Markov state models of biomolecular conformational dynamics

• Published in: Current opinion in structural biology Vol. 25; pp. 135 - 144
• Main Authors: Chodera, John D, Noé, Frank
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.04.2014
• Subjects: Biochemistry - methods; Markov Chains; Models, Molecular; Molecular Conformation; Proteins - chemistry; Proteins - metabolism
• ISSN: 0959-440X; 1879-033X
• DOI: 10.1016/j.sbi.2014.04.002

•Markov state models (MSMs) are now widely used to study the long-time statistical dynamics of biomolecules.•Recent theoretical advances emphasize MSMs can closely approximate the true statistical dynamics.•MSM construction has been greatly simplified by new software packages.•Numerous applications have demonstrated the utility of MSMs for extracting insight and connecting with experiment.•Remaining challenges include fully automated adaptive MSM construction and balancing of statistical and systematic error. It has recently become practical to construct Markov state models (MSMs) that reproduce the long-time statistical conformational dynamics of biomolecules using data from molecular dynamics simulations. MSMs can predict both stationary and kinetic quantities on long timescales (e.g. milliseconds) using a set of atomistic molecular dynamics simulations that are individually much shorter, thus addressing the well-known sampling problem in molecular dynamics simulation. In addition to providing predictive quantitative models, MSMs greatly facilitate both the extraction of insight into biomolecular mechanism (such as folding and functional dynamics) and quantitative comparison with single-molecule and ensemble kinetics experiments. A variety of methodological advances and software packages now bring the construction of these models closer to routine practice. Here, we review recent progress in this field, considering theoretical and methodological advances, new software tools, and recent applications of these approaches in several domains of biochemistry and biophysics, commenting on remaining challenges.