Affordable <i>Ab Initio</i> Path Integral for Thermodynamic Properties via Molecular Dynamics Simulations Using Semiempirical Reference Potential

Xue, Yuanfei; Wang, Jia‐Ning; Hu, Wenjing; Zheng, Jun; Li, Yongle; Pan, Xiaoliang; Mo, Yan; Shao, Yihan; Wang, Lu; Ye, Mei

doi:10.1021/acs.jpca.1c07727

Cited by 8 publications

(10 citation statements)

References 95 publications

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“…However, while dynamical properties from CMD and RPMD are considerably more accurate than those from conventional MD, challenges still exist with the curvature problem in CMD and spurious frequencies in RPMD. Both of these problems can lead to unreliable vibrational spectra, although several recent developments can mitigate them to some extent, including thermostatted RPMD, , Matsubara dynamics, and quasicentroid molecular dynamics. , Furthermore, in contrast with PIMD, which has many techniques developed to make it as efficient as conventional MD, − currently there are only a limited number of techniques available to accelerate RPMD/CMD simulations other than massive parallelization, and thus, the efficient simulation of dynamical properties remains a challenge.…”

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confidence: 99%

Incorporating Nuclear Quantum Effects in Molecular Dynamics with a Constrained Minimized Energy Surface

Chen

Yang

2023

J. Phys. Chem. Lett.

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The accurate incorporation of nuclear quantum effects in large-scale molecular dynamics (MD) simulations remains a significant challenge. Recently, we combined constrained nuclear-electronic orbital (CNEO) theory with classical MD and obtained a new approach (CNEO-MD) that can accurately and efficiently incorporate nuclear quantum effects into classical simulations. In this Letter, we provide the theoretical foundation for CNEO-MD by developing an alternative formulation of the equations of motion for MD. In this new formulation, the expectation values of quantum nuclear positions evolve classically on an effective energy surface that is obtained from a constrained energy minimization procedure when solving for the quantum nuclear wave function, thus enabling the incorporation of nuclear quantum effects in classical MD simulations. For comparison with other existing approaches, we examined a series of model systems and found that this new MD approach is significantly more accurate than the conventional way of performing classical MD and generally outperforms centroid MD and ring-polymer MD in describing vibrations in these model systems.

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confidence: 99%

Incorporating Nuclear Quantum Effects in Molecular Dynamics with a Constrained Minimized Energy Surface

Chen

Yang

2023

J. Phys. Chem. Lett.

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“…At each point along ξ PT , we report the average and standard deviation of the 16 FESs. An alternative approach for calculating FESs from PIMD simulations is to use a semiempirical reference potential, which is a viable strategy when the reference and target potentials have good phase space overlap. − …”

Section: Methodsmentioning

confidence: 99%

“…The development of machine learning correction potentials is not intended to supplant the use of free energy perturbation reweighting approaches. Methods such as weighted thermodynamic perturbation − (wTP) can be a cost-effective means to estimate the FES of an expensive, target Hamiltonian by reweighting the umbrella sampling performed with a reference potential; however, the success of reweighting methods heavily relies upon the degree of agreement between the reference and target potentials. A particularly useful metric to gauge the reliability of the free energy estimate is the “reweighting entropy” .…”

Section: Introductionmentioning

confidence: 99%

Combined QM/MM, Machine Learning Path Integral Approach to Compute Free Energy Profiles and Kinetic Isotope Effects in RNA Cleavage Reactions

