Design, Synthesis and Biological Evaluation of N-phenylindole Derivatives as Pks13 Inhibitors againstMycobacterium tuberculosis

Novel strategies based on natural products and synthetic derivatives to overcome resistance in Mycobacterium tuberculosis

One of the biggest health challenges of today's world is the emergence of antimicrobial resistance (AMR), which renders conventional therapeutics insufficient and urgently demands the generation of novel antimicrobial strategies. Mycobacterium tuberculosis (M. tuberculosis), the pathogen causing tuberculosis (TB), is among the most successful bacteria producing drug-resistant infections. The versatility of M. tuberculosis allows it to evade traditional anti-TB agents through various acquired and intrinsic mechanisms, rendering TB among the leading causes of infectious disease-related mortality. In this context, researchers worldwide focused on establishing novel approaches to address drug resistance in M. tuberculosis, developing diverse alternative treatments with varying effectiveness and in different testing phases. Overviewing the current progress, this paper aims to briefly present the mechanisms involved in M. tuberculosis drug-resistance, further reviewing in more detail the under-development antibiotics, nanotechnological approaches, and natural therapeutic solutions that promise to overcome current treatment limitations.

Unlocking Opportunities for Mycobacterium leprae and Mycobacterium ulcerans

In the recent decade, scientific communities have toiled to tackle the emerging burden of drug-resistant tuberculosis (DR-TB) and rapidly growing opportunistic nontuberculous mycobacteria (NTM). Among these, two neglected mycobacteria species of the Acinetobacter family, Mycobacterium leprae and Mycobacterium ulcerans, are the etiological agents of leprosy and Buruli ulcer infections, respectively, and fall under the broad umbrella of neglected tropical diseases (NTDs). Unfortunately, lackluster drug discovery efforts have been made against these pathogenic bacteria in the recent decade, resulting in the discovery of only a few countable hits and majorly repurposing anti-TB drug candidates such as telacebec (Q203), P218, and TB47 for current therapeutic interventions. Major ignorance in drug candidate identification might aggravate the dramatic consequences of rapidly spreading mycobacterial NTDs in the coming days. Therefore, this Review focuses on an up-to-date account of drug discovery efforts targeting selected druggable targets from both bacilli, including the accompanying challenges that have been identified and are responsible for the slow drug discovery. Furthermore, a succinct discussion of the all-new possibilities that could be alternative solutions to mitigate the neglected mycobacterial NTD burden and subsequently accelerate the drug discovery effort is also included. We anticipate that the state-of-the-art strategies discussed here may attract major attention from the scientific community to navigate and expand the roadmap for the discovery of next-generation therapeutics against these NTDs.

Comprehensive coverage on anti-mycobacterial endeavour reported during 2022

TB being one of the deadliest diseases and second most common infectious cause of deaths, poses the severe threat to global health. The extended duration of therapy owing to resistance and its upsurge in immune-compromised patients have been the driving force for the development of novel of anti-TB scaffolds. Recently, we have compiled the account of anti-mycobacterial scaffolds published during 2015-2020 and updated them in 2021. The present work involves the insights on the anti-mycobacterial scaffolds reported in 2022 with their mechanism of action, structure activity relationships, along with the key perceptions for the design of newer anti-TB agents for the broader interests of medicinal chemists.

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.