scholarly journals 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

2019 ◽  
Vol 21 (37) ◽  
pp. 20595-20605 ◽  
Author(s):  
Xiaoliang Pan ◽  
Pengfei Li ◽  
Junming Ho ◽  
Jingzhi Pu ◽  
Ye Mei ◽  
...  
Keyword(s):  
Free Energy ◽  
Ab Initio ◽  
Quantum Mechanical ◽  
Energy Profile ◽  
Force Matching ◽  
Energy Profiles ◽  
Reference Potential ◽  
Simulation Protocol ◽  
Semi Empirical ◽  
Free Energy Profiles

An efficient and accurate reference potential simulation protocol is proposed for producing ab initio quantum mechanical/molecular mechanical (AI-QM/MM) quality free energy profiles for chemical reactions in a solvent or macromolecular environment.

scholarly journals Accelerated Computation of Free Energy Profile at ab Initio Quantum Mechanical/Molecular Mechanics Accuracy via a Semi-Empirical Reference Potential. II. Recalibrating Semi-Empirical Parameters with Force Matching

2019 ◽  
Author(s):  
Xiaoliang Pan ◽  
Pengfei Li ◽  
Junming Ho ◽  
Jingzhi Pu ◽  
Ye Mei ◽  
...  
Keyword(s):  
Free Energy ◽  
Ab Initio ◽  
Quantum Mechanical ◽  
Energy Profile ◽  
Free Energy Profile ◽  
Force Matching ◽  
Energy Profiles ◽  
Reference Potential ◽  
Semi Empirical ◽  
Free Energy Profiles

An efficient and accurate reference potential simulation protocol is proposed for producing ab initio quantum mechanical molecular mechanical (AI-QM/MM) quality free energy profiles for chemical<br>reactions in a solvent or macromolecular environment. This protocol involves three stages: (a) using force matching to recalibrate a semi-empirical quantum mechanical (SE-QM) Hamiltonian for the specific reaction under study; (b) employing the recalibrated SE-QM Hamiltonian (in combination with molecular mechanical force fields) as the reference potential to drive umbrella samplings along the reaction pathway; and (c) computing AI-QM/MM energy values for collected configurations from the sampling and performing weighted thermodynamic perturbation to acquire AI-QM/MM corrected reaction free energy profile. For three model reactions (identity SN2 reaction, Menshutkin reaction, and glycine proton transfer reaction) in aqueous solution and one enzyme reaction (Claisen arrangement in chorismate mutase), our simulations using recalibrated PM3 SE-QM Hamiltonians well reproduced AI-QM/MM free energy profiles (at the B3LYP/6-31G* level of theory) all within 1 kcal/mol with a 20 to 45 fold reduction in the computer time.

scholarly journals Accelerated Computation of Free Energy Profile at ab Initio Quantum Mechanical/Molecular Mechanics Accuracy via a Semi-Empirical Reference Potential. II. Recalibrating Semi-Empirical Parameters with Force Matching

2019 ◽  
Author(s):  
Xiaoliang Pan ◽  
Pengfei Li ◽  
Junming Ho ◽  
Jingzhi Pu ◽  
Ye Mei ◽  
...  
Keyword(s):  
Free Energy ◽  
Ab Initio ◽  
Quantum Mechanical ◽  
Energy Profile ◽  
Free Energy Profile ◽  
Force Matching ◽  
Energy Profiles ◽  
Reference Potential ◽  
Semi Empirical ◽  
Free Energy Profiles

An efficient and accurate reference potential simulation protocol is proposed for producing ab initio quantum mechanical molecular mechanical (AI-QM/MM) quality free energy profiles for chemical<br>reactions in a solvent or macromolecular environment. This protocol involves three stages: (a) using force matching to recalibrate a semi-empirical quantum mechanical (SE-QM) Hamiltonian for the specific reaction under study; (b) employing the recalibrated SE-QM Hamiltonian (in combination with molecular mechanical force fields) as the reference potential to drive umbrella samplings along the reaction pathway; and (c) computing AI-QM/MM energy values for collected configurations from the sampling and performing weighted thermodynamic perturbation to acquire AI-QM/MM corrected reaction free energy profile. For three model reactions (identity SN2 reaction, Menshutkin reaction, and glycine proton transfer reaction) in aqueous solution and one enzyme reaction (Claisen arrangement in chorismate mutase), our simulations using recalibrated PM3 SE-QM Hamiltonians well reproduced AI-QM/MM free energy profiles (at the B3LYP/6-31G* level of theory) all within 1 kcal/mol with a 20 to 45 fold reduction in the computer time.

Free energy profile analysis to identify factors activating the aggregation-induced emission of a cyanostilbene derivative

2021 ◽  
Author(s):  
Norifumi Yamamoto
Keyword(s):  
Free Energy ◽  
Profile Analysis ◽  
Energy Profile ◽  
Contributing Factors ◽  
Free Energy Profile ◽  
Aggregation Induced Emission ◽  
Energy Profiles ◽  
Free Energy Profiles

The contributing factors that cause the aggregation-induced emission (AIE) are determined by identifying characteristic differences in the free energy profiles of the AIE processes of the AIE-active E-form of CN-MBE and the inactive Z-form.

Accelerated Computation of Free Energy Profile at Ab Initio QM/MM Accuracy via a Semi-Empirical Reference-Potential. III. Gaussian Smoothing on Density-of-States

2020 ◽  
Author(s):  
Wenxin Hu ◽  
Pengfei Li ◽  
Jia-Ning Wang ◽  
Yuanfei Xue ◽  
Yan Mo ◽  
...  
Keyword(s):  
Free Energy ◽  
Ab Initio ◽  
Density Of States ◽  
Energy Region ◽  
Potential Method ◽  
Small Sample ◽  
Low Energy ◽  
Energy Profile ◽  
Free Energy Profile ◽  
Reference Potential

Calculations of free energy profile, aka potential of mean force (PMF), along a chosen collective variable (CV) are now routinely applied to the studies of chemical processes, such as enzymatic reactions and chemical reactions in condensed phases. However, if the ab initio QM/MM level of accuracy is required for the PMF, it can be formidably expensive even with the most advanced enhanced sampling methods, such as umbrella sampling. To ameliorate this difficulty, we developed a novel method for the computation of free energy profile based on the reference-potential method recently, in which a low-level reference Hamiltonian is employed for phase space sampling and the free energy profile can be corrected to the level of interest (the target Hamiltonian) by energy reweighting in a nonparametric way. However, when the reference Hamiltonian is very different from the target Hamiltonian, the calculated ensemble averages, including the PMF, often suffer from numerical instability, which mainly comes from the overestimation of the density-of-states (DoS) in the low-energy region. Stochastic samplings of these low-energy configurations are rare events. If a low-energy configuration has been sampled with a small sample size N, the probability of visiting this energy region is ~ 1/N (shall be exactly 1/N for a single ensemble), which can be orders-of-magnitude larger than the actual DoS. In this work, an assumption of Gaussian distribution is applied to the DoS in each CV bin, and the weight of each configuration is rescaled according to the accumulated DoS. The results show that this smoothing process can remarkably reduce the ruggedness of the PMF and increase the reliability of the reference-potential method.

Sign in / Sign up

Export Citation Format

Share Document