Bioinformatic approach for repurposing immunomodulatory drugs for lepromatous leprosy

[[[ Background: ]]] The lepromatous leprosy (LL) disease is caused by Mycobacterium leprae and Mycobacterium lepromatosis which is characterized by inadequate response to treatment, a propensity to drug resistance, and patient disability. We aimed to evaluate current immunomodulatory medicines and their target proteins collectively as a drug repurposing strategy to decipher novel uses for LL. [[[ Methods: ]]] A dataset of human genes associated with LL-immune response was retrieved from public health genomic databases including the Human Genome Epidemiology Navigator and DisGeNET. Retrieved genes were filtered and enriched to set a robust network (≥10, up to 21 edges) and analyzed in the Cytoscape program (v3.9). Drug associations were obtained in the NDEx Integrated Query (v1.3.1) coupled with drug databases such as ChEMBL, BioGRID, and DrugBank. These networks were analyzed in Cytoscape with the CyNDEx-2 plugin and STRING protein network database. [[[ Results: ]]] Pathways analyses resulted in 100 candidate drugs organized into pharmacological groups with similar targets and filtered on 54 different drugs. Gene-target network analysis showed that the main druggable targets associated with LL were tumoral necrosis factor-alpha, interleukin-1B, and interferon-gamma. Consistently, glucosamine, binimetinib, talmapimod, dilmapimod, andrographolide, and VX-702 might have a possible beneficial effect coupled with LL treatment. [[[ Conclusion: ]]] Based on our drug repurposing analysis, immunomodulatory drugs might have a promising potential to be explored further as therapeutic options or to alleviate symptoms in LL patients.