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Blind Pose Prediction, Scoring, and Affinity Ranking of the CSAR 2014 Dataset.
Martiny, Virginie Y; Martz, François; Selwa, Edithe; Iorga, Bogdan I.
Afiliación
  • Martiny VY; Institut de Chimie des Substances Naturelles, CNRS UPR 2301, LabEx LERMIT , 91198 Gif-sur-Yvette, France.
  • Martz F; Department of Nephrology and Dialysis, AP-HP, Tenon Hospital, INSERM UMR_S 1155 , 75020 Paris, France.
  • Selwa E; Institut de Chimie des Substances Naturelles, CNRS UPR 2301, LabEx LERMIT , 91198 Gif-sur-Yvette, France.
  • Iorga BI; Institut de Chimie des Substances Naturelles, CNRS UPR 2301, LabEx LERMIT , 91198 Gif-sur-Yvette, France.
J Chem Inf Model ; 56(6): 996-1003, 2016 06 27.
Article en En | MEDLINE | ID: mdl-26391724
ABSTRACT
The 2014 CSAR Benchmark Exercise was focused on three protein targets coagulation factor Xa, spleen tyrosine kinase, and bacterial tRNA methyltransferase. Our protocol involved a preliminary analysis of the structural information available in the Protein Data Bank for the protein targets, which allowed the identification of the most appropriate docking software and scoring functions to be used for the rescoring of several docking conformations datasets, as well as for pose prediction and affinity ranking. The two key points of this study were (i) the prior evaluation of molecular modeling tools that are most adapted for each target and (ii) the increased search efficiency during the docking process to better explore the conformational space of big and flexible ligands.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Proteínas / Simulación del Acoplamiento Molecular Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2016 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Proteínas / Simulación del Acoplamiento Molecular Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2016 Tipo del documento: Article País de afiliación: Francia