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GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking.
Heo, Lim; Lee, Hasup; Seok, Chaok.
Afiliación
  • Heo L; Department of Chemistry, Seoul National University, Seoul 08826, Republic of Korea.
  • Lee H; Department of Chemistry, Seoul National University, Seoul 08826, Republic of Korea.
  • Seok C; Department of Chemistry, Seoul National University, Seoul 08826, Republic of Korea.
Sci Rep ; 6: 32153, 2016 08 18.
Article en En | MEDLINE | ID: mdl-27535582
ABSTRACT
Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http//galaxy.seoklab.org/refinecomplex.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Proteínas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2016 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Proteínas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2016 Tipo del documento: Article