Supporting data for "Mycobacterial Metabolic Model Development for Drug Target Identification"

Antibiotic resistance is increasing at an alarming rate, and three related mycobacteria are the source of widespread infections in humans. According to the World Health Organization, <i>Mycobacterium leprae</i>, which causes leprosy, is still endemic in tropical countries; <i>Mycobacterium tuberculosis</i> is the second-largest infectious disease killer worldwide after COVID-19; <i>Mycobacteroides abscessus</i>, a group of non-tuberculous mycobacteria, causes lung infections and other health-care-associated infections in humans. Due to the rise in resistance to common antibacterial drugs, it is critical to develop alternatives to traditional treatment procedures. Furthermore, an understanding of the biochemical mechanisms underlying pathogenic evolution is important for the treatment and management of these diseased conditions. <br>To this end, we have developed metabolic models of two bacterial pathogens, <i>M. leprae</i>, and <em></em><i>M. abscessus</i>, and used a new computational tool to identify potential drug targets, which we refer to as bottleneck reactions. We highlight the genes, reactions, and pathways in each of these organisms and potential drug targets which can be further explored as broad-spectrum antibacterials. The unique drug targets to each pathogen are significant for precision medicine initiatives. <br>The models and associating datasets are available in GigaDB and the following repositories: <i>M. abscessus</i>: Biomodels &amp; PatMeDB, <i>M. leprae</i>: Biomodels &amp; PatMeDB