Giese

Zeng

Ekesan

et al. 2022

J. Chem. Theory Comput.

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We present a fast, accurate, and robust approach for determination of free energy profiles and kinetic isotope effects for RNA 2′-O-transphosphorylation reactions with inclusion of nuclear quantum effects. We apply a deep potential range correction (DPRc) for combined quantum mechanical/molecular mechanical (QM/MM) simulations of reactions in the condensed phase. The method uses the second-order density-functional tight-binding method (DFTB2) as a fast, approximate base QM model. The DPRc model modifies the DFTB2 QM interactions and applies short-range corrections to the QM/MM interactions to reproduce ab initio DFT (PBE0/6-31G*) QM/MM energies and forces. The DPRc thus enables both QM and QM/MM interactions to be tuned to high accuracy, and the QM/MM corrections are designed to smoothly vanish at a specified cutoff boundary (6 Å in the present work). The computational speed-up afforded by the QM/MM +DPRc model enables free energy profiles to be calculated that include rigorous long-range QM/MM interactions under periodic boundary conditions and nuclear quantum effects through a path integral approach using a new interface between the AMBER and i-PI software. The approach is demonstrated through the calculation of free energy profiles of a native RNA cleavage model reaction and reactions involving thio-substitutions, which are important experimental probes of the mechanism. The DFTB2+DPRc QM/ MM free energy surfaces agree very closely with the PBE0/6-31G* QM/MM results, and it is vastly superior to the DFTB2 QM/ MM surfaces with and without weighted thermodynamic perturbation corrections. 18 O and 34 S primary kinetic isotope effects are compared, and the influence of nuclear quantum effects on the free energy profiles is examined.

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“…The wTP method has been developed over a series of recent articles. − The purpose of the method is to predict the FES of an expensive “target” PE function from the umbrella sampling performed with an inexpensive “reference” PE function. The unbiased target u t ( r hkn ) and reference u h ( r hkn ) PE functions of each sample are evaluated, and the energy differences Δ u th ( r hkn ) = u t ( r hkn ) – u h ( r hkn ) are used to predict the target FES.…”

Section: Theorymentioning

confidence: 99%

“…A series of recent studies have introduced the weighted thermodynamic perturbation (wTP) method. − This method estimates the FES of an expensive target potential from the umbrella sampling performed with a cost-effective reference potential. One can view the wTP method as being analogous to the reference potential method encountered in alchemical free energy applications, − and the accuracy of the wTP method similarly relies on close agreement between the target and reference potentials .…”

Section: Introductionmentioning

confidence: 99%

Multireference Generalization of the Weighted Thermodynamic Perturbation Method

2022

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We describe the generalized weighted thermodynamic perturbation (gwTP) method for estimating the free energy surface of an expensive “high-level” potential energy function from the umbrella sampling performed with multiple inexpensive “low-level” reference potentials. The gwTP method is a generalization of the weighted thermodynamic perturbation (wTP) method developed by Li and co-workers [J. Chem. Theory Comput. 2018, 14, 5583–5596] that uses a single “low-level” reference potential. The gwTP method offers new possibilities in model design whereby the sampling generated from several low-level potentials may be combined (e.g., specific reaction parameter models that might have variable accuracy at different stages of a multistep reaction). The gwTP method is especially well suited for use with machine learning potentials (MLPs) that are trained against computationally expensive ab initio quantum mechanical/molecular mechanical (QM/MM) energies and forces using active learning procedures that naturally produce multiple distinct neural network potentials. Simulations can be performed with greater sampling using the fast MLPs and then corrected to the ab initio level using gwTP. The capabilities of the gwTP method are demonstrated by creating reference potentials based on the MNDO/d and DFTB2/MIO semiempirical models supplemented with the “range-corrected deep potential” (DPRc). The DPRc parameters are trained to ab initio QM/MM data, and the potentials are used to calculate the free energy surface of stepwise mechanisms for nonenzymatic RNA 2′-O-transesterification model reactions. The extended sampling made possible by the reference potentials allows one to identify unequilibrated portions of the simulations that are not always evident from the short time scale commonly used with ab initio QM/MM potentials. We show that the reference potential approach can yield more accurate ab initio free energy predictions than the wTP method or what can be reasonably afforded from explicit ab initio QM/MM sampling.

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Affordable Ab Initio Path Integral for Thermodynamic Properties via Molecular Dynamics Simulations Using Semiempirical Reference Potential

Cited by 8 publications

References 95 publications

Incorporating Nuclear Quantum Effects in Molecular Dynamics with a Constrained Minimized Energy Surface

Incorporating Nuclear Quantum Effects in Molecular Dynamics with a Constrained Minimized Energy Surface

Combined QM/MM, Machine Learning Path Integral Approach to Compute Free Energy Profiles and Kinetic Isotope Effects in RNA Cleavage Reactions

Multireference Generalization of the Weighted Thermodynamic Perturbation Method

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