An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge.

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作者： Samarjeet,Prasad ^[1] ; Jing,Huang ^[2] ; Qiao,Zeng ^[3] ; Bernard R,Brooks ^[4]

作者单位： Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20814, USA. samar.samarjeet@nih.gov. ^[1] Biophysics and Biophysical Chemistry, The Johns Hopkins University, School of Medicine, Baltimore, MD, 21205, USA. samar.samarjeet@nih.gov. ^[2] School of Life Sciences, Westlake University, 18 Shilongshan Street, Xihu District, Hangzhou, Zhejiang, China. ^[3] Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20814, USA. ^[4]

关键词 Explicit solvent Hybrid QM and MM SAMPL6 pKa prediction

主题词杂环化合物(Heterocyclic Compounds);氢离子浓度(Hydrogen-Ion Concentration);模型, 化学(Models, Chemical);分子结构(Molecular Structure);溶剂(Solvents);热力学(Thermodynamics);水(Water)

DOI 10.1007/s10822-018-0167-1

PMID 30276503

发布时间 2023-10-05

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