元动力学
分子动力学
模拟退火
复制品
最大值和最小值
采样(信号处理)
计算机科学
统计物理学
伞式取样
生物系统
能源景观
复杂系统
计算化学
化学
物理
算法
数学
人工智能
生物
艺术
数学分析
生物化学
滤波器(信号处理)
视觉艺术
计算机视觉
作者
Rafael C. Bernardi,Marcelo C. R. Melo,Klaus Schulten
标识
DOI:10.1016/j.bbagen.2014.10.019
摘要
Molecular dynamics has emerged as an important research methodology covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local minima separated by high-energy barriers, which govern the biomolecular motion.In the past few decades methods have been developed that address the sampling problem, such as replica-exchange molecular dynamics, metadynamics and simulated annealing. Here we present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied.Enhanced sampling methods have been employed for a broad range of biological systems and the choice of a suitable method is connected to biological and physical characteristics of the system, in particular system size. While metadynamics and replica-exchange molecular dynamics are the most adopted sampling methods to study biomolecular dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromolecular complexes.Molecular dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biological function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
科研通智能强力驱动
Strongly Powered by AbleSci AI