Literature DB >> 21739500

Integrating atom-based and residue-based scoring functions for protein-protein docking.

Thom Vreven1, Howook Hwang, Zhiping Weng.   

Abstract

Most scoring functions for protein-protein docking algorithms are either atom-based or residue-based, with the former being able to produce higher quality structures and latter more tolerant to conformational changes upon binding. Earlier, we developed the ZRANK algorithm for reranking docking predictions, with a scoring function that contained only atom-based terms. Here we combine ZRANK's atom-based potentials with five residue-based potentials published by other labs, as well as an atom-based potential IFACE that we published after ZRANK. We simultaneously optimized the weights for selected combinations of terms in the scoring function, using decoys generated with the protein-protein docking algorithm ZDOCK. We performed rigorous cross validation of the combinations using 96 test cases from a docking benchmark. Judged by the integrative success rate of making 1000 predictions per complex, addition of IFACE and the best residue-based pair potential reduced the number of cases without a correct prediction by 38 and 27% relative to ZDOCK and ZRANK, respectively. Thus combination of residue-based and atom-based potentials into a scoring function can improve performance for protein-protein docking. The resulting scoring function is called IRAD (integration of residue- and atom-based potentials for docking) and is available at http://zlab.umassmed.edu.
Copyright © 2011 The Protein Society.

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Year:  2011        PMID: 21739500      PMCID: PMC3190152          DOI: 10.1002/pro.687

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  36 in total

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5.  HADDOCK: a protein-protein docking approach based on biochemical or biophysical information.

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Journal:  Biophys J       Date:  2003-03       Impact factor: 4.033

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Authors:  Rong Chen; Li Li; Zhiping Weng
Journal:  Proteins       Date:  2003-07-01

8.  CAPRI: a Critical Assessment of PRedicted Interactions.

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9.  ZDOCK predictions for the CAPRI challenge.

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  33 in total

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2.  Evaluating template-based and template-free protein-protein complex structure prediction.

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4.  Integrating ab initio and template-based algorithms for protein-protein complex structure prediction.

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5.  Contact Potential for Structure Prediction of Proteins and Protein Complexes from Potts Model.

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Journal:  Biophys J       Date:  2018-08-08       Impact factor: 4.033

6.  Molecular modeling of the binding modes of the iron-sulfur protein to the Jac1 co-chaperone from Saccharomyces cerevisiae by all-atom and coarse-grained approaches.

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Journal:  Proteins       Date:  2015-06-06

7.  Protein docking model evaluation by 3D deep convolutional neural networks.

Authors:  Xiao Wang; Genki Terashi; Charles W Christoffer; Mengmeng Zhu; Daisuke Kihara
Journal:  Bioinformatics       Date:  2020-04-01       Impact factor: 6.937

8.  Ranking protein-protein docking results using steered molecular dynamics and potential of mean force calculations.

Authors:  Laura J Kingsley; Juan Esquivel-Rodríguez; Ying Yang; Daisuke Kihara; Markus A Lill
Journal:  J Comput Chem       Date:  2016-05-27       Impact factor: 3.376

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

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Journal:  Nucleic Acids Res       Date:  2018-05-18       Impact factor: 16.971

10.  DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

Authors:  Li C Xue; Rafael A Jordan; Yasser El-Manzalawy; Drena Dobbs; Vasant Honavar
Journal:  Proteins       Date:  2013-10-17
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