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SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction.

, , , , , , and . J. Comput. Aided Mol. Des., 36 (4): 291-311 (2022)

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Identifying ligand binding sites and poses using GPU-accelerated Hamiltonian replica exchange molecular dynamics., , , and . J. Comput. Aided Mol. Des., 27 (12): 989-1007 (2013)OpenMM 7: Rapid development of high performance algorithms for molecular dynamics, , , , , , , , , and 3 other author(s). PLOS Computational Biology, 13 (7): 1-17 (July 2017)OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials., , , , , , , , , and 12 other author(s). CoRR, (2023)The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations., , , , , , , , , and 7 other author(s). J. Comput. Aided Mol. Des., 34 (5): 601-633 (2020)Markov models of molecular kinetics: Generation and validation, , , , , , , , and . The Journal of Chemical Physics, (2011)Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics, , , , and . The Journal of Chemical Physics, (2007)Markov state models of biomolecular conformational dynamics, and . Current Opinion in Structural Biology, (2014)SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction., , , , , , and . J. Comput. Aided Mol. Des., 36 (4): 291-311 (2022)Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions., , , , , and . J. Comput. Aided Mol. Des., 35 (2): 131-166 (2021)EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment., , , , , , and . CoRR, (2023)