Literature DB >> 16372349

Accounting for loop flexibility during protein-protein docking.

Karine Bastard1, Chantal Prévost, Martin Zacharias.   

Abstract

Although reliable docking can now be achieved for systems that do not undergo important induced conformational change upon association, the presence of flexible surface loops, which must adapt to the steric and electrostatic properties of a partner, generally presents a major obstacle. We report here the first docking method that allows large loop movements during a systematic exploration of the possible arrangements of the two partners in terms of position and rotation. Our strategy consists in taking into account an ensemble of possible loop conformations by a multi-copy representation within a reduced protein model. The docking process starts from regularly distributed positions and orientations of the ligand around the whole receptor. Each starting configuration is submitted to energy minimization during which the best-fitting loop conformation is selected based on the mean-field theory. Trials were carried out on proteins with significant differences in the main-chain conformation of the binding loop between isolated form and complexed form, which were docked to their partner considered in their bound form. The method is able to predict complexes very close to the crystal complex both in terms of relative position of the two partners and of the geometry of the flexible loop. We also show that introducing loop flexibility on the isolated protein form during systematic docking largely improves the predictions of relative position of the partners in comparison with rigid-body docking. 2005 Wiley-Liss, Inc.

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Year:  2006        PMID: 16372349     DOI: 10.1002/prot.20770

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


  25 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.  Predicting flexible loop regions that interact with ligands: the challenge of accurate scoring.

Authors:  Matthew L Danielson; Markus A Lill
Journal:  Proteins       Date:  2011-11-09

3.  Automatic prediction of flexible regions improves the accuracy of protein-protein docking models.

Authors:  Xiaohu Luo; Qiang Lü; Hongjie Wu; Lingyun Yang; Xu Huang; Peide Qian; Gang Fu
Journal:  J Mol Model       Date:  2011-09-27       Impact factor: 1.810

Review 4.  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

5.  Use of allostery to identify inhibitors of calmodulin-induced activation of Bacillus anthracis edema factor.

Authors:  Elodie Laine; Christophe Goncalves; Johanna C Karst; Aurélien Lesnard; Sylvain Rault; Wei-Jen Tang; Thérèse E Malliavin; Daniel Ladant; Arnaud Blondel
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-07       Impact factor: 11.205

6.  Investigating the local flexibility of functional residues in hemoproteins.

Authors:  Sophie Sacquin-Mora; Richard Lavery
Journal:  Biophys J       Date:  2006-01-20       Impact factor: 4.033

Review 7.  Protein mechanics: a route from structure to function.

Authors:  Richard Lavery; Sophie Sacquin-Mora
Journal:  J Biosci       Date:  2007-08       Impact factor: 1.826

8.  Monte Carlo refinement of rigid-body protein docking structures with backbone displacement and side-chain optimization.

Authors:  Stephan Lorenzen; Yang Zhang
Journal:  Protein Sci       Date:  2007-10-26       Impact factor: 6.725

9.  Improving database enrichment through ensemble docking.

Authors:  Shashidhar Rao; Paul C Sanschagrin; Jeremy R Greenwood; Matthew P Repasky; Woody Sherman; Ramy Farid
Journal:  J Comput Aided Mol Des       Date:  2008-02-06       Impact factor: 3.686

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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