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Ensemble-Based Convergence Analysis of Biomolecular Trajectories

Department of Computational Biology, School of Medicine and Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania

Correspondence: Address reprint requests to D. M. Zuckerman, Tel.: 412-648-3335; E-mail: dmz{at}ccbb.pitt.edu.

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 (50 ns) may not be converged for this small—but highly flexible—system.

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