Date of Award
2022
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Chemistry
First Advisor
Jianin Li
Second Advisor
Severin Schneebeli
Abstract
Computer aided drug design, a collection of computational methodologies including structure and ligand based drug design, has emerged as an efficient and accurate way to expedite the drug discovery process. Structure based drug design — methods which rely on the 3-dimensional structural information of biological targets — are of particular interest to chemists. Unfortunately, structural information can be difficult to obtain, and this can limit the usefulness of these methodologies. New methodologies and workflows, which are less reliant on difficult to obtain structural information are needed to fill in the gaps and push the drug development process forward. The first portion of this dissertation will discuss a novel ensemble docking approach for identifying antagonists of the PAC1R — a class B GPCR which has recently emerged as a potential target for the treatment of chronic pain (migraine) and stress (post-traumatic stress disorder). This approach begins with limited structural information and uses molecular dynamics to build a conformational ensemble of distinct deactivated PAC1R models. A novel aggregate scoring function was also developed to more physically assess the ability of a specific ligand to bind to ensembles. This methodology was designed to be general, and can be applied to other systems. The second portion of this dissertation will discuss the optimization of a small molecule PAC1R antagonist identified by the methodology outlined in the first portion of this dissertation as well as other PAC1R antagonists. This optimization is ongoing, and includes the implementation of free-energy calculations in the AMBER MD package to predict the difference in free-energy of binding (∆∆Gbind) of chemically similar ligands. The third portion of this dissertation will discuss how computer aided design has also been used to investigate and guide the synthesis of biologically relevant materials. Specifically, the use of molecular dynamics simulations to elucidate the mechanism of a size- selective catalytic molecular tetrahedron.
Language
en
Number of Pages
127 p.
Recommended Citation
McKay, Kyle Thomas, "Computer Aided Design: Targeting the PAC1R for Novel Therapeutics and Investigating Biologically Relevant Materials" (2022). Graduate College Dissertations and Theses. 1485.
https://scholarworks.uvm.edu/graddis/1485