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OPUS-PSP: an orientation-dependent statistical all-atom potential derived from side-chain packing.
Lu, Mingyang; Dousis, Athanasios D; Ma, Jianpeng.
Afiliação
  • Lu M; Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX77030, USA.
J Mol Biol ; 376(1): 288-301, 2008 Feb 08.
Article em En | MEDLINE | ID: mdl-18177896
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Química / Biologia Computacional / Modelos Químicos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2008 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Química / Biologia Computacional / Modelos Químicos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2008 Tipo de documento: Article