Multiple time step diffusive Langevin dynamics for proteins.

We present an algorithm for simulating the long time scale dynamics of proteins and other macromolecules. Our method applies the concept of multiple time step integration to the diffusive Langevin equation, in which short time scale dynamics are replaced by friction and noise. The macromolecular force field is represented at atomic resolution. Slow motions are modeled by constrained Langevin dynamics with very large time steps, while faster degrees of freedom are kept in local thermal equilibrium. In the limit of a sufficiently large molecule, our algorithm is shown to reduce the CPU time required by two orders of magnitude. We test the algorithm on two systems, alanine dipeptide and bovine pancreatic trypsin inhibitor (BPTI), and find that it accurately calculates a variety of equilibrium and dynamical properties. In the case of BPTI, the CPU time required is reduced by nearly a factor of 60 compared to a conventional, unconstrained Langevin simulation using the same force field.