showing that IPknot achieves better prediction accuracy and faster running time as compared with several competitive prediction methods., Availability: The program of IPknot is available at http://www.ncrna.org/software/ipknot/. IPknot is also available as a web server at http://rna.naist.jp/ipknot/., Contact: satoken@k.u-tokyo.ac.jp; ykato@is.naist.jp, Supplementary information: Supplementary data are available at Bioinformatics online.},
number = {13},
urldate = {2018-10-12},
journal = {Bioinformatics},
author = {Sato, Kengo and Kato, Yuki and Hamada, Michiaki and Akutsu, Tatsuya and Asai, Kiyoshi},
month = jul,
year = {2011},
pmid = {21685106},
pmcid = {PMC3117384},
pages = {i85--i93},
file = {Texte intégral:/nhome/siniac/lbecquey/Zotero/storage/EEWT77EA/Sato et al. - 2011 - IPknot fast and accurate prediction of RNA second.pdf:application/pdf}
}
@article{zirbel_identifying_2015,
title = {Identifying novel sequence variants of {RNA} 3D motifs},
volume = {43},
issn = {0305-1048},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4551918/},
doi = {10.1093/nar/gkv651},
abstract = {Predicting RNA 3D structure from sequence is a major challenge in biophysics. An important sub-goal is accurately identifying recurrent 3D motifs from RNA internal and hairpin loop sequences extracted from secondary structure (2D) diagrams. We have developed and validated new probabilistic models for 3D motif sequences based on hybrid Stochastic Context-Free Grammars and Markov Random Fields (SCFG/MRF). The SCFG/MRF models are constructed using atomic-resolution RNA 3D structures. To parameterize each model, we use all instances of each motif found in the RNA 3D Motif Atlas and annotations of pairwise nucleotide interactions generated by the FR3D software. Isostericity relations between non-Watson–Crick basepairs are used in scoring sequence variants. SCFG techniques model nested pairs and insertions, while MRF ideas handle crossing interactions and base triples. We use test sets of randomly-generated sequences to set acceptance and rejection thresholds for each motif group and thus control the false positive rate. Validation was carried out by comparing results for four motif groups to RMDetect. The software developed for sequence scoring (JAR3D) is structured to automatically incorporate new motifs as they accumulate in the RNA 3D Motif Atlas when new structures are solved and is available free for download.},
number = {15},
urldate = {2018-10-19},
journal = {Nucleic Acids Research},
author = {Zirbel, Craig L. and Roll, James and Sweeney, Blake A. and Petrov, Anton I. and Pirrung, Meg and Leontis, Neocles B.},
month = sep,
year = {2015},
pmid = {26130723},
pmcid = {PMC4551918},
pages = {7504--7520},
file = {PubMed Central Full Text PDF:/nhome/siniac/lbecquey/Zotero/storage/C68JKL5J/Zirbel et al. - 2015 - Identifying novel sequence variants of RNA 3D moti.pdf:application/pdf}
}
@software{cplex,
author = {IBM ILOG},
title = {{CPLEX}: {CPLEX} {Optimizer} (Academic license)},
version = {12.8},
howpublished = {\url{https://www.ibm.com/analytics/optimization-modeling-interfaces}},
year = {2018}
}
@article{andronescu2008rna,
title={RNA STRAND: the RNA secondary structure and statistical analysis database},
author={Andronescu, Mirela and Bereg, Vera and Hoos, Holger H and Condon, Anne},
journal={BMC bioinformatics},
volume={9},
number={1},
pages={340},
year={2008},
publisher={BioMed Central}
}
\ No newline at end of file
......@@ -15,15 +15,15 @@ import ast
# Retrieve Paths from file EditMe
jar3dexec = ""
HLmotifDir = ""
ILmotifDir = ""
descfolder = ""
bypdir = ""
biorseoDir = "."
