Literature DB >> 18177896

OPUS-PSP: an orientation-dependent statistical all-atom potential derived from side-chain packing.

Mingyang Lu1, Athanasios D Dousis, Jianpeng Ma.   

Abstract

Here we report an orientation-dependent statistical all-atom potential derived from side-chain packing, named OPUS-PSP. It features a basis set of 19 rigid-body blocks extracted from the chemical structures of all 20 amino acid residues. The potential is generated from the orientation-specific packing statistics of pairs of those blocks in a non-redundant structural database. The purpose of such an approach is to capture the essential elements of orientation dependence in molecular packing interactions. Tests of OPUS-PSP on commonly used decoy sets demonstrate that it significantly outperforms most of the existing knowledge-based potentials in terms of both its ability to recognize native structures and consistency in achieving high Z-scores across decoy sets. As OPUS-PSP excludes interactions among main-chain atoms, its success highlights the crucial importance of side-chain packing in forming native protein structures. Moreover, OPUS-PSP does not explicitly include solvation terms, and thus the potential should perform well when the solvation effect is difficult to determine, such as in membrane proteins. Overall, OPUS-PSP is a generally applicable potential for protein structure modeling, especially for handling side-chain conformations, one of the most difficult steps in high-accuracy protein structure prediction and refinement.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 18177896      PMCID: PMC2669442          DOI: 10.1016/j.jmb.2007.11.033

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  45 in total

Review 1.  Statistical potentials and scoring functions applied to protein-ligand binding.

Authors:  H Gohlke; G Klebe
Journal:  Curr Opin Struct Biol       Date:  2001-04       Impact factor: 6.809

2.  Discrimination of native protein structures using atom-atom contact scoring.

Authors:  Brendan J McConkey; Vladimir Sobolev; Marvin Edelman
Journal:  Proc Natl Acad Sci U S A       Date:  2003-03-11       Impact factor: 11.205

3.  Comparative protein structure modeling by iterative alignment, model building and model assessment.

Authors:  Bino John; Andrej Sali
Journal:  Nucleic Acids Res       Date:  2003-07-15       Impact factor: 16.971

4.  Ab initio construction of protein tertiary structures using a hierarchical approach.

Authors:  Y Xia; E S Huang; M Levitt; R Samudrala
Journal:  J Mol Biol       Date:  2000-06-30       Impact factor: 5.469

Review 5.  Development of novel statistical potentials for protein fold recognition.

Authors:  N-V Buchete; J E Straub; D Thirumalai
Journal:  Curr Opin Struct Biol       Date:  2004-04       Impact factor: 6.809

6.  OPUS-Ca: a knowledge-based potential function requiring only Calpha positions.

Authors:  Yinghao Wu; Mingyang Lu; Mingzhi Chen; Jialin Li; Jianpeng Ma
Journal:  Protein Sci       Date:  2007-07       Impact factor: 6.725

7.  Empirical potential function for simplified protein models: combining contact and local sequence-structure descriptors.

Authors:  Jinfeng Zhang; Rong Chen; Jie Liang
Journal:  Proteins       Date:  2006-06-01

8.  An improved protein decoy set for testing energy functions for protein structure prediction.

Authors:  Jerry Tsai; Richard Bonneau; Alexandre V Morozov; Brian Kuhlman; Carol A Rohl; David Baker
Journal:  Proteins       Date:  2003-10-01

9.  Hydrophobic potential of mean force as a solvation function for protein structure prediction.

Authors:  Matthew S Lin; Nicolas Lux Fawzi; Teresa Head-Gordon
Journal:  Structure       Date:  2007-06       Impact factor: 5.006

10.  Derivation and testing of pair potentials for protein folding. When is the quasichemical approximation correct?

Authors:  J Skolnick; L Jaroszewski; A Kolinski; A Godzik
Journal:  Protein Sci       Date:  1997-03       Impact factor: 6.725

View more
  72 in total

1.  GOAP: a generalized orientation-dependent, all-atom statistical potential for protein structure prediction.

Authors:  Hongyi Zhou; Jeffrey Skolnick
Journal:  Biophys J       Date:  2011-10-19       Impact factor: 4.033

2.  Sub-AQUA: real-value quality assessment of protein structure models.

Authors:  Yifeng David Yang; Preston Spratt; Hao Chen; Changsoon Park; Daisuke Kihara
Journal:  Protein Eng Des Sel       Date:  2010-06-04       Impact factor: 1.650

3.  Selective refinement and selection of near-native models in protein structure prediction.

Authors:  Jiong Zhang; Bogdan Barz; Jingfen Zhang; Dong Xu; Ioan Kosztin
Journal:  Proteins       Date:  2015-08-12

4.  PRIMO: A Transferable Coarse-grained Force Field for Proteins.

Authors:  Parimal Kar; Srinivasa Murthy Gopal; Yi-Ming Cheng; Alexander Predeus; Michael Feig
Journal:  J Chem Theory Comput       Date:  2013-08-13       Impact factor: 6.006

Review 5.  Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods.

Authors:  T Scott Chen; Amy E Keating
Journal:  Protein Sci       Date:  2012-06-08       Impact factor: 6.725

6.  Optimized atomic statistical potentials: assessment of protein interfaces and loops.

Authors:  Guang Qiang Dong; Hao Fan; Dina Schneidman-Duhovny; Ben Webb; Andrej Sali
Journal:  Bioinformatics       Date:  2013-09-27       Impact factor: 6.937

7.  Statistical potential for modeling and ranking of protein-ligand interactions.

Authors:  Hao Fan; Dina Schneidman-Duhovny; John J Irwin; Guangqiang Dong; Brian K Shoichet; Andrej Sali
Journal:  J Chem Inf Model       Date:  2011-11-21       Impact factor: 4.956

8.  A coarse-grained potential for fold recognition and molecular dynamics simulations of proteins.

Authors:  Peter Májek; Ron Elber
Journal:  Proteins       Date:  2009-09

9.  Pushing the Backbone in Protein-Protein Docking.

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

10.  Explicit orientation dependence in empirical potentials and its significance to side-chain modeling.

Authors:  Jianpeng Ma
Journal:  Acc Chem Res       Date:  2009-08-18       Impact factor: 22.384

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.