title: Enhanced sampling techniques in molecular dynamics simulations of biological systems.
abstract: 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.
  
  
  METHODS
  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.
  
  
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Beckman Institute, University of Illinois, Urbana, IL 61801, USA.
authors.forename: Rafael C
authors.initials: RC
authors.lastname: Bernardi
authors.affiliation: Center for Biophysics and Computational Biology, University of Illinois, Urbana, IL 61801, USA.
authors.forename: Marcelo C R
authors.initials: MCR
authors.lastname: Melo
authors.affiliation: Beckman Institute, University of Illinois, Urbana, IL 61801, USA; Center for Biophysics and Computational Biology, University of Illinois, Urbana, IL 61801, USA; Department of Physics, University of Illinois, Urbana, IL 61801, USA. Electronic address: kschulte@ks.uiuc.edu.
authors.forename: Klaus
authors.initials: K
authors.lastname: Schulten
mesh_terms: D000465:Algorithms; D002236:Carbohydrate Conformation; D002241:Carbohydrates / Q000737:chemistry*; D044603:Cellulosomes / Q000737:chemistry; D008055:Lipids / Q000737:chemistry*; D056004:Molecular Dynamics Simulation; D015394:Molecular Structure; D009690:Nucleic Acid Conformation; D009696:Nucleic Acids / Q000737:chemistry* / Q000378:metabolism; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D015203:Reproducibility of Results; D013269:Stochastic Processes; D013329:Structure-Activity Relationship; D013499:Surface Properties
chemical_list: D002241:Carbohydrates; D008055:Lipids; D009696:Nucleic Acids; D011506:Proteins
keywords: Cellulosome; Enhanced sampling; Generalized simulated annealing; Metadynamics; Molecular dynamics; Replica-exchange molecular dynamics