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Ligand-protein docking using a quantum stochastic tunneling optimization method
Authors:Mancera Ricardo L  Källblad Per  Todorov Nikolay P
Affiliation:De Novo Pharmaceuticals, Compass House, Vision Park, Histon, Cambridge CB4 9ZR, United Kingdom. Ricardo.Mancera@denovopharma.com
Abstract:A novel hybrid optimization method called quantum stochastic tunneling has been recently introduced. Here, we report its implementation within a new docking program called EasyDock and a validation with the CCDC/Astex data set of ligand-protein complexes using the PLP score to represent the ligand-protein potential energy surface and ScreenScore to score the ligand-protein binding energies. When taking the top energy-ranked ligand binding mode pose, we were able to predict the correct crystallographic ligand binding mode in up to 75% of the cases. By using this novel optimization method run times for typical docking simulations are significantly shortened.
Keywords:molecular docking  flexible docking  drug design  quantum stochastic tunneling  drug design  EasyDock  protein–ligand data set  binding mode  ligand–protein interactions
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