  Although atomistic simulations of proteins and other biological systems are
approaching microsecond timescales, the quality of trajectories has remained
difficult to assess. Such assessment is critical not only for establishing the
relevance of any individual simulation but also in the extremely active field
of developing computational methods. Here we map the trajectory assessment
problem onto a simple statistical calculation of the ``effective sample size''
- i.e., the number of statistically independent configurations. The mapping is
achieved by asking the question, ``How much time must elapse between snapshots
included in a sample for that sample to exhibit the statistical properties
expected for independent and identically distributed configurations?'' The
resulting ``structural de-correlation time'' is robustly calculated using exact
properties deduced from our previously developed ``structural histograms,''
without any fitting parameters. We show the method is equally and directly
applicable to toy models, peptides, and a 72-residue protein model. Variants of
our approach can readily be applied to a wide range of physical and chemical
systems.
