title: Using simulation to interpret experimental data in terms of protein conformational ensembles.
abstract: In their biological environment, proteins are dynamic molecules, necessitating an ensemble structural description. Molecular dynamics simulations and solution-state experiments provide complimentary information in the form of atomically detailed coordinates and averaged or distributions of structural properties or related quantities. Recently, increases in the temporal and spatial scale of conformational sampling and comparison of the more diverse conformational ensembles thus generated have revealed the importance of sampling rare events. Excitingly, new methods based on maximum entropy and Bayesian inference are promising to provide a statistically sound mechanism for combining experimental data with molecular dynamics simulations.
authors.affiliation: Centre for Theoretical Chemistry and Physics, Institute of Natural and Mathematical Sciences, Massey University Auckland, Albany, Auckland 0632, New Zealand; Biomolecular Interaction Centre, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand; Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Private Bag 92019, Auckland, New Zealand. Electronic address: j.allison@massey.ac.nz.
authors.forename: Jane R
authors.initials: JR
authors.lastname: Allison
mesh_terms: D001499:Bayes Theorem; D019277:Entropy; D056004:Molecular Dynamics Simulation; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism
chemical_list: D011506:Proteins