Molecular dynamics simulation is a powerful computational technique to study biomolecular systems, which complements experiments by providing insights into the structural dynamics relevant to biological functions at atomic scale. It can also be used to calculate the free energy landscapes of the conformational transitions to better understand the functions of the biomolecules. However, the sampling of biomolecular configurations is limited by the free energy barriers that need to be overcome, leading to considerable gaps between the timescales reached by MD simulation and those governing biological processes. To address this issue, many enhanced sampling methodologies have been developed to increase the sampling efficiency of molecular dynamics simulations and free energy calculations. Usually, enhanced sampling algorithms can be classified into methods based on collective variables (CV-based) and approaches which do not require predefined CVs (CV-free). In this chapter, the theoretical basis of free energy estimation is briefly reviewed first, followed by the reviews of the most common CV-based and CV-free methods including the presentation of some examples and recent developments. Finally, the combination of different enhanced sampling methods is discussed.

分子动力学模拟是研究生物分子系统的强大计算技术，它通过提供与原子尺度上与生物功能有关的结构动力学的见解来补充实验。它也可以用于计算构象转变的自由能态，以更好地了解生物分子的功能。但是，生物分子构型的采样受到需要克服的自由能壁垒的限制，这导致了MD模拟所达到的时标与控制生物过程的时标之间存在相当大的差距。为了解决这个问题，已经开发了许多增强的采样方法，以提高分子动力学模拟和自由能计算的采样效率。通常，增强型采样算法可分为基于集体变量的方法（基于CV）和不需要预定义CV的方法（无CV）。在本章中，首先简要回顾了自由能估算的理论基础，然后回顾了最常见的基于CV和无CV的方法，包括一些示例的介绍和最新进展。最后，讨论了不同增强采样方法的组合。