Literature DB >> 16488145

Flexible protein-protein docking.

Alexandre M J J Bonvin1.   

Abstract

Predicting the structure of protein-protein complexes using docking approaches is a difficult problem whose major challenges include identifying correct solutions, and properly dealing with molecular flexibility and conformational changes. Flexibility can be addressed at several levels: implicitly, by smoothing the protein surfaces or allowing some degree of interpenetration (soft docking) or by performing multiple docking runs from various conformations (cross or ensemble docking); or explicitly, by allowing sidechain and/or backbone flexibility. Although significant improvements have been achieved in the modeling of sidechains, methods for the explicit inclusion of backbone flexibility in docking are still being developed. A few novel approaches have emerged involving collective degrees of motion, multicopy representations and multibody docking, which should allow larger conformational changes to be modeled.

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Year:  2006        PMID: 16488145     DOI: 10.1016/j.sbi.2006.02.002

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


  98 in total

1.  A machine learning approach for the prediction of protein surface loop flexibility.

Authors:  Howook Hwang; Thom Vreven; Troy W Whitfield; Kevin Wiehe; Zhiping Weng
Journal:  Proteins       Date:  2011-06-01

2.  A generalized approach to sampling backbone conformations with RosettaDock for CAPRI rounds 13-19.

Authors:  Aroop Sircar; Sidhartha Chaudhury; Krishna Praneeth Kilambi; Monica Berrondo; Jeffrey J Gray
Journal:  Proteins       Date:  2010-11-15

Review 3.  Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches.

Authors:  Pierre Tuffery; Philippe Derreumaux
Journal:  J R Soc Interface       Date:  2011-10-12       Impact factor: 4.118

4.  The HADDOCK web server for data-driven biomolecular docking.

Authors:  Sjoerd J de Vries; Marc van Dijk; Alexandre M J J Bonvin
Journal:  Nat Protoc       Date:  2010-04-15       Impact factor: 13.491

5.  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

6.  Protein-Protein Docking Using EMAP in CHARMM and Support Vector Machine: Application to Ab/Ag Complexes.

Authors:  Jon D Wright; Karen Sargsyan; Xiongwu Wu; Bernard R Brooks; Carmay Lim
Journal:  J Chem Theory Comput       Date:  2013-08-16       Impact factor: 6.006

7.  Cryo-EM Data Are Superior to Contact and Interface Information in Integrative Modeling.

Authors:  Sjoerd J de Vries; Isaure Chauvot de Beauchêne; Christina E M Schindler; Martin Zacharias
Journal:  Biophys J       Date:  2016-02-01       Impact factor: 4.033

8.  Inferential optimization for simultaneous fitting of multiple components into a CryoEM map of their assembly.

Authors:  Keren Lasker; Maya Topf; Andrej Sali; Haim J Wolfson
Journal:  J Mol Biol       Date:  2009-02-20       Impact factor: 5.469

9.  Modeling oblong proteins and water-mediated interfaces with RosettaDock in CAPRI rounds 28-35.

Authors:  Nicholas A Marze; Jeliazko R Jeliazkov; Shourya S Roy Burman; Scott E Boyken; Frank DiMaio; Jeffrey J Gray
Journal:  Proteins       Date:  2016-10-24

10.  Pushing the Backbone in Protein-Protein Docking.

Authors:  Daisuke Kuroda; Jeffrey J Gray
Journal:  Structure       Date:  2016-08-25       Impact factor: 5.006

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