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Simultaneous refinement of inaccurate local regions and overall structure in the CASP12 protein model refinement experiment.
Lee, Gyu Rie; Heo, Lim; Seok, Chaok.
Afiliação
  • Lee GR; Department of Chemistry, Seoul National University, Seoul, Republic of Korea.
  • Heo L; Department of Chemistry, Seoul National University, Seoul, Republic of Korea.
  • Seok C; Department of Chemistry, Seoul National University, Seoul, Republic of Korea.
Proteins ; 86 Suppl 1: 168-176, 2018 03.
Article em En | MEDLINE | ID: mdl-29044810
ABSTRACT
Advances in protein model refinement techniques are required as diverse sources of protein structure information are available from low-resolution experiments or informatics-based computations such as cryo-EM, NMR, homology models, or predicted residue contacts. Given semi-reliable or incomplete structural information, structure quality of a protein model has to be improved by ab initio methods such as energy-based simulation. In this study, we describe a new automatic refinement server method designed to improve locally inaccurate regions and overall structure simultaneously. Locally inaccurate regions may occur in protein structures due to non-convergent or missing information in template structures used in homology modeling or due to intrinsic structural flexibilities not resolved by experimental techniques. However, such variable or dynamic regions often play important functional roles by participating in interactions with other biomolecules or in transitions between different functional states. The new refinement method introduced here utilizes diverse types of geometric operators which drive both local and global changes, and the effect of structure changes and relaxations are accumulated. This resulted in consistent refinement of both local and global structural features. Performance of this method in CASP12 is discussed.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Conformação Proteica / Proteínas / Modelos Moleculares / Biologia Computacional / Domínios e Motivos de Interação entre Proteínas / Aprendizado de Máquina Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Proteins Assunto da revista: BIOQUIMICA Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Conformação Proteica / Proteínas / Modelos Moleculares / Biologia Computacional / Domínios e Motivos de Interação entre Proteínas / Aprendizado de Máquina Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Proteins Assunto da revista: BIOQUIMICA Ano de publicação: 2018 Tipo de documento: Article