Publication Date
Fall 2020
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Chemistry
Advisor
Ningkun Wang
Subject Areas
Biochemistry; Chemistry; Computational chemistry
Abstract
SIRT1 is a mammalian NAD+-dependent lysine deacetylase involved in the regulation of physiological processes. Sirtuin-activating compounds (STACs) such as resveratrol bind to the allosteric site within the N-terminal domain (NTD) to regulate activity. Understanding these allosteric effects on SIRT1 would provide insights into drug design to modulate SIRT1-dependent deacetylation on specific substrates. The overall goal of this research is to identify key residues that are involved in allosteric activation of the enzyme, also known as an allosteric switch-like region. Using computational methods based on the primary sequence of SIRT1, we identified residues 186-193 to have a propensity to exhibit switch-like behavior, and we constructed mutants that were predicted to abolish this propensity. This involved clustering secondary structures assigned from coordinates of X-ray structures inclusive of homologues (98% identity or greater) as well as calculating, from sequence at each residue position, the variability (Vkabat) of an ensemble of secondary structure predictions, the sequence entropy and the Lobanov-Galzitskaya disorder propensity. To confirm the switch-like predictions, we studied the enzyme kinetics of the wild-type and mutant constructs on a known substrate, the results of which suggest that the 190-193 region would likely contain a switch-like region. Additional predictions by the cluster analysis approach pinpointed a possible switch-like residue at 193 within this region. The results of this study will provide a novel target site for controlling the regulation of SIRT1 activity as a therapeutic approach.
Recommended Citation
Huynh, Angelina, "Identifying Key Residues Involved in Allosteric Regulation of Human SIRT1 Deacetylation Activity" (2020). Master's Theses. 5148.
DOI: https://doi.org/10.31979/etd.yttn-af3v
https://scholarworks.sjsu.edu/etd_theses/5148
