RSM-Based Optimization of Dose Response and Antibacterial Potential of Cannabis sativa (L.) Leaves Using Computational Analysis.

Background: In light of the growing problem of antibiotic resistance, it is imperative to investigate new sources, and plants offer a promising supply of bioactive chemicals. Because of its numerous uses in industry, health, and nutrition as well as its antibacterial qualities, Cannabis sativa (C.sativa) has garnered a lot of study interest. This study sought to determine whether ethanolic extracts from C.sativa leaves have antibacterial properties against six human pathogenic microorganisms. Methodology: The antibacterial activity of C.sativa ethanolic extract was tested against six bacteria according to design of experiments made by Agar diffusion method accompanied by response surface method (RSM) of Minitab 17 software. The different combinations set were, concentration: 5.0, 7.5, and 10.0, pH: 5.0, 6.5, 8.0 and temperature: 35°C, 37.5°C, 40°C. By using RSM, maximum antibacterial activity has been checked for ethanolic extract of C.sativa against six bacteria by choosing three independent variables, temperature, pH, and concentration. In in-Silico studies, homology, threading approach, structure prediction, ligands designing and docking studies was performed against the antimicrobial target sequences for Beta-Lactamase, GABA Receptor, Lipoteichoic Acid, N-Acetylglucosamine (NAG), Peptidoglycan and Topoisomerase-IV through FASTA format from UniProt for structure prediction. Results: The results indicated that the three concentrations were effective against tested bacteria. Moreover, effect of pH caused a significant variation in zone of inhibition. The graphs presented in this study indicate the highest zone of inhibition for plant extract; have been achieved at concentration of 10.0, pH 5.1 and temperature 37.5°C. It shows that by keeping the pH low, antibacterial activity will increase. Through the multiple regression analysis on the experimental data, the fitted regression model for the response variable and the test variable x1, x2, x3 are correlated by the second order polymeric equation. Conclusion: It has been concluded that C.sativa can be considered as an effective drug in curing diseases caused by bacteria. Using the optimized values of temperature and pH analyzed in this experiment.