Date of Award
1-1-2019
Document Type
Dissertation
Degree Name
Ph.D. in Chemistry
First Advisor
Murrell Godfrey
Second Advisor
James Cizdziel
School
University of Mississippi
Relational Format
dissertation/thesis
Abstract
The object of this dissertation was to use a computational approach to predict and understand new psychoactive substances (NPS) to develop a database for state and federal crime. The primary scope of the dissertation was to better understand the interactions that take place between new psychoactive substances and their corresponding receptors. Through analysis of the interactions between the amino acids within the receptors and the NPS an understanding into the pharmacology and toxicology of these drugs can be gained. NPS such as synthetic cannabinoids fentanyl and its analogs and kratom have become more problematic for both state and federal crime labs as they rush to keep up with new compounds that appear on the drug market for recreational use. NPS pose many issues within the criminal justice field. A main issue is the inability of agencies like the Drug Enforcement Administration (DEA) to keep up with the increasing number of NPS that are used recreationally and have a high potential for abuse. When a new compound surfaces it can take weeks and sometimes months to identify the compound and understand its properties. This project used the molecular modeling software from Schrödinger Maestro to virtually dock NPS of interest to their receptors. Following thorough docking studies of known synthetic cannabinoids possible new structures of synthetic cannabinoids were designed and studied in the same way. This project focused on the specific structural characteristics of these compounds and how those characteristics influence the binding of the ligand to its receptor. Specific residue interactions taking place within the binding pocket of the receptor were also analyzed. This project sets the foundation of a larger project that will lead to a database that can be made available to all state and federal crime laboratories containing potential NPS that will aid in the rapid identification and pharmacological understanding of previously unidentified compounds.
Recommended Citation
Spencer, Caroline Amelia, "A computational approach to predicting and understanding new psychoactive substances (NPS) for developing a database for state and federal crime laboratories" (2019). Electronic Theses and Dissertations. 1787.
https://egrove.olemiss.edu/etd/1787