TY - JOUR
T1 - Biomolecular dynamics at long timesteps
T2 - Bridging the timescale gap between simulation and experimentation
AU - Schlick, Tamar
AU - Barth, Eric
AU - Mandziuk, Margaret
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 1997
Y1 - 1997
N2 - 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, symplectic, 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 Δt interval (5 fs or less), the solution of which is obtained by explicit integration at the inner timestep Δτ (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.
AB - 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, symplectic, 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 Δt interval (5 fs or less), the solution of which is obtained by explicit integration at the inner timestep Δτ (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.
KW - Linearized models
KW - Molecular and Langevin dynamics
KW - Multiple timesteps
KW - Normal modes
KW - Numerical integration
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U2 - 10.1146/annurev.biophys.26.1.181
DO - 10.1146/annurev.biophys.26.1.181
M3 - Review article
C2 - 9241418
AN - SCOPUS:0030918284
SN - 1056-8700
VL - 26
SP - 181
EP - 222
JO - Annual Review of Biophysics and Biomolecular Structure
JF - Annual Review of Biophysics and Biomolecular Structure
ER -