exec(compile(open(biorseoDir+"/EditMe").read(), '', 'exec'))
runDir = path.dirname(path.realpath(__file__))
dataFile = argv[1]
outputDir = biorseoDir + "/results/"
HLmotifDir = biorseoDir + "/data/modules/BGSU/HL/3.2/lib"
ILmotifDir = biorseoDir + "/data/modules/BGSU/IL/3.2/lib"
descfolder = biorseoDir + "/data/modules/DESC"
# Create some folders to store the results
subprocess.call(["mkdir", "-p", outputDir])
......@@ -360,8 +360,8 @@ def launch_RNAMoIP(seq_, header_, basename):
ninsertions = [ t[1] for t in results if t[0] != ""]
scores = [ t[2] for t in results if t[0] != ""]
rna = open(outputDir + basename + ".moip", "w")
rna.write(header_)
rna.write(seq_)
rna.write(header_+'\n')
rna.write(seq_+'\n')
for p,n,s in zip(predictions, ninsertions, scores):
rna.write(p+'\t'+str(n)+'\t'+str(s)+'\n')
rna.close()
......@@ -885,8 +885,8 @@ class RNA:
if ss not in self.biorseoBGSUBayesPairA.predictions:
self.biorseoBGSUBayesPairA.predictions.append(ss)
self.biorseoBGSUBayesPairA.ninsertions.append(lines[i].count('+'))
else:
print(targetdir+ self.basename + ".bgsubypA not found !")
# else:
# print(targetdir+ self.basename + ".bgsubypA not found !")
def get_biorseoBGSUBayesPairB_results(self, targetdir):
if path.isfile(targetdir+ self.basename + ".bgsubypB"):
......@@ -898,8 +898,8 @@ class RNA:
if ss not in self.biorseoBGSUBayesPairB.predictions:
self.biorseoBGSUBayesPairB.predictions.append(ss)
self.biorseoBGSUBayesPairB.ninsertions.append(lines[i].count('+'))
else:
print(targetdir+ self.basename + ".bgsubypB not found !")
# else:
# print(targetdir+ self.basename + ".bgsubypB not found !")
def get_biorseoBGSUBayesPairC_results(self, targetdir):
if path.isfile(targetdir+ self.basename + ".bgsubypC"):
......@@ -911,8 +911,8 @@ class RNA:
if ss not in self.biorseoBGSUBayesPairC.predictions:
self.biorseoBGSUBayesPairC.predictions.append(ss)
self.biorseoBGSUBayesPairC.ninsertions.append(lines[i].count('+'))
else:
print(targetdir+ self.basename + ".bgsubypC not found !")
# else:
# print(targetdir+ self.basename + ".bgsubypC not found !")
def get_biorseoBGSUBayesPairD_results(self, targetdir):
if path.isfile(targetdir+ self.basename + ".bgsubypD"):
......@@ -924,8 +924,8 @@ class RNA:
if ss not in self.biorseoBGSUBayesPairD.predictions:
self.biorseoBGSUBayesPairD.predictions.append(ss)
self.biorseoBGSUBayesPairD.ninsertions.append(lines[i].count('+'))
else:
print(targetdir+ self.basename + ".bgsubypD not found !")
# else:
# print(targetdir+ self.basename + ".bgsubypD not found !")
def load_results_from(self, targetDir):
self.get_biokop_results()
......@@ -1003,9 +1003,9 @@ for nt, number in ignored_nt_dict.items():
tot = len(RNAcontainer)
print("Loaded %d RNAs of length between 10 and 100. %d of them contain pseudoknots." % (tot, pk_counter))
# # ================= PREDICTION OF STRUCTURES ===============================
# #================= PREDICTION OF STRUCTURES ===============================
# # define job list
# #define job list
# joblist = []
# for instance in RNAcontainer:
# basename = instance.basename
......@@ -1017,7 +1017,7 @@ print("Loaded %d RNAs of length between 10 and 100. %d of them contain pseudokno
# # BayesPairing and BGSUBayesPairing
# joblist.append(Job(function=launch_BayesPairing, args=["rna3dmotif", instance.seq_, instance.header_, basename], how_many_in_parallel=-1, priority=3, checkFunc=check_BayesPairing, checkArgs=[basename]))
# joblist.append(Job(function=launch_BayesPairing, args=["3dmotifatlas", instance.seq_, instance.header_, basename], how_many_in_parallel=-1, priority=3, checkFunc=check_BGSUBayesPairing, checkArgs=[basename]))
# # bmotinBGSUJAR3DA-D
# # biorseoBGSUJAR3DA-D
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--jar3dcsv", outputDir+basename+".sites.csv", "-o", outputDir+"noPK/"+basename+".jar3dA", "--type", "A", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUJAR3DA, checkArgs=[basename, False]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--jar3dcsv", outputDir+basename+".sites.csv", "-o", outputDir+"noPK/"+basename+".jar3dB", "--type", "B", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUJAR3DB, checkArgs=[basename, False]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--jar3dcsv", outputDir+basename+".sites.csv", "-o", outputDir+"noPK/"+basename+".jar3dC", "--type", "C", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUJAR3DC, checkArgs=[basename, False]))
