Sampling and refinement protocols for template-based macrocycle docking: 2018 D3R Grand Challenge 4 |
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| Authors: | Sergei Kotelnikov Andrey Alekseenko Cong Liu Mikhail Ignatov Dzmitry Padhorny Emiliano Brini Mark Lukin Evangelos Coutsias Ken A. Dill Dima Kozakov |
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| Affiliation: | 1.Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA;2.Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA;3.Innopolis University, Innopolis, Russia;4.Department of Chemistry, Stony Brook University, Stony Brook, NY, USA;5.Institute for Advanced Computational Sciences, Stony Brook University, Stony Brook, NY, USA;6.Department of Pharmacological Sciences, Stony Brook University, Stony Brook, NY, USA;7.Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY, USA |
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| Abstract: | We describe a new template-based method for docking flexible ligands such as macrocycles to proteins. It combines Monte-Carlo energy minimization on the manifold, a fast manifold search method, with BRIKARD for complex flexible ligand searching, and with the MELD accelerator of Replica-Exchange Molecular Dynamics simulations for atomistic degrees of freedom. Here we test the method in the Drug Design Data Resource blind Grand Challenge competition. This method was among the best performers in the competition, giving sub-angstrom prediction quality for the majority of the targets. |
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