Archived
This content is available here for research, reference, and/or recordkeeping.
Author ORCID Identifier
https://orcid.org/0000-0001-2345-6789
Date Available
8-3-2026
Year of Publication
2026
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
College
Pharmacy
Department/School/Program
Pharmaceutical Sciences
Faculty
Kevin Tidgewell
Faculty
David Feola
Abstract
Natural products remain a rich source of structurally diverse bioactive compounds for drug discovery, particularly for pain therapeutics. However, the chemical complexity of natural product extracts presents significant challenges for the efficient identification and prioritization of bioactive metabolites. This dissertation integrates untargeted LC-MS/MS-based metabolomics, molecular networking, classical natural products chemistry, and neurobiological assays to accelerate the discovery of analgesic lead compounds targeting the emerging pain-associated receptor σ₂R/TMEM97.
An untargeted metabolomics workflow was developed to systematically profile complex biological extracts and guide bioactive compound isolation. High-resolution LC-MS/MS data were analyzed using molecular networking (GNPS/GNPS2) to visualize chemical space, dereplicate known metabolites, and prioritize bioactive fractions. This workflow was applied to both marine cyanobacterial and terrestrial medicinal plant extracts, demonstrating its versatility across diverse natural product sources.
From marine cyanobacteria, the depsipeptide Veraguamide E was isolated and structurally characterized using NMR spectroscopy and high-resolution mass spectrometry. Molecular networking facilitated its identification within a family of related analogs, while functional studies demonstrated modulation of intracellular calcium signaling and neuronal excitability, supporting interaction with σ₂R/TMEM97.
Application of the workflow to Acacia sieberiana enabled the targeted isolation of bioactive alkaloid amides, including piperine and moupinamide. Neurophysiological evaluation using stem cell-derived nociceptors demonstrated that these compounds modulate neuronal excitability while preserving sensory responsiveness under noxious conditions, supporting their potential as non-opioid analgesic leads.
In addition to compound discovery, this work introduces methodological advances in metabolomics-guided natural product research, including optimized LC-MS/MS workflows, data-processing strategies, and a targeted framework for prioritizing privileged molecular scaffolds within complex mixtures.
Collectively, this dissertation demonstrates that integrating metabolomics, molecular networking, and functional validation accelerates the discovery of bioactive natural products. These findings expand the chemical and biological understanding of σ₂R/TMEM97-associated pain modulation and establish a scalable strategy for natural product-based lead discovery from diverse marine and terrestrial sources.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2026.383
Archival?
Archival
Funding Information
This study was supported by the National Institutes of Health's grant (NIH NCCIH/FIC grant R21AT013164) and Center for Pharmaceutical Research and Innovation (CPRI) as part of NIH grant P20GM130456.
Recommended Citation
Mofidi Tabatabaei, Sahar, "METABOLOMICS DRIVEN DISCOVERY OF BIOACTIVE NATURAL PRODUCTS LEADS FROM MARINE AND TERRESTRIAL SOURCES FOR THE DEVELOPMENT OF ANALGESICS" (2026). University of Kentucky Doctoral Dissertations. 856.
https://uknowledge.uky.edu/gradschool_diss/856
Included in
Medicinal and Pharmaceutical Chemistry Commons, Natural Products Chemistry and Pharmacognosy Commons
