Introduction and Aim: Tuberculosis (TB) is a global health concern, claiming two million lives every year. Although an oldest known human infectious disease, researcher is falling short of giving out an effective and reliable vaccine or therapy. The current antimycobacterial drugs include Isoniazid, Ethambutol, Rifampicin and Pyrazinemamide available in market, but most of these are known to have certain adverse effects. Hence there is an increase in demand for natural products with anti-tuberculosis activity with no or limited side effects. Indian traditional systems of medicine have a plethora of promising plants for treatment of tuberculosis, of which Bergenin is the most well established and extensively used compound. The main aim of this research was to investigate the role of Bergenin as an anti-tuberculosis agent with the help of in-silico analysis and protein interaction studies.
Materials and Methods: In the present study 04 known 3-dimensional crystallized anti-tubercular drug target is considered and retrieved from PDB. Drug Isoniazid, Ethambutol, Rifampicin, Pyrazineamide and phytochemical Bergenin were retrieved, sketched and geometrically optimized. Molecular docking is carried to understand the binding mode and its core interactions. ADMET properties were calculated in assessment of the toxicity. Protein-protein interactions and enrichment analysis is carried out to understand the biological process involved with rpsA protein.
Results: In the present study other than Rifampicin, Bergenin reported with better binding energy and similar pharmacophoric interaction pattern as compared to all the 04 indigenous inhibitors. The PPI network and enrichment analysis predicts the plausible biological process involved with rpsA protein and can be further targeted in treatment of tuberculosis.
Conclusion: The results showed that Bergenin was better than and competent with the existing drugs and can be used as an anti-tuberculosis agent if studied in-vitro and in-vivo for its activity.
Class A β-lactamases and inhibitors: In silico analysis of the binding mode and the relationship with resistance
