GWOVina: A grey wolf optimization approach to rigid and flexible receptor docking.

Chemical Biology & Drug Design
Kin Meng WongShirley W I Siu

Abstract

Protein-ligand docking programs are indispensable tools for predicting the binding pose of a ligand to the receptor protein. In this paper, we introduce an efficient flexible docking method, GWOVina, which is a variant of the Vina implementation using the grey wolf optimizer (GWO) and random walk for the global search, and the Dunbrack rotamer library for side-chain sampling. The new method was validated for rigid and flexible-receptor docking using four independent datasets. In rigid docking, GWOVina showed comparable docking performance to Vina in terms of ligand pose RMSD, success rate, and affinity prediction. In flexible-receptor docking, GWOVina has improved success rate compared to Vina and AutoDockFR. It ran 2 to 7 times faster than Vina and 40 to 100 times faster than AutoDockFR. Therefore, GWOVina can play a role in solving the complex flexible-receptor docking cases and is suitable for virtual screening of compound libraries. GWOVina is freely available at https://cbbio.cis.um.edu.mo/software/gwovina for testing.

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Citations

Mar 5, 2021·Journal of Chemical Information and Modeling·Chao LiVasile Palade

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Methods Mentioned

BETA
X‐ray

Software Mentioned

GWO
plant
Vina
autodock4
SCWRL4
CentOS
MGLTools
GalaxyDock
autodock
wwPDB

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