Data-driven Drug Repurposing for Immune System-related Diseases

Authors

Sabyasachi Mohanty, University of Nebraska-LincolnFollow

First Advisor

Tomas Helikar

Committee Members

Massimiliano Pierobon, Toshihiro Obata

Date of this Version

7-2024

Document Type

Thesis

Citation

A thesis presented to the faculty of the Graduate College at the University of Nebraska in partial fulfilment of requirements for the degree of Master of Science

Major: Biochemistry

Under the supervision of Professor Tomas Helikar

Lincoln, Nebraska, July 2024

Comments

Copyright 2024, Sabyasachi Mohanty. Used by permission

Abstract

In this research, we explore a data-driven approach for drug repurposing to enhance the immunomodulatory effect by integrating pattern-based search and genome-scale metabolic modeling. This research helps to find a solution to the preexisting problems of drug discovery which includes expenses and a high amount of time consumption. By leveraging the pre-existing data of the approved drugs to identify the major metabolic pathway changes, we can find new drugs with similar effects with less off-target effects.

The focus on the immune system modulating drugs is due to the high prevalence of immune system-involved diseases and the growing demand for effective treatments to cater to specific conditions. Our approach captures the complex interaction of cellular metabolism and handles the high-dimensional data. The research combines comprehensive data from different databases to build a curated dataset of immunomodulatory drugs. Disease models were built using the COMO pipeline, which can integrate transcriptomic, proteomic, and metabolomic data. The pattern recognition method finds the common off-target effects and metabolic pathway changes in the disease and the effects of the drug.

The results identified high-confidence drugs for repurposing, specifically dimethyl fumarate (DMF), a drug approved for multiple sclerosis that can potentially be used to treat rheumatoid arthritis due to the sharing of common targets. Metformin, a diabetes drug that affects lipid metabolism, can also be repurposed for the treatment of systemic lupus erythematosus.

These repurposed drugs can be effective due to the common targets and mechanisms involved. Similar metabolic flux patterns show the method's potential in repurposing the drugs.

In conclusion, the research contributes to accelerating the process of drug discovery by having the potential to find faster and more cost-effective treatment options and to move toward personalized medicine.

Advisor: Tomas Helikar