Literature DB >> 23515575

A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement.

Mohammad Moghadasi1, Dima Kozakov, Artem B Mamonov, Pirooz Vakili, Sandor Vajda, Ioannis Ch Paschalidis.   

Abstract

We introduce a message-passing algorithm to solve the Side Chain Positioning (SCP) problem. SCP is a crucial component of protein docking refinement, which is a key step of an important class of problems in computational structural biology called protein docking. We model SCP as a combinatorial optimization problem and formulate it as a Maximum Weighted Independent Set (MWIS) problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP.

Entities:  

Year:  2012        PMID: 23515575      PMCID: PMC3600151          DOI: 10.1109/cdc.2012.6426600

Source DB:  PubMed          Journal:  Proc IEEE Conf Decis Control        ISSN: 0743-1546


  9 in total

1.  ClusPro: an automated docking and discrimination method for the prediction of protein complexes.

Authors:  Stephen R Comeau; David W Gatchell; Sandor Vajda; Carlos J Camacho
Journal:  Bioinformatics       Date:  2004-01-01       Impact factor: 6.937

2.  Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations.

Authors:  Jeffrey J Gray; Stewart Moughon; Chu Wang; Ora Schueler-Furman; Brian Kuhlman; Carol A Rohl; David Baker
Journal:  J Mol Biol       Date:  2003-08-01       Impact factor: 5.469

3.  Solving and analyzing side-chain positioning problems using linear and integer programming.

Authors:  Carleton L Kingsford; Bernard Chazelle; Mona Singh
Journal:  Bioinformatics       Date:  2004-11-16       Impact factor: 6.937

4.  Optimal clustering for detecting near-native conformations in protein docking.

Authors:  Dima Kozakov; Karl H Clodfelter; Sandor Vajda; Carlos J Camacho
Journal:  Biophys J       Date:  2005-05-20       Impact factor: 4.033

5.  PIPER: an FFT-based protein docking program with pairwise potentials.

Authors:  Dima Kozakov; Ryan Brenke; Stephen R Comeau; Sandor Vajda
Journal:  Proteins       Date:  2006-11-01

6.  SDU: A Semidefinite Programming-Based Underestimation Method for Stochastic Global Optimization in Protein Docking.

Authors:  Ioannis Ch Paschalidis; Yang Shen; Pirooz Vakili; Sandor Vajda
Journal:  IEEE Trans Automat Contr       Date:  2007-04-01       Impact factor: 5.792

7.  A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions.

Authors:  Maxim V Shapovalov; Roland L Dunbrack
Journal:  Structure       Date:  2011-06-08       Impact factor: 5.006

8.  Discrimination of near-native structures in protein-protein docking by testing the stability of local minima.

Authors:  Dima Kozakov; Ora Schueler-Furman; Sandor Vajda
Journal:  Proteins       Date:  2008-08-15

9.  Protein docking by the underestimation of free energy funnels in the space of encounter complexes.

Authors:  Yang Shen; Ioannis Ch Paschalidis; Pirooz Vakili; Sandor Vajda
Journal:  PLoS Comput Biol       Date:  2008-10-10       Impact factor: 4.475

  9 in total
  3 in total

1.  A New Distributed Algorithm for Side-Chain Positioning in the Process of Protein Docking*

Authors:  Mohammad Moghadasi; Dima Kozakov; Pirooz Vakili; Sandor Vajda; Ioannis Ch Paschalidis
Journal:  Proc IEEE Conf Decis Control       Date:  2013

2.  The impact of side-chain packing on protein docking refinement.

Authors:  Mohammad Moghadasi; Hanieh Mirzaei; Artem Mamonov; Pirooz Vakili; Sandor Vajda; Ioannis Ch Paschalidis; Dima Kozakov
Journal:  J Chem Inf Model       Date:  2015-03-24       Impact factor: 4.956

3.  A Subspace Semi-Definite programming-based Underestimation (SSDU) method for stochastic global optimization in protein docking.

Authors:  Feng Nan; Mohammad Moghadasi; Pirooz Vakili; Sandor Vajda; Dima Kozakov; Ioannis Ch Paschalidis
Journal:  Proc IEEE Conf Decis Control       Date:  2014-12
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.