Date of Award
Doctor of Philosophy (PhD)
Electrostatics plays an essential role in molecular biology. Modeling electrostatics in molecular biology is complicated due to the water phase, mobile ions, and irregularly shaped inhomogeneous biological macromolecules. This dissertation presents the popular DelPhi package that solves PBE and delivers the electrostatic potential distribution of biomolecules. We used the newly developed DelPhiForce steered Molecular Dynamics (DFMD) approach to model the binding of barstar to barnase and demonstrated that the first-principles method could also model the binding. This dissertation also reflects the use of existing computational approaches to model the effects of Single Amino Acid Variations (SAVs) to reveal molecular mechanisms related to human diseases. We used our supervised in-house combinatory in-silico predictor method to investigate the impact of unclassified missense mutations in the MEN1 gene found in breast cancer tissue. We also examined the biophysical and biochemical properties to predict the effects of these missense variants on the menin protein stability and interactions. The results are compared with the impact of known pathogenic mutations in menin causing neoplasia. In the end, we showed the role of intravesicular pH in melanosome maturation and formation. The computational investigation was done to understand the pH-dependent stability of several membrane proteins and compared them to the pH dependence of the strength of TYR. We confirmed that the pH optimum of TYR is neutral. Our findings are consistent with previous work that demonstrated a correlation between the pH optima of stability and activity.
Koirala, Mahesh, "Modeling Electrostatics in Molecular Biology and Its Relevance With Molecular Mechanisms of Diseases" (2022). All Dissertations. 3075.
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