In Silico Screening of Natural Compounds as Novel Drug Targets for the Treatment of Multiple Myeloma
Date of Award:
5-2026
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Plants, Soils, and Climate
Committee Chair(s)
Rakesh Kaundal
Committee
Rakesh Kaundal
Committee
John Stevens
Committee
Erin Bobeck
Committee
Matthew D. Robbins
Abstract
Multiple Myeloma (MM) is a blood cancer arising from abnormal plasma cells in the bone marrow, causing severe health complications. Multi-drug resistance (MDR) poses a significant challenge in Multiple Myeloma treatment. Genetic factors and key proteins like transferrin, serpins, TP53, and RAS family members are implicated in MM development and resistance. Natural compounds have exhibited therapeutic potential in various diseases, including cancer. In total, 10 Multiple Myeloma proteins were selected from proteins identified in serum, urine, and bone marrow, as well as RAS mutation proteins and TP53, the well-known drug target for most cancers. Leveraging diverse computational methods such as cheminformatics and systems pharmacology, we conducted an extensive screening of over 118,285 natural compounds from the ZINC database against the MM target proteins. Molecular docking, ADMET prediction, and dynamics simulation were performed to identify promising drug candidates. The top 10 best docked compounds were selected for each MM protein. These compounds were further analyzed for ADMET and compared with existing/known inhibitors/ligands to select best drug candidates. The natural compounds ZINC000085541907, ZINC000085552238, ZINC000150359973, ZINC000001900625, ZINC000150359959, ZINC000006142058 and ZINC000604403935 were found to interact best with MM proteins with inhibitor activity ranging from -15 to -7.5 kcal/mol. Based on these calculations and validation parameters, these selected natural compounds can be used as potential candidates for anti-Multiple Myeloma therapeutics. More research and validation are needed to determine their clinical viability for MM management. Our findings highlight the importance of accurate computational methods in identifying and characterizing the potential natural compounds for treating Multiple Myeloma and advancing cancer therapy. A web-based database was developed using MongoDB, Express, React, NodeJS, HTML5, and Python to house over 40 million compounds generated from comprehensive ligand analyses. This resource enables systematic exploration and prioritization of candidate models, providing a powerful platform for advancing therapeutic discovery and biological insight in Multiple Myeloma.
Recommended Citation
Larson, Rousselene B., "In Silico Screening of Natural Compounds as Novel Drug Targets for the Treatment of Multiple Myeloma" (2026). All Graduate Theses and Dissertations, Fall 2023 to Present. 771.
https://digitalcommons.usu.edu/etd2023/771
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