......@@ -1026,7 +1026,7 @@ print("Loaded %d RNAs of length between 10 and 100. %d of them contain pseudokno
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--jar3dcsv", outputDir+basename+".sites.csv", "-o", outputDir+"PK/"+basename+".jar3dB", "--type", "B"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUJAR3DB, checkArgs=[basename, True]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--jar3dcsv", outputDir+basename+".sites.csv", "-o", outputDir+"PK/"+basename+".jar3dC", "--type", "C"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUJAR3DC, checkArgs=[basename, True]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--jar3dcsv", outputDir+basename+".sites.csv", "-o", outputDir+"PK/"+basename+".jar3dD", "--type", "D"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUJAR3DD, checkArgs=[basename, True]))
# # bmotinBGSUBayesPairA-D
# # biorseoBGSUBayesPairA-D
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".bgsubyp.csv", "-o", outputDir+"noPK/"+basename+".bgsubypA", "--type", "A", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUBayesPairA, checkArgs=[basename, False]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".bgsubyp.csv", "-o", outputDir+"noPK/"+basename+".bgsubypB", "--type", "B", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUBayesPairB, checkArgs=[basename, False]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".bgsubyp.csv", "-o", outputDir+"noPK/"+basename+".bgsubypC", "--type", "C", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUBayesPairC, checkArgs=[basename, False]))
......@@ -1035,7 +1035,7 @@ print("Loaded %d RNAs of length between 10 and 100. %d of them contain pseudokno
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".bgsubyp.csv", "-o", outputDir+"PK/"+basename+".bgsubypB", "--type", "B"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUBayesPairB, checkArgs=[basename, True]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".bgsubyp.csv", "-o", outputDir+"PK/"+basename+".bgsubypC", "--type", "C"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUBayesPairC, checkArgs=[basename, True]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".bgsubyp.csv", "-o", outputDir+"PK/"+basename+".bgsubypD", "--type", "D"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBGSUBayesPairD, checkArgs=[basename, True]))
# # bmotinBayesPairA-D
# # biorseoBayesPairA-D
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".byp.csv", "-o", outputDir+"noPK/"+basename+".bypA", "--type", "A", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBayesPairA, checkArgs=[basename, False]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".byp.csv", "-o", outputDir+"noPK/"+basename+".bypB", "--type", "B", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBayesPairB, checkArgs=[basename, False]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir+basename+".fa", "--bayespaircsv", outputDir+basename+".byp.csv", "-o", outputDir+"noPK/"+basename+".bypC", "--type", "C", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoBayesPairC, checkArgs=[basename, False]))
......@@ -1049,7 +1049,7 @@ print("Loaded %d RNAs of length between 10 and 100. %d of them contain pseudokno
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir + basename + ".fa", "-d", descfolder, "-o", outputDir+"noPK/" + basename + ".rawB", "--type", "B", "-n"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoRawB, checkArgs=[basename, False]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir + basename + ".fa", "-d", descfolder, "-o", outputDir+"PK/" + basename + ".rawA", "--type", "A"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoRawA, checkArgs=[basename, True]))
# joblist.append(Job(command=[biorseoDir+"/bin/biorseo", "-s", outputDir + basename + ".fa", "-d", descfolder, "-o", outputDir+"PK/" + basename + ".rawB", "--type", "B"], priority=4, timeout=3600, how_many_in_parallel=3, checkFunc=check_biorseoRawB, checkArgs=[basename, True]))
# # RNA MoIP
# # RNA-MoIP
# joblist.append(Job(function=launch_RNAMoIP, args=[instance.seq_, instance.header_, basename], priority=3, timeout=3600, checkFunc=check_RNAMoIP, checkArgs=[basename]))
# # Biokop
# joblist.append(Job(command=[biorseoDir + "/../biokop/biokop", "-n1", "-i", outputDir + basename + ".fa", "-o", outputDir + basename + ".biok"], priority=5, timeout=15000, how_many_in_parallel=3, checkFunc=check_biokop, checkArgs=[basename]))
......@@ -1088,13 +1088,15 @@ print("Loaded %d RNAs of length between 10 and 100. %d of them contain pseudokno
