Literature DB >> 10861944

Scoring docked conformations generated by rigid-body protein-protein docking.

C J Camacho1, D W Gatchell, S R Kimura, S Vajda.   

Abstract

Rigid-body methods, particularly Fourier correlation techniques, are very efficient for docking bound (co-crystallized) protein conformations using measures of surface complementarity as the target function. However, when docking unbound (separately crystallized) conformations, the method generally yields hundreds of false positive structures with good scores but high root mean square deviations (RMSDs). This paper describes a two-step scoring algorithm that can discriminate near-native conformations (with less than 5 A RMSD) from other structures. The first step includes two rigid-body filters that use the desolvation free energy and the electrostatic energy to select a manageable number of conformations for further processing, but are unable to eliminate all false positives. Complete discrimination is achieved in the second step that minimizes the molecular mechanics energy of the retained structures, and re-ranks them with a combined free-energy function which includes electrostatic, solvation, and van der Waals energy terms. After minimization, the improved fit in near-native complex conformations provides the free-energy gap required for discrimination. The algorithm has been developed and tested using docking decoys, i.e., docked conformations generated by Fourier correlation techniques. The decoy sets are available on the web for testing other discrimination procedures. Proteins 2000;40:525-537. Copyright 2000 Wiley-Liss, Inc.

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Year:  2000        PMID: 10861944     DOI: 10.1002/1097-0134(20000815)40:3<525::aid-prot190>3.0.co;2-f

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


  32 in total

1.  Dynamical view of the positions of key side chains in protein-protein recognition.

Authors:  S R Kimura; R C Brower; S Vajda; C J Camacho
Journal:  Biophys J       Date:  2001-02       Impact factor: 4.033

2.  Soft protein-protein docking in internal coordinates.

Authors:  Juan Fernández-Recio; Maxim Totrov; Ruben Abagyan
Journal:  Protein Sci       Date:  2002-02       Impact factor: 6.725

3.  How common is the funnel-like energy landscape in protein-protein interactions?

Authors:  A Tovchigrechko; I A Vakser
Journal:  Protein Sci       Date:  2001-08       Impact factor: 6.725

4.  Protein docking along smooth association pathways.

Authors:  C J Camacho; S Vajda
Journal:  Proc Natl Acad Sci U S A       Date:  2001-08-21       Impact factor: 11.205

5.  Electrostatic contributions to protein-protein interactions: fast energetic filters for docking and their physical basis.

Authors:  R Norel; F Sheinerman; D Petrey; B Honig
Journal:  Protein Sci       Date:  2001-11       Impact factor: 6.725

6.  Protein-protein docking with multiple residue conformations and residue substitutions.

Authors:  David M Lorber; Maria K Udo; Brian K Shoichet
Journal:  Protein Sci       Date:  2002-06       Impact factor: 6.725

7.  Protein-protein docking with a reduced protein model accounting for side-chain flexibility.

Authors:  Martin Zacharias
Journal:  Protein Sci       Date:  2003-06       Impact factor: 6.725

8.  ClusPro: a fully automated algorithm for protein-protein docking.

Authors:  Stephen R Comeau; David W Gatchell; Sandor Vajda; Carlos J Camacho
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

9.  Experimentally biased model structure of the Hsc70/auxilin complex: substrate transfer and interdomain structural change.

Authors:  James M Gruschus; Lois E Greene; Evan Eisenberg; James A Ferretti
Journal:  Protein Sci       Date:  2004-08       Impact factor: 6.725

10.  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
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