Literature DB >> 26588275

Reaction Path Force Matching: A New Strategy of Fitting Specific Reaction Parameters for Semiempirical Methods in Combined QM/MM Simulations.

Yan Zhou1, Jingzhi Pu1.   

Abstract

We present a general strategy of reparametrizing semiempirical (SE) methods against ab initio (AI) methods for combined quantum mechanical and molecular mechanical (QM/MM) simulations of specific chemical reactions in condensed phases. The resulting approach, designated Reaction Path Force Matching (RP-FM), features cycles of sampling configurations along a reaction path on an efficient SE/MM potential energy surface (PES) and adjusting specific reaction parameters (SRPs) in the SE method such that the atomic forces computed at the target AI/MM level are reproduced. Iterative applications of the RP-FM cycle make possible achieving the accuracy of AI/MM simulations without explicitly sampling the computationally expensive AI/MM PES. The bypassed sampling, nevertheless, is implicitly accomplished through the aid of the efficient SE-SRP/MM PES, on which the target-level reaction path is expected to be obtained upon convergence. We demonstrate the effectiveness of the RP-FM procedure for a symmetric proton transfer reaction in the gas phase and in solution. The remarkable agreements between the RP-FM optimized SE-SRP methods and the target AI method on various properties, including energy profiles, potential of mean force free energy profiles, atomic forces, charge populations, and solvation effects, suggest that RP-FM can be used as an efficient and reliable strategy for simulating condensed-phase chemical reactions.

Year:  2014        PMID: 26588275     DOI: 10.1021/ct4009624

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  17 in total

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Authors:  Qiang Cui
Journal:  J Chem Phys       Date:  2016-10-14       Impact factor: 3.488

2.  Toward Determining ATPase Mechanism in ABC Transporters: Development of the Reaction Path-Force Matching QM/MM Method.

Authors:  Y Zhou; P Ojeda-May; M Nagaraju; J Pu
Journal:  Methods Enzymol       Date:  2016-07-01       Impact factor: 1.600

3.  Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery.

Authors:  Tai-Sung Lee; Bryce K Allen; Timothy J Giese; Zhenyu Guo; Pengfei Li; Charles Lin; T Dwight McGee; David A Pearlman; Brian K Radak; Yujun Tao; Hsu-Chun Tsai; Huafeng Xu; Woody Sherman; Darrin M York
Journal:  J Chem Inf Model       Date:  2020-09-16       Impact factor: 4.956

4.  Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations.

Authors:  Jingheng Wu; Lin Shen; Weitao Yang
Journal:  J Chem Phys       Date:  2017-10-28       Impact factor: 3.488

5.  Molecular Dynamics Simulations with Quantum Mechanics/Molecular Mechanics and Adaptive Neural Networks.

Authors:  Lin Shen; Weitao Yang
Journal:  J Chem Theory Comput       Date:  2018-02-26       Impact factor: 6.006

6.  Multiscale Quantum Mechanics/Molecular Mechanics Simulations with Neural Networks.

Authors:  Lin Shen; Jingheng Wu; Weitao Yang
Journal:  J Chem Theory Comput       Date:  2016-09-06       Impact factor: 6.006

7.  QM/MM free energy simulations: recent progress and challenges.

Authors:  Xiya Lu; Dong Fang; Shingo Ito; Yuko Okamoto; Victor Ovchinnikov; Qiang Cui
Journal:  Mol Simul       Date:  2016-07-05       Impact factor: 2.178

8.  Development of a Robust Indirect Approach for MM → QM Free Energy Calculations That Combines Force-Matched Reference Potential and Bennett's Acceptance Ratio Methods.

Authors:  Timothy J Giese; Darrin M York
Journal:  J Chem Theory Comput       Date:  2019-09-17       Impact factor: 6.006

9.  Accelerated computation of free energy profile at ab initio quantum mechanical/molecular mechanical accuracy via a semi-empirical reference potential. II. Recalibrating semi-empirical parameters with force matching.

Authors:  Xiaoliang Pan; Pengfei Li; Junming Ho; Jingzhi Pu; Ye Mei; Yihan Shao
Journal:  Phys Chem Chem Phys       Date:  2019-09-11       Impact factor: 3.676

10.  Accelerating QM/MM Free Energy Computations via Intramolecular Force Matching.

Authors:  Phillip S Hudson; Stefan Boresch; David M Rogers; H Lee Woodcock
Journal:  J Chem Theory Comput       Date:  2018-11-15       Impact factor: 6.006

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