Abstract

Increased numbers of reported cases of Mycobacterium tuberculosis (Mtb) resistance to the generally used antibiotics demand to identify novel therapeutic entities for better control of Tuberculosis. Most of the Structure-based Drug Discovery (SBDD) works reported earlier had screened compounds against a single drug target to avoid any off-target binding and related complications. Because of the development of Multi-Drug Resistant and Extensively Drug-Resistant strains of Mtb and looking into the incurable pathologies, targeting the right drug target with a promising ligand data set will result in effective therapeutics. Simultaneously, traditional knowledge-based drugs have earned little success in developing anti-tuberculosis drugs in recent studies. Combining the right-target approach and traditional herbal knowledge base, this in silico drug discovery study was carried out where 1236 compounds from two plants, traditionally used for TB treatment, Camellia sinensis, Ginkgo biloba along with the antibacterial compounds of DrugBank Database have been screened against Pantothenate synthetase of Mtb, a well-known drug target for anti-TB therapeutics. Through this analytics, Epigallocatechin gallate (EGCG) of Camellia sinensis has been reported through in silico docking studies and subsequent Molecular Dynamics simulation, as a promising anti-TB candidate due to its affinity towards Pantothenate synthetase of Mtb. EGCG was subjected to ADME-Tox studies as well as 3D QSAR analysis for the detection of its drug-like properties and for the determination of IC50 value. The EGCG showed the IC₅₀ value at 1404 nM, which is quite promising for a plant-origin compound. The selected ligand, EGCG, due to its promising affinity towards Pantothenate synthetase of Mtb with high drug-like properties, justifies its selection as a potential anti-tuberculosis compound.

Keywords: Structure-based Drug Discovery (SBDD), In silico, Mtb, Docking, Molecular Dynamics Simulation, QSAR, IC₅₀.

Graphical Abstract