Bioinformatics and omics revolutionizing leprosy research: Unveiling mechanisms and driving therapeutic innovations

Abstract

The integration of bioinformatics and omics technologies has revolutionized leprosy research, providing insights into Mycobacterium leprae (M. leprae) biology. In this context, the present review analyzes two decades (2001–2021) of research using computational approaches to elucidate molecular mechanisms, identify biomarkers, and support drug discovery for leprosy. The search was conducted in the Web of Science database and found 30 studies, of which 23 met the inclusion criteria with a focus on genomic, proteomic and immunoinformatics applications targeting leprosy. Key advances include the identification of unique antigenic proteins, prediction of drug resistance mechanisms, and the development of in silico tools for diagnostics and therapeutic targeting. Comparative genomic studies have identified genes unique to M. leprae, such as ML2613, that may serve as potential therapeutic targets. Furthermore, bioinformatics has been used to identify biomarkers such as the recombinant antigen rMLP15, which has been shown to be effective in the diagnosis and differentiation between paucibacillary and multibacillary patients. Therefore, the present study highlights the role of bioinformatics in driving innovation for leprosy and underscores the need for continued investment in computational approaches to improve diagnostics and treatment strategies.

Keywords

• Bioinformatics
• In silico characterization
• Leprosy
• Mycobacterium leprae
• Therapeutic and diagnostic purposes