Protein-RNA Complexes and Efficient Automatic Docking: Expanding RosettaDock Possibilities

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2014 Oct 1

PMID 25268579

Citations 13

Authors

Adrien Guilhot-Gaudeffroy

Christine Froidevaux

Jerome Aze

Julie Bernauer

Affiliations

Soon will be listed here.

Abstract

Protein-RNA complexes provide a wide range of essential functions in the cell. Their atomic experimental structure solving, despite essential to the understanding of these functions, is often difficult and expensive. Docking approaches that have been developed for proteins are often challenging to adapt for RNA because of its inherent flexibility and the structural data available being relatively scarce. In this study we adapted the RosettaDock protocol for protein-RNA complexes both at the nucleotide and atomic levels. Using a genetic algorithm-based strategy, and a non-redundant protein-RNA dataset, we derived a RosettaDock scoring scheme able not only to discriminate but also score efficiently docking decoys. The approach proved to be both efficient and robust for generating and identifying suitable structures when applied to two protein-RNA docking benchmarks in both bound and unbound settings. It also compares well to existing strategies. This is the first approach that currently offers a multi-level optimized scoring approach integrated in a full docking suite, leading the way to adaptive fully flexible strategies.

Citing Articles

Structural comparison of homologous protein-RNA interfaces reveals widespread overall conservation contrasted with versatility in polar contacts.

Mahmoudi I, Quignot C, Martins C, Andreani J PLoS Comput Biol. 2024; 20(12):e1012650.

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An overview of structural approaches to study therapeutic RNAs.

Mollica L, Cupaioli F, Rossetti G, Chiappori F Front Mol Biosci. 2022; 9:1044126.

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Computational tools to study RNA-protein complexes.

Bheemireddy S, Sandhya S, Srinivasan N, Sowdhamini R Front Mol Biosci. 2022; 9:954926.

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Structural model of the M7G46 Methyltransferase TrmB in complex with tRNA.

Blersch K, Burchert J, August S, Welp L, Neumann P, Koster S RNA Biol. 2021; 18(12):2466-2479.

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PredPRBA: Prediction of Protein-RNA Binding Affinity Using Gradient Boosted Regression Trees.

Deng L, Yang W, Liu H Front Genet. 2019; 10:637.

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