Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein-Ligand Docking.
Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein-Ligand Docking.
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由小分子晶格数据引导的力场优化可以使一致的子角蛋白蛋白质配体对接。
DOI:
10.1021/acs.jctc.0c01184
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发表时间:
2021-03-09
影响因子:
5.5
通讯作者:
DiMaio F
中科院分区:
文献类型:
--
作者:
Park H;Zhou G;Baek M;Baker D;DiMaio F
Accurate and rapid calculation of protein-small molecule interaction free energies is critical for computational drug discovery. Because of the large chemical space spanned by drug-like molecules, classical force fields contain thousands of parameters describing atom-pair distance and torsional preferences; each parameter is typically optimized independently on simple representative molecules. Here we describe a new approach in which small molecule force field parameters are jointly optimized guided by the rich source of information contained within thousands of available small molecule crystal structures. We optimize parameters by requiring that the experimentally determined molecular lattice arrangements have lower energy than all alternative lattice arrangements. Thousands of independent crystal lattice-prediction simulations were run on each of 1,386 small molecule crystal structures, and energy function parameters of an implicit solvent energy model were optimized so native crystal lattice arrangements had the lowest energy. The resulting energy model was implemented in Rosetta, together with a rapid genetic algorithm docking method employing grid-based scoring and receptor flexibility. The success rate of bound structure recapitulation in cross-docking on 1,112 complexes was improved by more than 10% over previously published methods, with solutions within <1 Å in over half of the cases. Our results demonstrate that small molecule crystal structures are a rich source of information for guiding molecular force field development, and the improved Rosetta energy function should increase accuracy in a wide range of small molecule structure prediction and design studies.
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DOI:
10.1107/s2052520616006831
发表时间:
2016-08-01
影响因子:
1.9
作者:
Broo, Anders;Lill, Sten O. Nilsson
通讯作者:
Lill, Sten O. Nilsson
影响因子:
4.4
作者:
JORGENSEN, WL;CHANDRASEKHAR, J;KLEIN, ML
通讯作者:
KLEIN, ML
影响因子:
62.1
作者:
Lemkul JA;Huang J;Roux B;MacKerell AD Jr
通讯作者:
MacKerell AD Jr
影响因子:
5.5
作者:
Boulanger, Eliot;Huang, Lei;Roux, Benoit
通讯作者:
Roux, Benoit
影响因子:
5.5
作者:
Alford, Rebecca F.;Leaver-Fay, Andrew;Gray, Jeffrey J.
通讯作者:
Gray, Jeffrey J.