A Maximum Flow-Based Approach to Prioritize Drugs for Drug Repurposing of Chronic Diseases

Abstract

The discovery of new drugs is required in the time of global aging and increasing populations. Traditional drug development strategies are expensive, time-consuming, and have high risks. Thus, drug repurposing, which treats new/other diseases using existing drugs, has become a very admired tactic. It can also be referred to as the re-investigation of the existing drugs that failed to indicate the usefulness for the new diseases. Previously published literature used maximum flow approaches to identify new drug targets for drug-resistant infectious diseases but not for drug repurposing. Therefore, we are proposing a maximum flow-based protein–protein interactions (PPIs) network analysis approach to identify new drug targets (proteins) from the targets of the FDA (Food and Drug Administration) drugs and their associated drugs for chronic diseases (such as breast cancer, inflammatory bowel disease (IBD), and chronic obstructive pulmonary disease (COPD)) treatment. Experimental results showed that we have successfully turned the drug repurposing into a maximum flow problem. Our top candidates of drug repurposing, Guanidine, Dasatinib, and Phenethyl Isothiocyanate for breast cancer, IBD, and COPD were experimentally validated by other independent research as the potential candidate drugs for these diseases, respectively. This shows the usefulness of the proposed maximum flow approach for drug repurposing.

Informatics on Drug Repurposing for Breast Cancer

“… Captopril, glibenclamide, fluorometholone et al [ 25 ] Copy number variation and aberration data were employed in the development of a network-based integration approach. Ruxolitinib, bromocriptine, deferiprone et al [ 26 ] A maximum flow-based PPI network was constructed and new drug targets were identified from the targets of the FDA drugs and their associated drugs through the network. Guanidine , phenethyl isothiocyanate, caffeine et al [ 27 ] Key hub genes involved in driving neoadjuvant chemotherapy resistance were obtained via gene co-expression network analysis and Multiple Correlation Clustering.…”

“…Ruxolitinib, bromocriptine, deferiprone et al [26] A maximum flow-based PPI network was constructed and new drug targets were identified from the targets of the FDA drugs and their associated drugs through the network.…”

“…Based on this theory, Islam et al constructed a maximum flow-based PPI network through which new drug targets were identified from the targets of the FDA drugs and their associated drugs for chronic disease treatment. 26 Existing drugs were repurposed based on the maximum flow values of each newly identified target protein. The top four repurposed drugs for BC had been reported by other independent studies, demonstrating the feasibility of this framework.…”

Recent Trends in Computational Biomedical Research

“…The paper titled "A Maximum Flow-Based Approach to Prioritize Drugs for Drug Repurposing of Chronic Diseases" is on drug repurposing, i.e., using existing drugs to treat new/other diseases [4]. The work proposes a maximum-flow-based approach using proteinprotein interactions (PPIs) of drug targets (proteins) and risk genes corresponding to chronic diseases such as breast cancer, inflammatory bowel disease (IBD), and chronic obstructive pulmonary disease (COPD).…”