  There is significant interest in rapid protein simulations because of the
time-scale limitations of all-atom methods. Exploiting the low cost and great
availability of computer memory, we report a Monte Carlo technique for
incorporating fully flexible atomistic protein components (e.g., peptide
planes) into protein models without compromising sampling speed or statistical
rigor. Building on existing approximate methods (e.g., Rosetta), the technique
uses pre-generated statistical libraries of all-atom components which are
swapped with the corresponding protein components during a simulation. The
simple model we study consists of the three all-atom backbone residues -- Ala,
Gly, and Pro -- with structure-based (Go-like) interactions. For the five
different proteins considered in this study, LBMC can generate at least 30
statistically independent configurations in about a month of single CPU time.
Minimal additional cost is required to add residue-specific interactions.
