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I am a postdoc in the chemistry department working in Prof. Yu Shan Lin's group. My research involves extensive Molecular Dynamics (MD) simulation of peptides and proteins. We use the MD method to study the folding thermodynamics and kinetics of glycoproteins, stapled peptides and cyclic peptides. The free energy landscape of protein and peptide folding is believed to be rugged. It contains many free energy barriers that are much larger than thermal energies, and the protein might get trapped in many local free energy minima at room temperature. This trapping limits the capacity of effectively sampling protein configuration space. In my research, we use various techniques to overcome the free energy barriers and improve the sampling, for example by using, the Replica-Exchange Molecular Dynamics (REMD) method and the Umbrella Sampling (US) method. In a typical US simulation, the reaction coordinate(s) is broken into small windows, and independent runs have to be done for each window. For example, 36 independent runs have to be performed if we choose a dihedral as the reaction coordinate and use 10 degree window. In a 2D US simulation, the number of independent runs increases to 36x36. Our system usually contains 1 protein molecule and thousands of water molecules; an independent run usually takes about 2.5 hours with 8 CPUs. This means that we have to run 135 days to finish one 2D US simulation on a single 8-core machine! With the large amounts of CPUs provided by the Tufts cluster, we can finish one 2D US simulation within 2 days! The benefit provided by the speed up is that we have the chance to explore more systems and methods.Rebecca Batorsky
As part of my PhD research in the physics department, I studied various aspects of intra-host virus evolution. I used the cluster in order to run large simulations of evolving virus populations. Our simulations typically ran in Matlab, and we were able to run more than 30 simulations in parallel using multiple compute nodes. This enables faster collection of simulation data and allowed us to study large population sizes than would otherwise have been possible. Furthermore, the ability to access the my files on the cluster and programs like Matlab and Mathematica from any computer was extremely useful.
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