A Multi-Pronged Computational Pipeline for Prioritizing Drug Target Strategies for Latent Tuberculosis.

ABSTRACT: Tuberculosis is one of the deadliest infectious diseases worldwide and the prevalence of latent tuberculosis acts as a huge roadblock in the global effort to eradicate tuberculosis. Most of the currently available anti-tubercular drugs act against the actively replicating form of Mycobacterium tuberculosis (Mtb), and are not effective against the non-replicating dormant form present in latent tuberculosis. With about 30% of the global population harboring latent tuberculosis and the requirement for prolonged treatment duration with the available drugs in such cases, the rate of adherence and successful completion of therapy is low. This necessitates the discovery of new drugs effective against latent tuberculosis. In this work, we have employed a combination of bioinformatics

SUBMITTER: Banerjee U 

PROVIDER: S-EPMC7767875 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature