Literature DB >> 27172383

A benchmark testing ground for integrating homology modeling and protein docking.

Tanggis Bohnuud1, Lingqi Luo1, Shoshana J Wodak2,3,4, Alexandre M J J Bonvin5, Zhiping Weng6, Sandor Vajda1,7, Ora Schueler-Furman8, Dima Kozakov1,9.   

Abstract

Protein docking procedures carry out the task of predicting the structure of a protein-protein complex starting from the known structures of the individual protein components. More often than not, however, the structure of one or both components is not known, but can be derived by homology modeling on the basis of known structures of related proteins deposited in the Protein Data Bank (PDB). Thus, the problem is to develop methods that optimally integrate homology modeling and docking with the goal of predicting the structure of a complex directly from the amino acid sequences of its component proteins. One possibility is to use the best available homology modeling and docking methods. However, the models built for the individual subunits often differ to a significant degree from the bound conformation in the complex, often much more so than the differences observed between free and bound structures of the same protein, and therefore additional conformational adjustments, both at the backbone and side chain levels need to be modeled to achieve an accurate docking prediction. In particular, even homology models of overall good accuracy frequently include localized errors that unfavorably impact docking results. The predicted reliability of the different regions in the model can also serve as a useful input for the docking calculations. Here we present a benchmark dataset that should help to explore and solve combined modeling and docking problems. This dataset comprises a subset of the experimentally solved 'target' complexes from the widely used Docking Benchmark from the Weng Lab (excluding antibody-antigen complexes). This subset is extended to include the structures from the PDB related to those of the individual components of each complex, and hence represent potential templates for investigating and benchmarking integrated homology modeling and docking approaches. Template sets can be dynamically customized by specifying ranges in sequence similarity and in PDB release dates, or using other filtering options, such as excluding sets of specific structures from the template list. Multiple sequence alignments, as well as structural alignments of the templates to their corresponding subunits in the target are also provided. The resource is accessible online or can be downloaded at http://cluspro.org/benchmark, and is updated on a weekly basis in synchrony with new PDB releases. Proteins 2016; 85:10-16.
© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  CAPRI docking experiment; method development; protein structure prediction; protein-protein docking; user community

Mesh:

Substances:

Year:  2016        PMID: 27172383      PMCID: PMC5817996          DOI: 10.1002/prot.25063

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  29 in total

1.  Templates are available to model nearly all complexes of structurally characterized proteins.

Authors:  Petras J Kundrotas; Zhengwei Zhu; Joël Janin; Ilya A Vakser
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-29       Impact factor: 11.205

2.  A structure-based benchmark for protein-protein binding affinity.

Authors:  Panagiotis L Kastritis; Iain H Moal; Howook Hwang; Zhiping Weng; Paul A Bates; Alexandre M J J Bonvin; Joël Janin
Journal:  Protein Sci       Date:  2011-02-16       Impact factor: 6.725

Review 3.  High-resolution protein-protein docking by global optimization: recent advances and future challenges.

Authors:  Hahnbeom Park; Hasup Lee; Chaok Seok
Journal:  Curr Opin Struct Biol       Date:  2015-09-01       Impact factor: 6.809

4.  The protein structure prediction problem could be solved using the current PDB library.

Authors:  Yang Zhang; Jeffrey Skolnick
Journal:  Proc Natl Acad Sci U S A       Date:  2005-01-14       Impact factor: 11.205

5.  Protein-Protein Docking Benchmark 2.0: an update.

Authors:  Julian Mintseris; Kevin Wiehe; Brian Pierce; Robert Anderson; Rong Chen; Joël Janin; Zhiping Weng
Journal:  Proteins       Date:  2005-08-01

6.  Are scoring functions in protein-protein docking ready to predict interactomes? Clues from a novel binding affinity benchmark.

