| Summary: | Thesis (Ph.D.)--Boston University === PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. === The binding of small molecules to a protein is among the most important phenomena in the chemistry of life; the activity and functionality of many proteins depend critically on binding small molecules. A deep understanding of protein-small molecule interactions and the interplay between ligation and function can give valuable insight into key systems of interest. The complete characterization of any small molecule-protein interaction requires quantification of many interactions and the pursuit of such information is the purpose of this body of work.
The discovery of binding regions on proteins, or "hot spots," is an important step in drug development. To this end, a highly regarded and robust fragment-based protocol has been developed for the detection of hot spots. Firstly, we use this protocol in conjunction with other computation techniques, such as homology modeling, to locate the allosteric binding site of £-phenylalanine in Phenylalanine Hydroxylase. Secondly, computational fragment mapping was employed to locate the site of allostery for Ras, an important signaling protein. Lastly, the identification of hot spots for many unligated protein targets is presented highlighting the importance of a reliable way to predict druggability computationally.
The second part of this dissertation shifts focus to the development of electrostatic models of small molecules. It is widely believed that classical potentials can describe neither vibrational frequency shifts in condensed phases nor the response of vibrational frequencies to an applied electric field, the vibrational Stark effect. In this work, an improved classical molecular electrostatic model for the CO ligand was developed to faithfully model these phenomena. This model is found to predict the vibrational Stark effect and Fe-CO binding energy with unprecedented accuracy for such a classical model. As an extension of this work, a geometrically dependent water potential was developed. This work has shown that comparison of results obtained from current water models against experimentally determined proton momentum distributions is an invaluable benchmark === 2031-01-01
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