Pan Xiaoliang, Van Richard, Epifanovsky Evgeny, Liu Jian, Pu Jingzhi, Nam Kwangho, Shao Yihan
Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019-5251, United States.
Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, United States.
J Phys Chem B. 2022 Jun 2. doi: 10.1021/acs.jpcb.2c02262.
Molecular dynamics (MD) simulations employing quantum mechanical and molecular mechanical (ai-QM/MM) potentials are considered to be the state of the art, but the high computational cost associated with the ai-QM calculations remains a theoretical challenge for their routine application. Here, we present a modified protocol of the multiple time step (MTS) method for accelerating ai-QM/MM MD simulations of condensed-phase reactions. Within a previous MTS protocol [Nam 2014, 10, 4175], reference forces are evaluated using a low-level (semiempirical QM/MM) Hamiltonian and employed at inner time steps to propagate the nuclear motions. Correction forces, which arise from the force differences between high-level (ai-QM/MM) and low-level Hamiltonians, are applied at outer time steps, where the MTS algorithm allows the time-reversible integration of the correction forces. To increase the outer step size, which is bound by the highest-frequency component in the correction forces, the semiempirical QM Hamiltonian is recalibrated in this work to minimize the magnitude of the correction forces. The remaining high-frequency modes, which are mainly bond stretches involving hydrogen atoms, are then removed from the correction forces. When combined with a Langevin or SIN(R) thermostat, the modified MTS-QM/MM scheme remains robust with an up to 8 (with Langevin) or 10 fs (with SIN(R)) outer time step (with 1 fs inner time steps) for the chorismate mutase system. This leads to an over 5-fold speedup over standard ai-QM/MM simulations, without sacrificing the accuracy in the predicted free energy profile of the reaction.
采用量子力学和分子力学(ai-QM/MM)势的分子动力学(MD)模拟被认为是目前的先进技术,但与ai-QM计算相关的高计算成本仍然是其常规应用的理论挑战。在此,我们提出了一种改进的多时间步长(MTS)方法协议,用于加速凝聚相反应的ai-QM/MM MD模拟。在先前的MTS协议[Nam 2014, 10, 4175]中,参考力使用低级(半经验QM/MM)哈密顿量进行评估,并在内部时间步长用于传播核运动。由高级(ai-QM/MM)和低级哈密顿量之间的力差产生的校正力,在外部时间步长应用,其中MTS算法允许校正力的时间可逆积分。为了增加受校正力中最高频率分量限制的外部步长,在这项工作中对半经验QM哈密顿量进行了重新校准,以最小化校正力的大小。然后从校正力中去除主要涉及氢原子的键伸缩的其余高频模式。当与朗之万或SIN(R)恒温器结合时,改进的MTS-QM/MM方案对于分支酸变位酶系统在高达8 fs(使用朗之万)或10 fs(使用SIN(R))的外部时间步长(内部时间步长为1 fs)下仍然稳健。这导致比标准ai-QM/MM模拟加速超过5倍,而不会牺牲反应预测自由能分布的准确性。