Data Driven Modeling of Proteins
Doctor of Philosophy
Proteins are tiny molecular machines that perform the vast majority of the functions in living cells. In order for the protein to perform its function, it has to be able to fold from a disordered coil into a specific compact structure. Two new computational methods are developed that take advantage of the large amount of data generated in both experiments and computer simulations in order to better understand how proteins work. The first method (pyODEM) improves the modeling of proteins on the global scale, while a second method (pyFrustration) probes the protein's local frustration that might impede the folding process. Use of these methods allows us to construct more dynamically accurate protein models and improves our understanding of how a protein folds and performs its function.