<br>高斯加速分子动力学：原理与应用,Wiley Interdisciplinary Reviews: Computational Molecular Science

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高斯加速分子动力学：原理与应用
Wiley Interdisciplinary Reviews: Computational Molecular Science ( IF 16.8 ) Pub Date : 2021-03-01 , DOI: 10.1002/wcms.1521
Jinan Wang ₁ , Pablo R Arantes ₂ , Apurba Bhattarai ₃ , Rohaine V Hsu ₂ , Shristi Pawnikar ₁ , Yu-Ming M Huang ₄ , Giulia Palermo ₅ , Yinglong Miao ₆

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高斯加速分子动力学 (GaMD) 是一种强大的计算方法，用于同时进行生物分子的无约束增强采样和自由能计算。它的工作原理是添加谐波增强电势来平滑生物分子势能表面并减少能量势垒。 GaMD 将生物分子模拟大大加速了几个数量级。 GaMD 无需设置预定义的反应坐标或集体变量，即可提供无约束的增强采样，有利于模拟复杂的生物过程。 GaMD 增强势呈现高斯分布，从而允许通过累积量扩展至二阶（即“高斯近似”）进行能量重新加权。这导致了生物分子自由能景观的准确重建。还引入了与其他增强采样方法的混合方案，例如副本交换 GaMD (rex-GaMD) 和副本交换伞采样 GaMD (GaREUS)，进一步改进了采样和自由能计算。最近，包括配体 GaMD (LiGaMD) 和肽 GaMD (Pep-GaMD) 在内的新“选择性 GaMD”算法使微秒模拟能够捕获小分子配体和高度灵活的肽的重复解离和结合。然后，模拟可以对配体/肽结合热力学和动力学进行高效的定量表征。总而言之，GaMD 及其创新变体适用于模拟各种生物分子动力学，包括蛋白质折叠、构象变化和变构、配体结合、肽结合、蛋白质-蛋白质/核酸/碳水化合物相互作用以及碳水化合物/核酸相互作用。在这篇综述中，我们介绍了 GaMD 算法的原理以及最近在生物分子模拟和药物设计中的应用。

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Gaussian accelerated molecular dynamics: Principles and applications

Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., “Gaussian approximation”). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica-exchange GaMD (rex-GaMD) and replica-exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new “selective GaMD” algorithms including the Ligand GaMD (LiGaMD) and Peptide GaMD (Pep-GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small-molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein–protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design.

更新日期：2021-03-01

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