Fu Haohao, Zhou Mengchen, Chipot Christophe, Cai Wensheng
Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China.
Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China.
J Phys Chem B. 2024 Oct 10;128(40):9706-9713. doi: 10.1021/acs.jpcb.4c04857. Epub 2024 Sep 25.
This tutorial is designed to help users overcome sampling challenges and improve computational efficiency in collective-variable (CV)-based enhanced-sampling, or importance-sampling, simulations. Toward this end, we introduce well-tempered metadynamics-extended adaptive biasing force (WTM-eABF) and its integration with Gaussian accelerated molecular dynamics (GaMD). Additionally, use will be made of a method for identifying the least-free-energy pathway (LFEP) and multiple concurrent pathways on high-dimensional free-energy surfaces. We illustrate these sampling techniques with the conformational equilibria of trialanine and chignolin in aqueous solution as test cases. This tutorial assumes that the user has prior experience with molecular dynamics (MD) simulations, in general, with the popular program NAMD, and to some extent with Colvars, the module for CV-based calculations. This tutorial can, however, in large measure be used in conjunction with alternate MD engines that support the Colvars module such as GROMACS, LAMMPS, and Tinker-HP.
本教程旨在帮助用户克服采样挑战，并提高基于集体变量（CV）的增强采样（即重要性采样）模拟中的计算效率。为此，我们引入了温和元动力学扩展自适应偏置力（WTM-eABF）及其与高斯加速分子动力学（GaMD）的集成。此外，还将使用一种在高维自由能表面上识别最低自由能路径（LFEP）和多个并发路径的方法。我们以水溶液中三丙氨酸和奇果菌素的构象平衡作为测试案例来说明这些采样技术。本教程假定用户一般具有分子动力学（MD）模拟的经验，特别是使用流行的程序NAMD，并且在一定程度上熟悉用于基于CV计算的模块Colvars。不过，本教程在很大程度上也可与支持Colvars模块的其他MD引擎（如GROMACS、LAMMPS和Tinker-HP）结合使用。
