The Mycobacterium tuberculosis drugome and its polypharmacological implications

Area of Science:

• Computational drug discovery
• Structural bioinformatics
• Systems biology

Background:

• Tuberculosis (TB) remains a widespread infectious disease, necessitating novel therapeutic strategies.
• Existing drug discovery pipelines face challenges in identifying effective treatments.

Purpose of the Study:

• To develop a computational approach for constructing a large-scale drug-target network.
• To identify potential drug repurposing candidates and novel drug targets for Mycobacterium tuberculosis (M.tb).

Main Methods:

• Integration of structural bioinformatics, molecular modeling, and systems biology.
• Application to the M.tb genome to create the 'TB-drugome' network.
• Analysis of approved drugs and their interactions with M.tb receptors.

Main Results:

• The TB-drugome identified approximately one-third of examined drugs as potential candidates for TB treatment repurposing.
• Numerous unexploited M.tb receptors were found to be druggable, suggesting novel anti-tubercular targets.
• Drug-target networks were confirmed to be modular, with randomness attributed to biased target coverage.

Conclusions:

• The TB-drugome is a valuable resource for developing new anti-TB drugs.
• The computational methodology can be extended to other pathogens.
• Findings provide insights into the structure and properties of drug-target networks.