BIOMOLECULAR DYNAMICS AT LONG TIMESTEPS - BRIDGING THE TIMESCALE GAP BETWEEN SIMULATION AND EXPERIMENTATION

Innovative algorithms have been developed during the past decade for s imulating Newtonian physics for macromolecules. A major goal is allevi ation of the severe requirement that the integration timestep be small enough to resolve the fastest components of the motion and thus guara ntee numerical stability. This timestep problem is challenging if stri ctly faster methods with the same all-atom resolution at small timeste ps are sought. Mathematical techniques that have worked well in other multiple-timescale contexts-where the fast motions are rapidly decayin g or largely decoupled from others-have not been as successful for bio molecules, where vibrational coupling is strong. This review examines general issues that limit the timestep and describes available methods (constrained, reduced-variable, implicit, symplectic, multiple-timest ep, and normal-mode-based schemes). A section compares results of sele cted integrators for a model dipeptide, assessing physical and numeric al performance. Included is our dual timestep method LN, which relies on an approximate linearization of the equations of motion every Delta t interval (5 fs or less), the solution of which is obtained by expli cit integration at the inner timestep Delta tau (e.g., 0.5 fs). LN is computationally competitive, providing 4-5 speedup factors, and result s are in good agreement, in comparison to 0.5 fs trajectories. These c ollective algorithmic efforts help fill the gap between the time range that can be simulated and the timespans of major biological interest (milliseconds and longer). Still, only a hierarchy of models and metho ds, along with experimentational improvements, will ultimately give th eoretical modeling the status of partner with experiment.