High-throughput screening of compounds library to identify novel inhibitors against latent Mycobacterium tuberculosis using streptomycin-dependent Mycobacterium tuberculosis 18b strain as a model. (September 2020) - Sharma, Smriti; Bhat, Rahul; Singh, Rohit; Sharma, Sumit; wazir, Priya; Singh, Parvinder Pal; Vishwakarma, Ram A.; Khan, Inshad Ali
Abstract: One of the significant challenges to treat tuberculosis is the phenotypic resistance adapted by the latent or dormant Mycobacterium tuberculosis (M. tuberculosis) cells against most of the available drugs. Different in-vitro assay such as oxygen depletion model and nutrient starvation models have contributed to unravelling the pathogen phenotypic resistance but are too cumbersome for application to high-throughput screening (HTS) assays. In this context, non-replicating streptomycin-starved 18b (SS18b) mutant strain of M. tuberculosis provided a simple and reproducible model. This model mimics latent tuberculosis and is best suited for screening medicinally appropriate libraries. Using SS18b strain in a resazurin reduction microplate assay (REMA), high-throughput screening of ChemDiv library constituting of 30, 000 compounds resulted in the identification of 470 active compounds. Clustering and scaffolding based medicinal chemistry analysis characterized these hits into 15 scaffolds. Seven most potent compounds exhibiting an MIC ≤ 1 μg/ml against SS18b were non-toxic in HepG2 cell line (selective Index ≥ 160). Our screening revealed seven novel compounds exhibiting activity against the non-replicating form of M tuberculosis . 8002–7516 was the most promising compound showing intracellular killing and could be optimized to develop a lead drug candidate. Graphical abstract: Image 1 Highlights: Screening of 30, 000 chemDiv library identified seven novel compounds having activity against SS18b. All compounds were non-toxic on HepG2 cell line. Finally compounds 8002–7516 and 3013–0377 selected for further evaluation. Compound 8002–7516 found to be the most promising that could be optimized to develop as a lead drug candidate.