Use of the FACTS solvation model for protein-ligand docking calculations. Application to EADock.

Détails

ID Serval
serval:BIB_8FD709286C95
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Use of the FACTS solvation model for protein-ligand docking calculations. Application to EADock.
Périodique
Journal of Molecular Recognition
Auteur(s)
Zoete V., Grosdidier A., Cuendet M., Michielin O.
ISSN
1099-1352[electronic], 0952-3499[linking]
Statut éditorial
Publié
Date de publication
2010
Volume
23
Numéro
5
Pages
457-461
Langue
anglais
Résumé
Protein-ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure-based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling.
Mots-clé
Algorithms, Computer Simulation, Drug Discovery, Ligands, Models, Molecular, Protein Binding, Proteins/chemistry, Proteins/metabolism, Solvents/chemistry, Static Electricity, Thermodynamics
Pubmed
Web of science
Création de la notice
25/08/2010 14:14
Dernière modification de la notice
03/03/2018 19:23
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