首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Unconstrained enhanced sampling for free energy calculations of biomolecules: a review
Authors:Yinglong Miao  J Andrew McCammon
Institution:1. Howard Hughes Medical Institute, University of California, San Diego, CA, USA;2. Department of Pharmacology, University of California, San Diego, CA, USAyimiao@ucsd.edu;4. Department of Pharmacology, University of California, San Diego, CA, USA;5. Department of Chemistry and Biochemistry, University of California, San Diego, CA, USA
Abstract:Abstract

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations.
Keywords:Biomolecules  enhanced sampling  unconstrained  free energy
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号