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使用TIP3P-F水在分子动力学模拟中实现更快采样

Faster Sampling in Molecular Dynamics Simulations with TIP3P-F Water.

作者信息

Rosas Jiménez José Guadalupe, Fábián Balázs, Hummer Gerhard

机构信息

Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max-von-Laue-Straße 3, 60438 Frankfurt am Main, Germany.

IMPRS on Cellular Biophysics, Max Planck Institute of Biophysics, Max-von-Laue-Straße 3, 60438 Frankfurt am Main, Germany.

出版信息

J Chem Theory Comput. 2024 Dec 24;20(24):11068-11081. doi: 10.1021/acs.jctc.4c00990. Epub 2024 Dec 12.

DOI:10.1021/acs.jctc.4c00990
PMID:39668361
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11672673/
Abstract

The need for short time steps currently limits routine atomistic molecular dynamics (MD) simulations to the microsecond time scale. For long time steps, the numerical integration of the equations of motion becomes unstable, resulting in catastrophic crashes. Here, we combine mass repartitioning and rescaling to construct a water model that increases the sampling efficiency in biomolecular simulations without compromising integration stability and with preserved structural and thermodynamic properties. The resulting "fast water" is then used with a time step as before in combination with standard force fields. The reduced water viscosity and faster diffusion result in proportionally faster sampling of the larger-scale motions in the conformation space of both solute and solvent. We illustrate this approach by developing TIP3P-F based on the popular TIP3P model of water. A roughly 2-fold boost in the sampling efficiency at minimal cost in accuracy is substantial and helps lower the energy impact of large-scale MD simulations. The approach is general and can readily be applied to other water models and different types of solvents.

摘要

目前，由于需要采用短时间步长，常规的原子分子动力学（MD）模拟被限制在微秒时间尺度。对于长时间步长，运动方程的数值积分会变得不稳定，从而导致灾难性的崩溃。在此，我们结合质量重新分配和重新缩放来构建一个水模型，该模型在不影响积分稳定性且保留结构和热力学性质的情况下，提高了生物分子模拟中的采样效率。然后将得到的“快速水”与之前的时间步长一起用于标准力场。水的粘度降低和扩散加快，使得溶质和溶剂在构象空间中更大尺度运动的采样速度相应加快。我们通过基于流行的TIP3P水模型开发TIP3P-F来说明这种方法。在精度损失最小的情况下，采样效率大约提高了2倍，这是相当可观的，有助于降低大规模MD模拟的能量影响。该方法具有通用性，可轻松应用于其他水模型和不同类型的溶剂。

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