Computational Ancestral Gene Resurrection for investigating selectivity mechanisms of Kinases and GPCRs

Diwakar Shukla, University of Illinois at Urbana-Champaign

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Kinases and G-protein coupled receptors (GPCRs) are cell signaling proteins involved in various physiological functions. Small molecules and other allosteric enhancers such as sodium (Na⁺) ions bind to these proteins and modulate their function. The drug and ion binding sites of kinases and GPCRs share a high degree of similarity but different significantly in their selectivity towards same binding partner. Designing selective molecules and elucidating functional mechanisms is a key challenge in the drug discovery pipeline. Since the conformational changes of these proteins occur at long time scales, more powerful computational resource are required to study these complex systems. Computational time on Blue Waters would help us to study such rare biological events at multi-microsecond time scales. Here, we investigate the molecular mechanisms of kinases and GPCRs using molecular dynamics simulation to identify the atomic level details of conformational changes involved in drug and sodium ion binding. In particular, we employ computational ancestral gene resurrection methodology to elucidate the molecular origin of differences in selectivity of modern proteins by studying the ancestral proteins along the evolutionary tree connecting the proteins.