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  • 1
    Electronic Resource
    Electronic Resource
    Palo Alto, Calif. : Annual Reviews
    Annual Review of Biophysics and Biomolecular Structure 26 (1997), S. 181-222 
    ISSN: 1056-8700
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
    Topics: Biology , Physics
    Notes: Abstract Innovative algorithms have been developed during the past decade for simulating Newtonian physics for macromolecules. A major goal is alleviation of the severe requirement that the integration timestep be small enough to resolve the fastest components of the motion and thus guarantee numerical stability. This timestep problem is challenging if strictly faster methods with the same all-atom resolution at small timesteps are sought. Mathematical techniques that have worked well in other multiple-timescale contexts-where the fast motions are rapidly decaying or largely decoupled from others-have not been as successful for biomolecules, where vibrational coupling is strong. This review examines general issues that limit the timestep and describes available methods (constrained, reduced-variable, implicit, symplecttic, multiple-timestep, and normal-mode-based schemes). A section compares results of selected integrators for a model dipeptide, assessing physical and numerical performance. Included is our dual timestep method LN, which relies on an approximate linearization of the equations of motion every Deltat interval (5 fs or less), the solution of which is obtained by explicit integration at the inner timestep Deltatau (e.g., 0.5 fs). LN is computationally competitive, providing 4-5 speedup factors, and results are in good agreement, in comparison to 0.5 fs trajectories. These collective 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 methods, along with experimentational improvements, will ultimately give theoretical modeling the status of partner with experiment.
    Type of Medium: Electronic Resource
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