Ligand-protein docking using a quantum stochastic tunneling optimization method |
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Authors: | Mancera Ricardo L Källblad Per Todorov Nikolay P |
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Affiliation: | De Novo Pharmaceuticals, Compass House, Vision Park, Histon, Cambridge CB4 9ZR, United Kingdom. Ricardo.Mancera@denovopharma.com |
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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. |
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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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