Analysis of Binding Site Hot Spots on the Surface of Ras GTPase

We have recently discovered an allosteric switch in Ras, bringing an additional level of complexity to this GTPase whose mutants are involved in nearly 30% of cancers. Upon activation of the allosteric switch, there is a shift in helix 3/loop 7 associated with a disorder to order transition in the active site. Here, we use a combination of multiple solvent crystal structures and computational solvent mapping (FTMap) to determine binding site hot spots in the “off” and “on” allosteric states of the GTP-bound form of H-Ras. Thirteen sites are revealed, expanding possible target sites for ligand binding well beyond the active site. Comparison of FTMaps for the H and K isoforms reveals essentially identical hot spots. Furthermore, using NMR measurements of spin relaxation, we determined that K-Ras exhibits global conformational dynamics very similar to those we previously reported for H-Ras. We thus hypothesize that the global conformational rearrangement serves as a mechanism for allosteric coupling between the effector interface and remote hot spots in all Ras isoforms. At least with respect to the binding sites involving the G domain, H-Ras is an excellent model for K-Ras and probably N-Ras as well. Ras has so far been elusive as a target for drug design. The present work identifies various unexplored hot spots throughout the entire surface of Ras, extending the focus from the disordered active site to well-ordered locations that should be easier to target

Understanding small molecule-protein interactions

Thesis (Ph.D.)--Boston UniversityPLEASE 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 [email protected]. 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 benchmark2031-01-0

New Frontiers in Druggability

A powerful early approach to evaluating the druggability of proteins involved determining the hit rate in NMR-based screening of a library of small compounds. Here, we show that a computational analog of this method, based on mapping proteins using small molecules as probes, can reliably reproduce druggability results from NMR-based screening and can provide a more meaningful assessment in cases where the two approaches disagree. We apply the method to a large set of proteins. The results show that, because the method is based on the biophysics of binding rather than on empirical parametrization, meaningful information can be gained about classes of proteins and classes of compounds beyond those resembling validated targets and conventionally druglike ligands. In particular, the method identifies targets that, while not druggable by druglike compounds, may become druggable using compound classes such as macrocycles or other large molecules beyond the rule-of-five limit