Literature DB >> 26776208

A MOTIF-BASED METHOD FOR PREDICTING INTERFACIAL RESIDUES IN BOTH THE RNA AND PROTEIN COMPONENTS OF PROTEIN-RNA COMPLEXES.

Usha Muppirala1, Benjamin A Lewis2, Carla M Mann3, Drena Dobbs4.   

Abstract

Efforts to predict interfacial residues in protein-RNA complexes have largely focused on predicting RNA-binding residues in proteins. Computational methods for predicting protein-binding residues in RNA sequences, however, are a problem that has received relatively little attention to date. Although the value of sequence motifs for classifying and annotating protein sequences is well established, sequence motifs have not been widely applied to predicting interfacial residues in macromolecular complexes. Here, we propose a novel sequence motif-based method for "partner-specific" interfacial residue prediction. Given a specific protein-RNA pair, the goal is to simultaneously predict RNA binding residues in the protein sequence and protein-binding residues in the RNA sequence. In 5-fold cross validation experiments, our method, PS-PRIP, achieved 92% Specificity and 61% Sensitivity, with a Matthews correlation coefficient (MCC) of 0.58 in predicting RNA-binding sites in proteins. The method achieved 69% Specificity and 75% Sensitivity, but with a low MCC of 0.13 in predicting protein binding sites in RNAs. Similar performance results were obtained when PS-PRIP was tested on two independent "blind" datasets of experimentally validated protein- RNA interactions, suggesting the method should be widely applicable and valuable for identifying potential interfacial residues in protein-RNA complexes for which structural information is not available. The PS-PRIP webserver and datasets are available at: http://pridb.gdcb.iastate.edu/PSPRIP/.

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Year:  2016        PMID: 26776208      PMCID: PMC4721245     

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  20 in total

Review 1.  Computational methods for prediction of protein-RNA interactions.

Authors:  Tomasz Puton; Lukasz Kozlowski; Irina Tuszynska; Kristian Rother; Janusz M Bujnicki
Journal:  J Struct Biol       Date:  2011-10-12       Impact factor: 2.867

2.  Predicting protein-binding RNA nucleotides using the feature-based removal of data redundancy and the interaction propensity of nucleotide triplets.

Authors:  Sungwook Choi; Kyungsook Han
Journal:  Comput Biol Med       Date:  2013-08-21       Impact factor: 4.589

3.  Predicting protein associations with long noncoding RNAs.

Authors:  Matteo Bellucci; Federico Agostini; Marianela Masin; Gian Gaetano Tartaglia
Journal:  Nat Methods       Date:  2011-06       Impact factor: 28.547

Review 4.  RNA processing and its regulation: global insights into biological networks.

Authors:  Donny D Licatalosi; Robert B Darnell
Journal:  Nat Rev Genet       Date:  2010-01       Impact factor: 53.242

Review 5.  Prediction of RNA binding proteins comes of age from low resolution to high resolution.

Authors:  Huiying Zhao; Yuedong Yang; Yaoqi Zhou
Journal:  Mol Biosyst       Date:  2013-10

6.  A compendium of RNA-binding motifs for decoding gene regulation.

Authors:  Debashish Ray; Hilal Kazan; Kate B Cook; Matthew T Weirauch; Hamed S Najafabadi; Xiao Li; Serge Gueroussov; Mihai Albu; Hong Zheng; Ally Yang; Hong Na; Manuel Irimia; Leah H Matzat; Ryan K Dale; Sarah A Smith; Christopher A Yarosh; Seth M Kelly; Behnam Nabet; Desirea Mecenas; Weimin Li; Rakesh S Laishram; Mei Qiao; Howard D Lipshitz; Fabio Piano; Anita H Corbett; Russ P Carstens; Brendan J Frey; Richard A Anderson; Kristen W Lynch; Luiz O F Penalva; Elissa P Lei; Andrew G Fraser; Benjamin J Blencowe; Quaid D Morris; Timothy R Hughes
Journal:  Nature       Date:  2013-07-11       Impact factor: 49.962

7.  RBPDB: a database of RNA-binding specificities.

Authors:  Kate B Cook; Hilal Kazan; Khalid Zuberi; Quaid Morris; Timothy R Hughes
Journal:  Nucleic Acids Res       Date:  2010-10-29       Impact factor: 16.971

8.  Prediction of RNA-binding amino acids from protein and RNA sequences.

Authors:  Sungwook Choi; Kyungsook Han
Journal:  BMC Bioinformatics       Date:  2011-11-30       Impact factor: 3.169

9.  Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas.

Authors:  Anton I Petrov; Craig L Zirbel; Neocles B Leontis
Journal:  RNA       Date:  2013-08-22       Impact factor: 4.942

10.  Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.

Authors:  Rasna R Walia; Cornelia Caragea; Benjamin A Lewis; Fadi Towfic; Michael Terribilini; Yasser El-Manzalawy; Drena Dobbs; Vasant Honavar
Journal:  BMC Bioinformatics       Date:  2012-05-10       Impact factor: 3.169

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  3 in total

1.  Sequence-Based Prediction of RNA-Binding Residues in Proteins.

Authors:  Rasna R Walia; Yasser El-Manzalawy; Vasant G Honavar; Drena Dobbs
Journal:  Methods Mol Biol       Date:  2017

2.  Partner-specific prediction of RNA-binding residues in proteins: A critical assessment.

Authors:  Yong Jung; Yasser El-Manzalawy; Drena Dobbs; Vasant G Honavar
Journal:  Proteins       Date:  2018-12-30

Review 3.  Comprehensive Survey and Comparative Assessment of RNA-Binding Residue Predictions with Analysis by RNA Type.

Authors:  Kui Wang; Gang Hu; Zhonghua Wu; Hong Su; Jianyi Yang; Lukasz Kurgan
Journal:  Int J Mol Sci       Date:  2020-09-19       Impact factor: 5.923

  3 in total

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