# print()
# for j in fails:
# print(j.cmd_)
# exit()
# else:
# print()
# print("Computations ran successfully.")
# print()
# ================= Statistics (without pseudoknots) ========================
print("Loading results from files... (without pseudoknots)")
# load results in objects
for instance in RNAcontainer:
instance.load_results_from(outputDir + "noPK/")
......@@ -1145,7 +1147,7 @@ x_noPK_fully = [
print()
print("Without PK:")
print("%s RNAsubopt predictions" % is_all(len(x_noPK[0]), tot))
print("%s RNA MoIP predictions" % is_all(len(x_noPK[1]), tot))
print("%s RNA-MoIP predictions" % is_all(len(x_noPK[1]), tot))
print("%s biorseo + BGSU + JAR3D + f1A predictions" % is_all(len(x_noPK[2]), tot))
print("%s biorseo + BGSU + JAR3D + f1B predictions" % is_all(len(x_noPK[3]), tot))
print("%s biorseo + BGSU + JAR3D + f1C predictions" % is_all(len(x_noPK[4]), tot))
......@@ -1174,6 +1176,7 @@ print("Wilcoxon signed rank test with PK: H0 = 'The position parameter of RNA-Mo
# ================= Statistics (with pseudoknots) ========================
print("Loading results from files... (with pseudoknots)")
# load results in objects
for instance in RNAcontainer:
instance.load_results_from(outputDir + "PK/")
......@@ -1271,8 +1274,8 @@ print("Wilcoxon signed rank test with PK: H0 = 'The position parameter of Biokop
# print("RNA-MOIP",":",x_noPK[1])
# for data, name in zip(x_PK, labels):
# print(name,":",data)
# labels = ["RNAsubopt","Biokop\t", "RNA MoIP\t","RawA\t","RawB\t","BayesPairingA","BayesPairingB","BayesPairingC","BayesPairingD","JAR3DA\t","JAR3DB\t","JAR3DC\t","JAR3DD\t","BGSUBPairingA","BGSUBPairingB","BGSUBPairingC","BGSUBPairingD"]
# # for r in RNAcontainer:
# labels = ["RNAsubopt","Biokop\t", "RNA-MoIP\t","RawA\t","RawB\t","BayesPairingA","BayesPairingB","BayesPairingC","BayesPairingD","JAR3DA\t","JAR3DB\t","JAR3DC\t","JAR3DD\t","BGSUBPairingA","BGSUBPairingB","BGSUBPairingC","BGSUBPairingD"]
# for r in RNAcontainer:
# print("\n",r.header_,"\nTrue structure:\t", r.true2d)
# for m, name in zip([r.rnasubopt, r.biokop, r.rnamoip,
# r.biorseoRawA,
......@@ -1295,7 +1298,7 @@ print("Wilcoxon signed rank test with PK: H0 = 'The position parameter of Biokop
merge = [ x_PK_fully[0], # Biokop
x_noPK_fully[0], # RNA subopt
x_noPK_fully[1], # RNA MoIP
x_noPK_fully[1], # RNA-MoIP
x_noPK_fully[2], x_PK_fully[2], #biorseoRawA
x_noPK_fully[3], x_PK_fully[3], #biorseoRawB
x_noPK_fully[4], x_PK_fully[4], #biorseoBayesPairA
......@@ -1329,7 +1332,7 @@ colors = [ 'green', 'blue', 'goldenrod',
'lime', 'lime'
]
labels = [ "Biokop", "RNAsubopt",
"RNA MoIP",
"RNA-MoIP",
"$f_{1A}$",
"$f_{1B}$",
"$f_{1A}$",
......@@ -1360,7 +1363,7 @@ for patch, color in zip(bplot['boxes'], colors):
