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Research Article: pso @ autodock : A Fast Flexible Molecular Docking Program Based on Swarm Intelligence
Author(s) -
Namasivayam Vigneshwaran,
Günther Robert
Publication year - 2007
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2007.00588.x
Subject(s) - autodock , docking (animal) , protein–ligand docking , dock , virtual screening , computer science , searching the conformational space for docking , particle swarm optimization , molecular dynamics , chemistry , machine learning , protein structure , computational chemistry , in silico , biochemistry , medicine , nursing , gene
On the quest of novel therapeutics, molecular docking methods have proven to be valuable tools for screening large libraries of compounds determining the interactions of potential drugs with the target proteins. A widely used docking approach is the simulation of the docking process guided by a binding energy function. On the basis of the molecular docking program autodock , we present pso @ autodock as a tool for fast flexible molecular docking. Our novel Particle Swarm Optimization (PSO) algorithms var CPSO and var CPSO‐ls are suited for rapid docking of highly flexible ligands. Thus, a ligand with 23 rotatable bonds was successfully docked within as few as 100 000 computing steps (rmsd = 0.87 Å), which corresponds to only 10% of the computing time demanded by autodock . In comparison to other docking techniques as gold 3.0, dock 6.0, flexx 2.2.0, autodock 3.05, and sodock , pso @ autodock provides the smallest rmsd values for 12 in 37 protein–ligand complexes. The average rmsd value of 1.4 Å is significantly lower then those obtained with the other docking programs, which are all above 2.0 Å. Thus, pso @ autodock is suggested as a highly efficient docking program in terms of speed and quality for flexible peptide–protein docking and virtual screening studies.