Molecular Docking Suggests the Targets of Anti-Mycobacterial Natural Products

Tuberculosis (TB) is a major global threat, mostly due to the development of antibiotic-resistant forms of Mycobacterium tuberculosis, the causal agent of the disease. Driven by the pressing need for new anti-mycobacterial agents several natural products (NPs) have been shown to have in vitro activities against M. tuberculosis. The utility of any NP as a drug lead is augmented when the anti-mycobacterial target(s) is unknown. To suggest these, we used a molecular reverse docking approach to predict the interactions of 53 selected anti-mycobacterial NPs against known druggable mycobacterial targets ClpP1P2, DprE1, InhA, KasA, PanK, PknB and Pks13. The docking scores/binding free energies were predicted and calculated using AutoDock Vina along with physicochemical and structural properties of the NPs, using PaDEL descriptors. These were compared to the established inhibitor (control) drugs for each mycobacterial target. The specific interactions of the bisbenzylisoquinoline alkaloids 2-nortiliacorinine, tiliacorine and 13 '-bromotiliacorinine against the targets PknB and DprE1 (-11.4, -10.9 and -9.8 kcal center dot mol(-1); -12.7, -10.9 and -10.3 kcal center dot mol(-1), respectively) and the lignan alpha-cubebin and Pks13 (-11.0 kcal center dot mol(-1)) had significantly superior docking scores compared to controls. Our approach can be used to suggest predicted targets for the NP to be validated experimentally, but these in silico steps are likely to facilitate drug optimization.

Automated summary

In this study, a molecular reverse docking approach was used to predict interactions between 53 selected anti-mycobacterial natural products and known druggable mycobacterial targets. Results showed that certain compounds had significantly higher binding free energies against PknB and DprE1 targets, suggesting their potential use in drug optimization research.