Potential targets in quest for new antitubercular drugs: Implications of computational approaches for end-TB strategy

Abstract

Abstract The emergence of drug-resistant strains of Mycobacterium tuberculosis has encouraged researchers to develop auspicious antitubercular drugs. Novel antitubercular drugs can be developed by identifying diversiform targets in M. tuberculosis. Metabolic processes such as cell wall synthesis, amino acid synthesis, cofactor biosynthesis, mycothiol synthesis, DNA synthesis, and ATP synthesis have been identified as promising targets in M. tuberculosis for developing tuberculosis (TB) drugs. Computational approaches such as molecular modeling and docking strategies have shown tremendous efficacy of the disparate ideal ligands against the selected receptors of M. tuberculosis. Additionally, several TB databases are available that help to identify auspicious ligands for assessing preclinical as well as clinical trials toward antitubercular drug discovery. This chapter not only sheds light on the key targets investigated so far in M. tuberculosis, but also analyzes the prominent role of computational tools toward designing and developing efficacious drugs for TB treatment over the next few decades. Computational approaches and unique databases may help in investigating novel cost-effective antitubercular drugs in a short period and may initiate unique antitubercular strategies.