Literature DB >> 28580613

Update of the ATTRACT force field for the prediction of protein-protein binding affinity.

Jean-Baptiste Chéron1, Martin Zacharias2,3, Serge Antonczak1, Sébastien Fiorucci1.   

Abstract

Determining the protein-protein interactions is still a major challenge for molecular biology. Docking protocols has come of age in predicting the structure of macromolecular complexes. However, they still lack accuracy to estimate the binding affinities, the thermodynamic quantity that drives the formation of a complex. Here, an updated version of the protein-protein ATTRACT force field aiming at predicting experimental binding affinities is reported. It has been designed on a dataset of 218 protein-protein complexes. The correlation between the experimental and predicted affinities reaches 0.6, outperforming most of the available protocols. Focusing on a subset of rigid and flexible complexes, the performance raises to 0.76 and 0.69, respectively.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Keywords:  binding affinity; coarse-grained force field; docking; protein-protein interaction; scoring function

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Year:  2017        PMID: 28580613     DOI: 10.1002/jcc.24836

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  3 in total

1.  Determination of an effective scoring function for RNA-RNA interactions with a physics-based double-iterative method.

Authors:  Yumeng Yan; Zeyu Wen; Di Zhang; Sheng-You Huang
Journal:  Nucleic Acids Res       Date:  2018-05-18       Impact factor: 16.971

2.  Structural Design and Analysis of the RHOA-ARHGEF1 Binding Mode: Challenges and Applications for Protein-Protein Interface Prediction.

Authors:  Ennys Gheyouche; Matthias Bagueneau; Gervaise Loirand; Bernard Offmann; Stéphane Téletchéa
Journal:  Front Mol Biosci       Date:  2021-05-24

3.  Computational Assessment of Protein-protein Binding Affinity by Reversely Engineering the Energetics in Protein Complexes.

Authors:  Bo Wang; Zhaoqian Su; Yinghao Wu
Journal:  Genomics Proteomics Bioinformatics       Date:  2021-04-07       Impact factor: 6.409

  3 in total

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