Frontiers in High-Performance, Large-Scale Molecular Dynamics. 35 Years of Molecular-Dynamics Simulations of Biological Systems
WS Cai and C Chipot, ACTA CHIMICA SINICA, 71, 159-168 (2013).
The main thrust of this contribution is to review applications of numerical simulations to biological systems over the past 35 years- specifically classical molecular-dynamics simulations, and related preferential sampling approaches aimed at exploring selected degrees of freedom of the molecular assembly. Arguably enough, structural biology and biophysics represent one of the greatest challenges for molecular dynamics, owing to the size of the biological.objects of interest and the time scales spanned by the molecular processes of the cell machinery in which these objects are prominent actors. The reader is assumed to be fully familiarized with the basic theoretical underpinnings of molecular-dynamics simulations, which will be discussed here from a biological standpoint, emphasizing how the enterprise of modeling increasingly larger molecular assemblies over physiologically relevant times has shaped the field. This review article will further show how the unbridled race to dilate both the spatial and the temporal scales, in an effort to bridge the gap between the latter, has greatly benefitted from groundbreaking advances on the hardware, computational front-notably through the development of massively parallel and dedicated architectures, as well as on the methodological, algorithmic front. The current trends in this research field, boosted by recent, cutting-edge achievements, wherein molecular dynamics has reached new frontiers, provide the basis for an introspective reflection and a prospective outlook into the future of biologically-oriented, high- performance numerical simulations. Furthermore, alternatives to brute- force molecular dynamics towards connecting time and size scales will be discussed, in particular a class of approaches relying upon the preferential sampling of judiciously chosen, important degrees of freedom of the biological object at hand. These methods, targeted primarily at providing a detailed thermodynamic picture of the molecular process at hand, can be viewed as computational tweezers designed to dissect the latter by means of a reduced set of collective variables.
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