The recognition of small organic compounds and metabolites is essential for living systems, enabling the cell to sense environmental stimuli and respond appropriately. Developing quantitative models of living systems which can incorporate these environmental stimuli would accordingly benefit from comprehensive mapping of interactions between proteins and small molecules of interest. While high-throughput experimental methods provide a wealth of interaction data, the scale of chemical space currently precludes comprehensive enumeration of protein-compound interaction space. Computational methods can help to bridge this gap by inferring proteome-scale protein-compound interactomes, elucidating structural features within protein families which mediate specificity of binding to specific small molecules, and inferring the affinity of binding for specific protein-compound interactions. In this thesis, we attempt to use, and in some cases develop, methods to study protein-compound interactions at these three scales.
First, we describe recent work in extending our structure-based algorithm for predicting protein-compound interactions throughout the proteome to include a wider array of small molecules. We demonstrate that this method performs comparably to existing methods and describe an online database storing the results of this analysis. We also report several case studies illustrating how this database can be used along with cautionary vignettes indicating areas where the method fails and directions for future improvement.
We subsequently analyze druggable pockets occurring within protein-protein interfaces (PPIs) to assess whether they are less structurally conserved than analogous pockets of conventional drug sites. We find that PPI interfacial pockets are associated with fewer expected off-targets than conventional drug sites, however that this finding is specific to individual protein families, rather than a general feature of interfacial PPI pockets. Finally, we use Free Energy Perturbation to predict the binding affinity of an array of small volatile odorants with an olfactory receptor from the jumping bristletail, Machilis hrabei, as well as attempt to further optimize the system in order to study the effects of mutating receptor binding site residues on binding affinity to its active ligands.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/gnd3-mf07 |
| Date | January 2024 |
| Creators | Trudeau, Stephen Joseph |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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