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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This work was supported by National Institutes of Health grants R21 GM127952 and 1R01GM125813-01; National Science Foundation grants AF 1816314, AF 1645512, and DBI 1759277; and the National Science Foundation PRAC Award ACI-1713695. Part of this research has been enabled by the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (Awards OCI-0725070 and ACI-1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana–Champaign and its National Center for Supercomputing Applications. This work was funded by Division of Computing and Communication Foundations (Grant No. AF 1816314).
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Kotelnikov, S., Alekseenko, A., Liu, C. et al. Sampling and refinement protocols for template-based macrocycle docking: 2018 D3R Grand Challenge 4. J Comput Aided Mol Des 34, 179–189 (2020). https://doi.org/10.1007/s10822-019-00257-1
- Protein–ligand docking
- Template-based docking