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A new Lamarckian genetic algorithm for flexible ligand‐receptor docking
Author(s) -
Fuhrmann Jan,
Rurainski Alexander,
Lenhof HansPeter,
Neumann Dirk
Publication year - 2010
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/jcc.21478
Subject(s) - dock , heuristics , docking (animal) , protein–ligand docking , computer science , algorithm , genetic algorithm , local search (optimization) , mathematical optimization , molecular dynamics , mathematics , chemistry , virtual screening , machine learning , computational chemistry , medicine , biochemistry , nursing
We present a Lamarckian genetic algorithm (LGA) variant for flexible ligand‐receptor docking which allows to handle a large number of degrees of freedom. Our hybrid method combines a multi‐deme LGA with a recently published gradient‐based method for local optimization of molecular complexes. We compared the performance of our new hybrid method to two non gradient‐based search heuristics on the Astex diverse set for flexible ligand‐receptor docking. Our results show that the novel approach is clearly superior to other LGAs employing a stochastic optimization method. The new algorithm features a shorter run time and gives substantially better results, especially with increasing complexity of the ligands. Thus, it may be used to dock ligands with many rotatable bonds with high efficiency. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010