Abstract
Accurate electrostatic descriptions of aqueous solvent are critical for simulation studies of bio-molecules, but the computational cost of explicit treatment of solvent is very high. A computationally more feasible alternative is a generalized Born implicit solvent description which models polar solvent as a dielectric continuum. Unfortunately, the attainable simulation speedup does not transfer to the massive parallel computers often employed for simulation of large structures. Longer cutoff distances, spatially heterogenous distribution of atoms and the necessary three-fold iteration over atom-pairs in each timestep combine to challenge efficient parallel performance of generalized Born implicit solvent algorithms. Here we report how NAMD, a parallel molecular dynamics program, meets the challenge through a unique parallelization strategy. NAMD now permits efficient simulation of large systems whose slow conformational motions benefit most from implicit solvent descriptions due to the inherent low viscosity. NAMD's implicit solvent performance is benchmarked and then illustrated in simulating the ratcheting Escherichia coli ribosome involving ~250,000 atoms.