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 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.mol-1
; -12.7, -10.9 and -10.3 kcal.mol-1 , respectively) and the lignan αcubebin and Pks13 (-11.0 kcal.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 optimisation.
Computational evaluation of the reactivity and pharmaceutical potential of an organic amine: A DFT, molecular dynamics simulations and molecular docking approach
