Multiscale Monte Carlo Modeling of Proteins

A multiscale Monte Carlo sampling scheme for macromolecules is presented that allows for hierarchical sampling [1] of sidechain and backbone degrees of freedom.  The multiscale sampling strategy is adapted from a multiple ‘time step' sampling algorithm [2], and obeys detailed balance.  The method uses the OPLS-AA 2001 forcefield [3] and the SGB/NP [4,5] implicit solvent models for solvation.  The sidechains are sampled using randomly selected chi angles and subsequent steric screening, and the backbone degrees of freedom sampled using a modern analytical loop closure algorithm[6].  Validation data will be presented on binding pockets and flexible loops.  As an application of the method, binding pocket flexibility of 6 apo proteins are studied, as well as protein loops with known flexibility.  The method presented could provide insight into flexible residues of a protein that are likely to change conformation in the presence upon ligand binding.

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