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A rapidly-mixing Monte Carlo method for the simulation of slow molecular processes.

V. Durmaz, K. Fackelday, M. Weber – 2011

Since the middle of the last century, the continously increasing computational power has been adopted to molecular modeling and the simulation of molecular dynamics as well. In this field of research, one is interested in the dynamical behaviour of molecular systems. In contrast to the beginnings when only single or very few atoms could be simulated, the systems under consideration have grown to the size of macromolecules like proteins, DNA, or membrane structures nowadays resulting in high-dimensional conformational spaces. This development is triggered by permanently increasing computational power, the utilization of massively parallel hardware as well as improved algorithms and enhanced molecular force fields, covering chemical and especially biological molecular systems at a progressive rate. Applications basing on molecular modeling help to understand and predict molecular phenomena in various fields of applications providing information on e. g. molecular conformations and recognition, protein folding, drug-design, or binding affinities. Typical fields benefiting from their usage are pharmacy, medicine, chemistry and materials research. Unfortunately, often the atomistic structure is so complex that a satisfactory mapping of the processes can hardly be realized, due to the large number of atoms and in particular, the difference in time scales. More precisely, for the molecular function of a protein for example, its folding is a key issue. In contrast to this folding event that may last up to several seconds or even minutes, the time step of an ordinary trajectory based molecular simulation is linked to the fastest molecular oscillation which occurs in case of the chemical H − C bond with a time period around few 10−15 seconds. Even today, exorbitant computational effort and time need to be invested in order to capture such interesting processes.

A rapidly-mixing Monte Carlo method for the simulation of slow molecular processes.
V. Durmaz, K. Fackelday, M. Weber
ISBN: 978-953-307-427-6
Applications of Monte Carlo Methods in Biology, Medicine and Other Fields of Science, C. J. Mode (ed.), InTech, chapter 22, 2011