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J Comput Aided Mol Des ; 32(1): 199-210, 2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-29134431

RESUMO

The Drug Design Data Resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of Farsenoid X Receptor (FXR) inhibitors with a semi-automated alchemical free energy calculation workflow featuring FESetup and SOMD software tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless, blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature structure activity relationships (SAR)s only, and comparable or slightly inferior, to the best submissions from other groups.


Assuntos
Desenho Assistido por Computador , Desenho de Fármacos , Simulação de Acoplamento Molecular , Receptores Citoplasmáticos e Nucleares/metabolismo , Termodinâmica , Sítios de Ligação , Cristalografia por Raios X , Bases de Dados de Proteínas , Humanos , Ligantes , Ligação Proteica , Conformação Proteica , Receptores Citoplasmáticos e Nucleares/química
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