title: Ensemble-based convergence analysis of biomolecular trajectories.
abstract: Assessing the convergence of a biomolecular simulation is an essential part of any careful computational investigation, because many fundamental aspects of molecular behavior depend on the relative populations of different conformers. Here we present a physically intuitive method to self-consistently assess the convergence of trajectories generated by molecular dynamics and related methods. Our approach reports directly and systematically on the structural diversity of a simulation trajectory. Straightforward clustering and classification steps are the key ingredients, allowing the approach to be trivially applied to systems of any size. Our initial study on met-enkephalin strongly suggests that even fairly long trajectories (approximately 50 ns) may not be converged for this small--but highly flexible--system.
authors.affiliation: Department of Computational Biology, School of Medicine, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
authors.forename: Edward
authors.initials: E
authors.lastname: Lyman
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Zuckerman
mesh_terms: D001704:Biopolymers / Q000737:chemistry*; D003198:Computer Simulation; D004548:Elasticity; D008956:Models, Chemical; D008958:Models, Molecular; D009038:Motion; D046912:Multiprotein Complexes / Q000737:chemistry* / Q000648:ultrastructure; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure; D013314:Stress, Mechanical
chemical_list: D001704:Biopolymers; D046912:Multiprotein Complexes; D011506:Proteins