title: A new Lamarckian genetic algorithm for flexible ligand-receptor docking.
abstract: 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.
authors.affiliation: Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
authors.forename: Jan
authors.initials: J
authors.lastname: Fuhrmann
authors.forename: Alexander
authors.initials: A
authors.lastname: Rurainski
authors.forename: Hans-Peter
authors.initials: HP
authors.lastname: Lenhof
authors.forename: Dirk
authors.initials: D
authors.lastname: Neumann
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008024:Ligands; D008957:Models, Genetic; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism
chemical_list: D008024:Ligands; D011506:Proteins