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Description
The relation between water and protein physics is a topic of much interest. Molecular dynamics (MD) simulations of biomolecules are a common computational technique to obtain atomistic insight into the physical behavior of biomolecules, including the nature of the interaction between water and the protein. In order to model biomolecules

The relation between water and protein physics is a topic of much interest. Molecular dynamics (MD) simulations of biomolecules are a common computational technique to obtain atomistic insight into the physical behavior of biomolecules, including the nature of the interaction between water and the protein. In order to model biomolecules at the highest level of accuracy, an explicit, atomistic representation of the water is typically necessary. The number of water molecules that need to be simulated is normally on the order of thousands. The high dimensional MD dataset is then expanded with considerably more dimensions. We describe here a set of tools which can be used to extract general features of the water behavior, which can then be utilized to build simplified models of the water kinetics which make quantitative predictions, such as the flux rate through a pore.
ContributorsWelland, Ian (Author) / Beckstein, Oliver (Committee member) / Matyushov, Dmitry (Committee member) / Barrett, The Honors College (Contributor)
Created2015-12
Description
The purpose of this project was to compare the different physical models behind four algorithms in computational chemistry: Molecular dynamics with a thermostat (specifically simple velocity rescaling, Berendsen, and Nosé-Hoover), Langevin dynamics, Brownian dynamics, and Monte Carlo. These algorithms were programmed in C and the impact of specific parameters, such

The purpose of this project was to compare the different physical models behind four algorithms in computational chemistry: Molecular dynamics with a thermostat (specifically simple velocity rescaling, Berendsen, and Nosé-Hoover), Langevin dynamics, Brownian dynamics, and Monte Carlo. These algorithms were programmed in C and the impact of specific parameters, such as the coupling parameter and time step, were studied. Their results were compared based on their radial distribution functions and, when the thermostats were in use, fluctuations in temperature.
ContributorsHemesath, Holly (Author) / Heyden, Matthias (Thesis director) / Sulc, Petr (Committee member) / Matyushov, Dmitry (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor)
Created2022-12