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

A library-based Monte Carlo technique enables rapid equilibrium sampling of a protein model with atomistic components