Department of Physics, School of Science, Nagoya University, JAPAN

Enhanced configurational sampling methods for molecular simulations

          Conventional Monte Carlo and molecular dynamics simulations are greatly hampered by the multiple-minima problem, where the simulations tend to get trapped in some of astronomically large number of local-minimum energy states. In order to overcome this difficulty, we have been advocating the uses of generalized-ensemble algorithms which are based on non-Boltzmann weight factors (for reviews, see, e.g., Refs. [1-3]). With these algorithms we can explore a wide range of the configurational space.
          The advantage of generalized-ensemble algorithms lies in the fact that from only one simulation run, one can obtain various thermodynamic quantities as functions of temperature and other physical parameters by the reweighting techniques. In this talk, I will present the latest results of various applications of generalized-ensemble algorithms in molecular simulations.
[1] A. Mitsutake, Y. Sugita, and Y. Okamoto, Biopolymers 60, 96-123  (2001).
[2] A. Mitsutake, Y. Mori, and Y. Okamoto, in Biomolecular Simulations: Methods and Protocols, L. Monticelli and E. Salonen (eds.) (Humana Press, 2013) pp. 153-195.
[3] Y. Okamoto, in Molecular Science of Fluctuations toward Biological Functions, M. Terazima, M. Kataoka, R. Ueoka, and Y. Okamoto (eds.) (Springer, 2016) pp. 183-204.