# plt.axhline(y=0, color="black", linewidth=1)
# plt.axhline(y=1, color="black", linewidth=1)
plt.xticks([1.0+i for i in range(16)], labels[1:])
plt.ylim((0, 1.01))
plt.ylim((0.5, 1.01))
plt.ylabel("MCC", fontsize=12)
plt.subplots_adjust(left=0.05, right=0.95)
# plt.title("Performance without pseudoknots (%d RNAs included)" % len(x_noPK_fully[0]))
......@@ -1382,7 +1385,7 @@ for patch, color in zip(bplot['boxes'], colors):
# plt.axhline(y=0, color="black", linewidth=1)
# plt.axhline(y=1, color="black", linewidth=1)
plt.xticks([1.0+i for i in range(16)], labels)
plt.ylim((0, 1.01))
plt.ylim((0.5, 1.01))
plt.ylabel("MCC", fontsize=12)
plt.subplots_adjust(left=0.05, right=0.95)
# plt.text(6.2,-0.3,"Performance with pseudoknots (%d RNAs included)" % len(x_PK_fully[0]), fontsize=12)
......@@ -1392,20 +1395,18 @@ plt.show()
# # ================== MCC performance ====================================
# # plt.subplot(141)
# RNAs_fully_predicted.sort(key=lambda x: x.rnasubopt.max_mcc)
# RNAcontainer.sort(key=lambda x: x.rnasubopt.max_mcc)
# x = [
# [ rna.rnasubopt.max_mcc for rna in RNAs_fully_predicted],
# [ rna.rnamoip.max_mcc for rna in RNAs_fully_predicted],
# #[ rna.biorseoRawA.max_mcc for rna in RNAs_fully_predicted],
# [ rna.rnasubopt.max_mcc for rna in RNAcontainer],
# [ rna.rnamoip.max_mcc for rna in RNAcontainer],
# # [ rna.biorseoRawA.max_mcc for rna in RNAs_fully_predicted],
# # [ rna.biorseoRawB.max_mcc for rna in RNAs_fully_predicted],
# #[ rna.biokop.max_mcc for rna in RNAs_fully_predicted],
# #[ rna.biorseoBGSUJAR3DA.max_mcc for rna in RNAs_fully_predicted]
# # [ rna.biokop.max_mcc for rna in RNAs_fully_predicted],
# # [ rna.biorseoBGSUJAR3DA.max_mcc for rna in RNAs_fully_predicted]
# ]
# colors = ['xkcd:blue','goldenrod']#, 'green', 'cyan']
# labels = ["Best RNAsubopt MCC", "Best RNA-MoIP MCC"]#, "Best Biokop prediction", "Best JAR3DA prediction"]
# colors = ['xkcd:blue','goldenrod']#xkcd:red', 'green', 'cyan']
# labels = ["Best RNAsubopt MCC", "Best RNA-MoIP MCC"]# "Best RawA prediction", "Best Biokop prediction", "Best JAR3DA prediction"]
# for y, col, lab in zip(x, colors, labels):
# x_data = [ i for i in range(len(y)) if y[i]]
# y_data = [ i for i in y if i]
......@@ -1544,7 +1545,7 @@ plt.show()
# [ rna.biokop.max_mcc - rna.rnasubopt.max_mcc for rna in RNAcontainer if len(rna.biokop.predictions)],
#]
# colors = ['xkcd:goldenrod', 'xkcd:red', 'firebrick', 'limegreen']
# labels = ["$\Delta$MCC(RNAsubopt,RNA MoIP)","$\Delta$MCC(RNAsubopt,RNA MoBOIP)",
# labels = ["$\Delta$MCC(RNAsubopt,RNA-MoIP)","$\Delta$MCC(RNAsubopt,RNA MoBOIP)",
# "$\Delta$MCC(RNAsubopt,RNA MoBOIP++)","$\Delta$MCC(RNAsubopt,Biokop)"]
# bplot = plt.boxplot(x, vert=False, patch_artist=True, notch=False, whis=[3,97])
# for patch, color in zip(bplot['boxes'], colors):
......