Bernardi, Rafael C.; Melo, Marcelo C. R.; Schulten, Klaus
Enhanced sampling techniques in molecular dynamics simulations of biological systems
BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS, 1850:872-877, MAY 2015

Background: 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. Scope of review: 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. Major conclusions: 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. General significance: Molecular dynamics trajectories frequently do not reach all relevant conformational sub-states, 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. (C) 2014 Elsevier B.V. All rights reserved.

DOI:10.1016/j.bbagen.2014.10.019

Find in TCBG Publications Database.

Find full text with Google Scholar.