Equilibrium sampling of self-associating polymer solutions: a parallel selective tempering approach.

Abstract

We present a novel simulation algorithm based on tempering a fraction of relaxation-limiting interactions to accelerate the process of obtaining uncorrelated equilibrium configurations of self-associating polymer solutions. This approach consists of tempering (turning off) the attractive interactions for a fraction of self-associating groups determined by a biasing field h. A number of independent configurations (replicas) with overlapping Hamiltonian distributions in the expanded (NVTh) ensemble with constant NVT but different biasing fields, forming a chain of Hamiltonians, were simulated in parallel with occasional attempts to exchange the replicas associated with adjacent fields. Each field had an associated distribution of tempered interactions, average fraction of tempered interactions, and structural decorrelation time. Tempering parameters (number of replicas, fields, and exchange frequencies) were chosen to obtain the highest efficiency in sampling equilibrium configurations of a self-association polymer solution based on short serial simulation runs and a statistical model. Depending on the strength of the relaxation-limiting interactions, system size, and thermodynamic conditions, the algorithm can be orders of magnitude more efficient than conventional canonical simulation and is superior to conventional temperature parallel tempering.