Scheraga Harold A, Khalili Mey, Liwo Adam
Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853-1301, USA.
Annu Rev Phys Chem. 2007;58:57-83. doi: 10.1146/annurev.physchem.58.032806.104614.
Molecular dynamics (MD) is an invaluable tool with which to study protein folding in silico. Although just a few years ago the dynamic behavior of a protein molecule could be simulated only in the neighborhood of the experimental conformation (or protein unfolding could be simulated at high temperature), the advent of distributed computing, new techniques such as replica-exchange MD, new approaches (based on, e.g., the stochastic difference equation), and physics-based reduced models of proteins now make it possible to study protein-folding pathways from completely unfolded structures. In this review, we present algorithms for MD and their extensions and applications to protein-folding studies, using all-atom models with explicit and implicit solvent as well as reduced models of polypeptide chains.
分子动力学（MD）是一种用于在计算机上研究蛋白质折叠的宝贵工具。尽管就在几年前，蛋白质分子的动态行为还只能在实验构象附近进行模拟（或者在高温下模拟蛋白质解折叠），但分布式计算的出现、诸如副本交换分子动力学等新技术、新方法（例如基于随机差分方程）以及基于物理学的蛋白质简化模型，现在使得从完全未折叠的结构研究蛋白质折叠途径成为可能。在这篇综述中，我们介绍分子动力学算法及其扩展，以及它们在蛋白质折叠研究中的应用，使用了具有显式和隐式溶剂的全原子模型以及多肽链的简化模型。
