Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging
Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging
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DOI：
10.1016/j.saa.2013.10.059
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发表时间：
2015-02-05
影响因子：
4.4
通讯作者：
Popelier, Paul L. A.
中科院分区：
文献类型：
--
作者：
Hughes, Timothy J.;Kandathil, Shaun M.;Popelier, Paul L. A.
由于分子间的相互作用，如氢键是静电的起源，严格处理这个术语的力场方法应该是强制性的。我们提出了一种方法，能够准确地再现这种相互作用的七个货车德瓦耳斯复合物。它使用原子多极矩到六极矩，通过机器学习方法克里金映射到核坐标的位置。在HF/6- 31 C **、B3 LYP/aug-cc-pVDZ和M06-2X/aug-cc-pVDZ三个水平上建立模型。克立格模型的质量是通过其预测真实能量已知的外部测试示例中原子之间的静电相互作用能的能力来衡量的。在所有的理论水平上，>90%的小货车德瓦尔斯复合物的测试案例预测在1 kJ mol（-1），降低到60-70%的测试案例为较大的碱基对复合物。在B3 LYP和M06-2X水平上获得的矩建立的模型通常优于HF水平。对于所有系统的个人相互作用预测的平均无符号误差小于1千焦摩尔（-1）。(C)2013爱思唯尔有限公司版权所有。
As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31C**, B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1). (C) 2013 Elsevier B.V. All rights reserved.