Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4.
J Comput Aided Mol Des
; 28(4): 363-73, 2014 Apr.
Article
em En
| MEDLINE
| ID: mdl-24446075
ABSTRACT
The SAMPL challenges provide an ideal opportunity for unbiased evaluation and comparison of different approaches used in computational drug design. During the fourth round of this SAMPL challenge, we participated in the virtual screening and binding pose prediction on inhibitors targeting the HIV-1 integrase enzyme. For virtual screening, we used well known and widely used in silico methods combined with personal in cerebro insights and experience. Regular docking only performed slightly better than random selection, but the performance was significantly improved upon incorporation of additional filters based on pharmacophore queries and electrostatic similarities. The best performance was achieved when logical selection was added. For the pose prediction, we utilized a similar consensus approach that amalgamated the results of the Glide-XP docking with structural knowledge and rescoring. The pose prediction results revealed that docking displayed reasonable performance in predicting the binding poses. However, prediction performance can be improved utilizing scientific experience and rescoring approaches. In both the virtual screening and pose prediction challenges, the top performance was achieved by our approaches. Here we describe the methods and strategies used in our approaches and discuss the rationale of their performances.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
HIV-1
/
Desenho Assistido por Computador
/
Inibidores de Integrase de HIV
/
Integrase de HIV
/
Simulação de Acoplamento Molecular
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
/
Screening_studies
Limite:
Humans
Idioma:
En
Revista:
J Comput Aided Mol Des
Assunto da revista:
BIOLOGIA MOLECULAR
/
ENGENHARIA BIOMEDICA
Ano de publicação:
2014
Tipo de documento:
Article
País de afiliação:
Japão