Authors:  Panagiotis L Kastritis; Alexandre M J J Bonvin
Journal:  J Proteome Res       Date:  2010-05-07       Impact factor: 4.466

7.  Docking, scoring, and affinity prediction in CAPRI.

Authors:  Marc F Lensink; Shoshana J Wodak
Journal:  Proteins       Date:  2013-10-17

8.  Protein-protein docking benchmark version 3.0.

Authors:  Howook Hwang; Brian Pierce; Julian Mintseris; Joël Janin; Zhiping Weng
Journal:  Proteins       Date:  2008-11-15

9.  The relation between the divergence of sequence and structure in proteins.

Authors:  C Chothia; A M Lesk
Journal:  EMBO J       Date:  1986-04       Impact factor: 11.598

10.  Protein Structure Initiative Material Repository: an open shared public resource of structural genomics plasmids for the biological community.

Authors:  Catherine Y Cormier; Stephanie E Mohr; Dongmei Zuo; Yanhui Hu; Andreas Rolfs; Jason Kramer; Elena Taycher; Fontina Kelley; Michael Fiacco; Greggory Turnbull; Joshua LaBaer
Journal:  Nucleic Acids Res       Date:  2009-11-11       Impact factor: 16.971

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  12 in total

1.  Homology models of mouse and rat estrogen receptor-α ligand-binding domain created by in silico mutagenesis of a human template: molecular docking with 17ß-estradiol, diethylstilbestrol, and paraben analogs.

Authors:  Thomas L Gonzalez; James M Rae; Justin A Colacino; Rudy J Richardson
Journal:  Comput Toxicol       Date:  2018-11-28

2.  The ClusPro web server for protein-protein docking.

Authors:  Dima Kozakov; David R Hall; Bing Xia; Kathryn A Porter; Dzmitry Padhorny; Christine Yueh; Dmitri Beglov; Sandor Vajda
Journal:  Nat Protoc       Date:  2017-01-12       Impact factor: 13.491

3.  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

4.  New additions to the ClusPro server motivated by CAPRI.

Authors:  Sandor Vajda; Christine Yueh; Dmitri Beglov; Tanggis Bohnuud; Scott E Mottarella; Bing Xia; David R Hall; Dima Kozakov
Journal:  Proteins       Date:  2017-01-05

Review 5.  Computational approaches to macromolecular interactions in the cell.

Authors:  Ilya A Vakser; Eric J Deeds
Journal:  Curr Opin Struct Biol       Date:  2019-04-15       Impact factor: 6.809

6.  ClusPro in rounds 38 to 45 of CAPRI: Toward combining template-based methods with free docking.

Authors:  Dzmitry Padhorny; Kathryn A Porter; Mikhail Ignatov; Andrey Alekseenko; Dmitri Beglov; Sergei Kotelnikov; Ryota Ashizawa; Israel Desta; Nawsad Alam; Zhuyezi Sun; Emiliano Brini; Ken Dill; Ora Schueler-Furman; Sandor Vajda; Dima Kozakov
Journal:  Proteins       Date:  2020-03-23

Review 7.  Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

Authors:  Yuemin Bian; Xiang-Qun Sean Xie
Journal:  AAPS J       Date:  2018-04-09       Impact factor: 4.009

8.  InterEvDock3: a combined template-based and free docking server with increased performance through explicit modeling of complex homologs and integration of covariation-based contact maps.

Authors:  Chloé Quignot; Guillaume Postic; Hélène Bret; Julien Rey; Pierre Granger; Samuel Murail; Pablo Chacón; Jessica Andreani; Pierre Tufféry; Raphaël Guerois
Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

9.  An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants.

Authors:  Johnathan D Guest; Thom Vreven; Jing Zhou; Iain Moal; Jeliazko R Jeliazkov; Jeffrey J Gray; Zhiping Weng; Brian G Pierce
Journal:  Structure       Date:  2021-02-03       Impact factor: 5.871

10.  Sense and simplicity in HADDOCK scoring: Lessons from CASP-CAPRI round 1.

Authors:  A Vangone; J P G L M Rodrigues; L C Xue; G C P van Zundert; C Geng; Z Kurkcuoglu; M Nellen; S Narasimhan; E Karaca; M van Dijk; A S J Melquiond; K M Visscher; M Trellet; P L Kastritis; A M J J Bonvin
Journal:  Proteins       Date:  2016-11-24
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