  Assessing the convergence of a biomolecular simulation is an essential part
of any computational investigation. This is because many important quantities
(e.g., free energy differences) depend on the relative populations of different
conformers; insufficient convergence translates into systematic errors. Here we
present a simple method to self-consistently assess the convergence of a
simulation. Standard clustering methods first generate a set of reference
structures to any desired precision. The trajectory is then classified by
proximity to the reference structures, yielding a one-dimensional histogram of
structurally distinct populations. Comparing ensembles of different
trajectories (or different parts of the same trajectory) built with the same
reference structures provides a sensitive, quantitative measure of convergence.
Please note: this is a preliminary manuscript, and should be read as such.
Comments are most welcome, especially regarding pertinent prior work.
