Abstract

Drug discovery process includes screening of potential compounds to propose as drug and identification of potential targets to be inhibited in order to combat disease prognosis. A combined approach of phytochemistry and bioinformatics is used to deal with drug discovery against antimicrobial resistance by identifying potential targets and candidate drugs. The work includes evaluation of antimicrobial activity of terpenoid-based plant extracts against antibiotic resistant microorganisms. The study was conducted to explain possible new perspective of drug discovery. Phytocompounds from herbal medicinal plants Bacopa monnieri and Andrographis paniculata were employed. Phytochemical tests were performed for both the plants to screen the presence of phytocompounds. Antimicrobial activities of the crude extracts of two medicinal plants (Bacopa monnieri and Andrographis paniculata) were screened. Best reported zone of inhibition observed with Andrographis paniculata was 1.5 cm in Pseudomonas aeruginosa and 1.0 cm in Bacillus subtilis. The least inhibition was shown by Bacopa monnieri, i.e. 0.7 cm in Pseudomonas aeruginosa and 0.6 cm in Bacillus subtilis. In silico analysis of phytochemicals is studied against multidrug resistant (MDR) strains of methicillin resistant Staphylococcus aureus using computer-aided drug discovery. Identification of target proteins was performed using database mining. Subsequently, molecular docking was done to depict the interaction of chosen terpenoid (Bacoside, Bacopa saponin, andrographin and β-sitosterol) against the identified target proteins (PDB entry 2X4K & 2IHY) of MRSA. Andrographin and bacoside has more specificity towards the target protein identified for Staphylococcus aureus. This justifies them as potential compound with antimicrobial property. This study concludes the antimicrobial property of medicinal extracts of Bacopa monnieri and Andrographis paniculata against methicillin resistance Staphylococcus aureus and establishes the interaction of current phytochemicals involved in antimicrobial activity through an in-silico approach to reduce the cost incurred in experimental efforts.

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