Date of Award

8-2019

Document Type

Thesis

Degree Name

Master of Science (MS)

College/School

College of Science and Mathematics

Department/Program

Chemistry and Biochemistry

Thesis Sponsor/Dissertation Chair/Project Chair

Nina Goodey

Committee Member

John Siekierka

Committee Member

David Rotella

Committee Member

Saliya Desilva

Subject(s)

Drugs -- Effectiveness, Tetrahydrofolate dehydrogenase

Abstract

In drug discovery, building a comprehensive picture of the binding events between a drug and its enzyme target can be useful, especially in the development of new drugs or predicting the effect of a drug on a similar target from the same protein family. It is well known that a drug's selectivity is influenced by its interactions with amino acid residues within the active site, but contributions from residues situated away from (distal to) the active site are less well understood. Using a novel predictive approach PAnPredictor that employs sequence alignments, we have previously predicted residue positions in the dihydrofolate reductase (DHFR) family that play a role in drug selectivity. Interestingly, while a few of these predicted residues are located within the active site and are known drug specificity determining positions, other residues fall spatially in clusters distal to the active site. We used Bacillus stearothermophilus dihydrofolate reductase (Bs DHFR) to study the effect that introducing amino acid replacements at these predicted clusters has on the drug selectivity profile. Mutations were introduced randomly into each individual cluster and screened for functional DHFR enzymes. We determined kcat and KM values for the mutant enzymes that passed the functional screen to confirm that these mutants are functioning properly. Next, we determined KD values of the mutant enzymes to two common DHFR competitive drugs trimethoprim (TMP), and pyrimethamine (PYR) using fluorescence equilibrium titrations to identify residues where perturbations resulted in altered drug selectivity profiles. These data will help us understand the effect that distal residues have on drug selectivity and inform us on the ability of the predictive tool, PAnPredictor, to successfully identify Bacillus stearothennophilus dihydrofolate reductase determining residue positions in the DHFR enzyme family. If we find the approach successful, we plan to employ PAnPredictor to other protein families in the future.

File Format

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Available for download on Friday, November 20, 2020

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