Ensemble based convergence analysis of biomolecular trajectories

¹ University of Pittsburgh
² University of Pittsburgh, Dept of Computational Biology

^* To whom correspondence should be addressed. E-mail: dmz{at}ccbb.pitt.edu.

Submitted on February 8, 2006
Revised on March 15, 2006
Accepted on 30 March 2006

	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 (~ 50 nsec) may not be converged for this small---but highly flexible---system.

Key Words: convergence, efficiency, met-enkephalin, structural histograms

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