Date of Award

Fall 12-17-2019

Document Type

Thesis

Degree Name

Bachelor of Arts (BA)

Honors Designation

yes

Program of Study

Chemistry

Language

English

First Advisor

Dr. Timothy Cardozo

Second Advisor

Dr. Olga Lavinda

Third Advisor

Dr. Jean Gaffney

Abstract

The goal of this project was to investigate the complex mechanism of covalent bonding among different molecules and their targets in a modeling software ICM-Pro. Specifically, it included the identification of fundamental aspects of a covalent bonding mechanism of the Michael addition reaction. Michael addition reaction of electrophilic α, β-unsaturated carbonyl compounds with a nucleophilic cysteine residue in thymidylate synthase, papain, and EGFR tyrosine kinase were examined. Thymidylate synthase and EGFR were chosen because they are important targets in the treatment of various types of cancer. In order to find the most optimal parameters, identification and assessment of the effect of the pre-bonding features such as distance, angle and dihedral angle, which have not previously been exploited, and their accuracy in the refinement of covalent docking simulation results was performed. The validity of results was determined through the comparison of the data obtained through noncovalent, covalent and 4D docking of a set of molecules in a virtual environment to the experimentally determined measures of binding affinity, IC50 and Ki values. The statistical analysis showed no linear relationship between the covalent docking score and any of the aforementioned pre-bonding features equally among binders and nonbinders. One-sided t-test analysis indicated that binders are significantly closer positioned to the cysteine residue in a noncovalent setting than nonbinders (p = 0.0296). Such findings can be further used to analyze the molecules in a docking setting with distance restraints and may contribute to a currently existing computational algorithm in ICM-Pro. The feature additionally can be used for the analysis of large datasets of molecules and can be further incorporated to improve prediction scores for covalent inhibitors screening protocol. Consequently, more accurate elimination of potential false positives and false negatives can lead to breakthroughs in a field of targeted covalent inhibitors.

Comments

The research described in this student thesis was done in the laboratory of Dr. Timothy Cardozo at NYU Langone Health, under the supervision of Dr. Cardozo and Dr. Olga Lavinda, post-doctoral fellow in the Cardozo laboratory. Dr. Cardozo conceived the study and supervised the research. Dr. Lavinda designed the experimental plan and directly supervised the undergraduate student thesis candidate, Yuliya Mazo, in the research execution, including generation of data, analysis of data and drafting of the text of the honors thesis. Dr. Jean Gaffney reviewed the thesis and met the administrative requirements required by Baruch College for the mentors.

Available for download on Wednesday, August 24, 2022

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