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Assessing search strategies for flexible docking
Author(s) -
Vieth Michal,
Hirst Jonathan D.,
Dominy Brian N.,
Daigler Heidi,
Brooks Charles L.
Publication year - 1998
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/(sici)1096-987x(19981115)19:14<1623::aid-jcc8>3.0.co;2-l
Subject(s) - autodock , docking (animal) , monte carlo method , molecular dynamics , computer science , algorithm , chemistry , statistical physics , computational chemistry , mathematical optimization , mathematics , physics , statistics , medicine , biochemistry , nursing , in silico , gene
We assess the efficiency of molecular dynamics (MD), Monte Carlo (MC), and genetic algorithms (GA) for docking five representative ligand–receptor complexes. All three algorithms employ a modified CHARMM‐based energy function. The algorithms are also compared with an established docking algorithm, AutoDock. The receptors are kept rigid while flexibility of ligands is permitted. To test the efficiency of the algorithms, two search spaces are used: an 11‐Å‐radius sphere and a 2.5‐Å‐radius sphere, both centered on the active site. We find MD is most efficient in the case of the large search space, and GA outperforms the other methods in the small search space. We also find that MD provides structures that are, on average, lower in energy and closer to the crystallographic conformation. The GA obtains good solutions over the course of the fewest energy evaluations. However, due to the nature of the nonbonded interaction calculations, the GA requires the longest time for a single energy evaluation, which results in a decreased efficiency. The GA and MC search algorithms are implemented in the CHARMM macromolecular package. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 1623–1631, 1998