Literature DB >> 23871100

Scoring functions for protein-protein interactions.

Iain H Moal1, Rocco Moretti, David Baker, Juan Fernández-Recio.   

Abstract

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23871100     DOI: 10.1016/j.sbi.2013.06.017

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  32 in total

1.  Computational Design of PDZ-Peptide Binding.

Authors:  Nicolas Panel; Francesco Villa; Vaitea Opuu; David Mignon; Thomas Simonson
Journal:  Methods Mol Biol       Date:  2021

2.  Structural quality of unrefined models in protein docking.

Authors:  Ivan Anishchenko; Petras J Kundrotas; Ilya A Vakser
Journal:  Proteins       Date:  2016-11-13

3.  A minimal model of protein-protein binding affinities.

Authors:  Joël Janin
Journal:  Protein Sci       Date:  2014-10-25       Impact factor: 6.725

4.  Application of docking methodologies to modeled proteins.

Authors:  Amar Singh; Taras Dauzhenka; Petras J Kundrotas; Michael J E Sternberg; Ilya A Vakser
Journal:  Proteins       Date:  2020-03-20

5.  Dockground: A comprehensive data resource for modeling of protein complexes.

Authors:  Petras J Kundrotas; Ivan Anishchenko; Taras Dauzhenka; Ian Kotthoff; Daniil Mnevets; Matthew M Copeland; Ilya A Vakser
Journal:  Protein Sci       Date:  2017-10-10       Impact factor: 6.725

6.  Modeling CAPRI targets 110-120 by template-based and free docking using contact potential and combined scoring function.

Authors:  Petras J Kundrotas; Ivan Anishchenko; Varsha D Badal; Madhurima Das; Taras Dauzhenka; Ilya A Vakser
Journal:  Proteins       Date:  2017-09-28

Review 7.  Prediction and redesign of protein-protein interactions.

Authors:  Rhonald C Lua; David C Marciano; Panagiotis Katsonis; Anbu K Adikesavan; Angela D Wilkins; Olivier Lichtarge
Journal:  Prog Biophys Mol Biol       Date:  2014-05-27       Impact factor: 3.667

8.  Updates to the Integrated Protein-Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2.

Authors:  Thom Vreven; Iain H Moal; Anna Vangone; Brian G Pierce; Panagiotis L Kastritis; Mieczyslaw Torchala; Raphael Chaleil; Brian Jiménez-García; Paul A Bates; Juan Fernandez-Recio; Alexandre M J J Bonvin; Zhiping Weng
Journal:  J Mol Biol       Date:  2015-07-29       Impact factor: 5.469

Review 9.  Recent advances in automated protein design and its future challenges.

Authors:  Dani Setiawan; Jeffrey Brender; Yang Zhang
Journal:  Expert Opin Drug Discov       Date:  2018-04-25       Impact factor: 6.098

10.  An Integrated Approach for Determining a Protein-Protein Binding Interface in Solution and an Evaluation of Hydrogen-Deuterium Exchange Kinetics for Adjudicating Candidate Docking Models.

Authors:  Mengru Mira Zhang; Brett R Beno; Richard Y-C Huang; Jagat Adhikari; Ekaterina G Deyanova; Jing Li; Guodong Chen; Michael L Gross
Journal:  Anal Chem       Date:  2019-11-22       Impact factor: 6.986

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