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Date of Award
5-2025
Document Type
Restricted Thesis: Campus only access
Degree Name
Bachelor of Science
Department
Chemistry
First Advisor
Dr. Kristine Nolin
Abstract
Natural products (NPs) are the cornerstone of traditional and modern pharmaceuticals, yet the process of discovering new bioactive compounds remains largely speculative. To address this, we developed the Nolin Natural Product Collection (NolinNPC), a unified database cataloging plant-derived NPs, their structural characteristics, biological activities, source organisms, extraction methods, and associated diseases or biochemical pathways. The initial stages of the NPC relied on manually curated Excel datasets, but the project has since transitioned to a modular relational database framework supported by R and Python. This structure allows for more rigorous data visualization, analysis, and expansion. Core external resources, including CrossRef, PubChem, and the Global Biodiversity Information Facility (GBIF), are accessed through API integration, streamlining metadata validation and enabling dynamic updates. Compounds are systematically classified according to chemical structure, supporting finer differentiation among novel NPs, while occurrence data linked to source organisms enhances the strategic selection of biodiversity targets. Maintaining many-to-many relational integrity through junction tables ensures flexibility in representing the complex interconnections between compounds, organisms, and biological effects. The NPC is currently undergoing migration to a PostgreSQL environment, with future plans to deploy a web-accessible platform using Django. Future development will also focus on implementing structured data entry pipelines using ChatGPT outputs, enabling standardized and semi-automated database expansion while minimizing human error. Additional goals include local storage of molecular files for compounds not yet cataloged in PubChem and the development of integrated 2D/3D structural visualization tools. By consolidating diverse streams of natural product data into a coherent, expandable platform, the NolinNPC seeks to transform NP discovery into a strategic, data-driven process, significantly accelerating the identification of candidates for therapeutic development.
Recommended Citation
Mershon, Parisa, "NolinNPC: The Natural Products Collection Database" (2025). Honors Theses. 1838.
https://scholarship.richmond.edu/honors-theses/1838
