PLANTS: Application of Ant Colony Optimization to Structure-Based Drug Design
A central part of the rational drug development process is the prediction of the complex structure of a small ligand with a protein, the so-called protein-ligand docking problem, used in virtual screening of large databases and lead optimization. In the work presented here, we introduce a new docking algorithm called PLANTS (Protein-Ligand ANTSystem), which is based on ant colony optimization. An artificial ant colony is employed to find a minimum energy conformation of the ligand in the protein’s binding site. We present the effectiveness of PLANTS for several parameter settings as well as a direct comparison to a state-of-the-art program called GOLD, which is based on a genetic algorithm. Last but not least, results for a virtual screening on the protein target factor Xa are presented.
KeywordsRoot Mean Square Deviation Virtual Screening Rotatable Bond Heuristic Information Average Success Rate
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