Molecular Mechanisms of MmpL3 Function and Inhibition

The Mycobacterium tuberculosis MmpL3 inhibitor MSU-43085 is active in a mouse model of infection

IMPORTANCE

MmpL3 is a protein that is required for the survival of bacteria that cause tuberculosis (TB) and nontuberculous mycobacterial (NTM) infections. This report describes the discovery and characterization of a new small molecule, MSU-43085, that targets MmpL3 and is a potent inhibitor of Mycobacterium tuberculosis (Mtb) and M. abscessus survival. MSU-43085 is shown to be orally bioavailable and efficacious in an acute model of Mtb infection. However, the analog is inactive against Mtb in chronically infected mice. Pharmacokinetic and metabolite identification studies identified in vivo metabolism of MSU-43085, leading to a short half-life in treated mice. These proof-of-concept studies will guide further development of the MSU-43085 series for the treatment of TB or NTM infections.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.