Date of Award
Doctor of Philosophy
G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three-dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a practical option for high throughput screening and other experimental approaches during the beginning phases of ligand discovery. In this work, we set out to computationally uncover and understand the binding of a single ligand to GPCRs from several different families. We analyzed the sequences and 3D structures of GPCRs from various families that bind to the same ligand. To conduct the analysis, we used currently available tools as well as newly developed Python scripts. These include MEME for motif search, FATCAT for 3D structural comparison, P2Rank for pocket prediction, APoc for pocket comparison, and our own Python codes for computing overlap scores. Comparison of 3D GPCR structures that bind to the same ligand revealed local 3D structural similarities and the similar regions often overlap with locations of binding pockets. Using Apoc, these pockets were found to be similar based on backbone geometry and side-chain orientation, and they correlate positively with electrostatic properties of the pockets. Moreover, the more similar the pockets, the more likely a ligand binding to the pockets will interact with similar residues, have similar conformations, and produce similar binding affinities across the pockets. These findings can lead to improved protein function inference, drug repurposing, and drug toxicity prediction, which can, in turn, accelerate the development of new therapeutics. Furthermore, the computational workflow and program codes established for this analysis can be developed into a software pipeline for more extensive investigation of GPCR-ligand binding mechanisms.
Received from ProQuest
Kwabena Owusu Dankwah
Dankwah, Kwabena Owusu, "What Makes GPCRs From Different Families Bind To The Same Ligand?" (2022). Open Access Theses & Dissertations. 3664.