Masking resonance artifacts in force-splitting methods for biomolecular simulations by extrapolative Langevin dynamics

Numerical resonance artifacts have become recognized recently as a limiting factor to increasing the timestep in multiple-timestep (MTS) biomolecular dynamics simulations. At certain timesteps correlated to internal motions (e.g., 5 fs, around half the period of the fastest bond stretch, T-min), visible inaccuracies or instabilities can occur. Impulse-MTS schemes are vulnerable to these resonance errors since large energy pulses are introduced to the governing dynamics equations when the slow forces are evaluated. We recently showed that such resonance artifacts can be masked significantly by applying extrapolative splitting to stochastic dynamics. Theoretical and numerical analyses of force-splitting integrators based on the Verlet discretization are reported here for linear models to explain these observations and to suggest how to construct effective integrators for biomolecular dynamics that balance stability with accuracy. Analyses for Newtonian dynamics demonstrate the severe resonance patterns of the Impulse splitting, with this severity worsening with the outer timestep. Delta t: Constant Extrapolation is generally unstable, but the disturbances do not grow with Delta t. Thus. the stochastic extrapolative combination can counteract generic instabilities and largely alleviate resonances with a sufficiently strong Langevin heat-bath coupling (gamma), estimates for which are derived here based on the fastest and slowest motion periods. These resonance results generally hold for nonlinear test systems: a water tetramer and solvated protein. Proposed related approaches such as Extrapolation/Correction and Midpoint Extrapolation work better than Constant Extrapolation only for timesteps less than T-min/2. An effective extrapolative stochastic approach for biomolecules that balances long-timestep stability with good accuracy for the fast subsystem is then applied to a biomolecule using a three-class partitioning: the medium forces are treated by Midpoint Extrapolation via position Verlet, and the slow forces are incorporated by Constant Extrapolation. The resulting algorithm (LN) performs well on a solvated protein system in terms of thermodynamic properties and yields an order of magnitude speedup with respect to single-timestep Langevin trajectories. Computed spectral density functions also show how the Newtonian modes can be approximated by using a small gamma in the range Of 5-20 ps(-1). (C) 1999 Academic Press.