AUTHOR=Gorityala Neelima , Baidya Anthony Samit , Sagurthi Someswar R. TITLE=Genome mining of Mycobacterium tuberculosis: targeting SufD as a novel drug candidate through in silico characterization and inhibitor screening JOURNAL=Frontiers in Microbiology VOLUME=15 YEAR=2024 URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2024.1369645 DOI=10.3389/fmicb.2024.1369645 ISSN=1664-302X ABSTRACT=

Tuberculosis (TB) stands as the second most fatal infectious disease globally, causing 1.3 million deaths in 2022. The resurgence of TB and the alarming rise of antibiotic resistance demand urgent call to develop novel antituberculosis drugs. Despite concerted efforts to control TB, the disease persists and spreads rapidly on a global scale. Targeting stress response pathways in Mycobacterium tuberculosis (Mtb) has become imperative to achieve complete eradication. This study employs subtractive genomics to identify and prioritize potential drug targets among the hypothetical proteins of Mtb, focusing on indispensable pathways. Amongst 177 essential hypothetical proteins, 152 were nonhomologous to human. These proteins participated in 34 pathways, and a 20-fold enrichment of SUF pathway genes led to its selection as a target pathway. Fe–S clusters are fundamental, widely distributed protein cofactors involved in vital cellular processes. The survival of Mtb in a hypoxic environment relies on the iron–sulfur (Fe–S) cluster biogenesis pathway for the repair of damaged Fe–S clusters. It also protects pathogen against drugs, ensuring controlled iron utilization and contributing to drug resistance. In Mtb, six proteins of Fe–S cluster assembly pathway are encoded by the suf operon. The present study was focused on SufD because of its role in iron acquisition and prevention of Fenton reaction. The research further delves into the in silico characterization of SufD, utilizing bioinformatics tools for sequence and structure based analysis. The protein’s structural features, including the identification of conserved regions, motifs, and 3D structure prediction enhanced functional annotation. Target based virtual screening of compounds from the ChEMBL database resulted in 12 inhibitors with best binding affinities. Drug likeness and ADMET profiling of potential inhibitors identified promising compounds with favorable drug-like properties. The study also involved cloning in SUMO-pRSF-Duet1 expression vector, overexpression, and purification of recombinant SufD from E. coli BL21 (DE3) cells. Optimization of expression conditions resulted in soluble production, and subsequent purification highlighting the efficacy of the SUMO fusion system for challenging Mtb proteins in E. coli. These findings provide valuable insights into pharmacological targets for future experimental studies, holding promise for the development of targeted therapy against Mtb.