Molecular modeling of a series of dehydroquinate dehydratase type II inhibitors of Mycobacterium tuberculosis and design of new binders

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.

In Silico Study, Physicochemical, and In Vitro Lipase Inhibitory Activity of α,β-Amyrenone Inclusion Complexes with Cyclodextrins

α,β-amyrenone (ABAME) is a triterpene derivative with many biological activities; however, its potential pharmacological use is hindered by its low solubility in water. In this context, the present work aimed to develop inclusion complexes (ICs) of ABAME with γ- and β-cyclodextrins (CD), which were systematically characterized through molecular modeling studies as well as FTIR, XRD, DSC, TGA, and SEM analyses. In vitro analyses of lipase activity were performed to evaluate possible anti-obesity properties. Molecular modeling studies indicated that the CD:ABAME ICs prepared at a 2:1 molar ratio would be more stable to the complexation process than those prepared at a 1:1 molar ratio. The physicochemical characterization showed strong evidence that corroborates with the in silico results, and the formation of ICs with CD was capable of inducing changes in ABAME physicochemical properties. ICs was shown to be a stronger inhibitor of lipase activity than Orlistat and to potentiate the inhibitory effects of ABAME on porcine pancreatic enzymes. In conclusion, a new pharmaceutical preparation with potentially improved physicochemical characteristics and inhibitory activity toward lipases was developed in this study, which could prove to be a promising ingredient for future formulations.