COMPUTATIONAL SCREENING OF THE BIOACTIVE METABOLITE 2,6-DIMETHOXYPHENOL FROM SALVADORA PERSICA IDENTIFIED BY GC–MS AGAINST DRUG-RESISTANT ESCHERICHIA COLI AND STAPHYLOCOCCUS AUREUS

Abstract

Background: Antimicrobial resistance has increased the need for new antibacterial candidates from natural sources. Salvadora persica is a medicinal plant with reported antibacterial effects due to its rich phytochemical contents.  Methods: Methanolic extract of S. persica was profiled using GC–MS for identification of bioactive metabolites. 2,6-dimethoxyphenol was chosen for computational analysis, based on its occurrence and reported antimicrobial relevance. The three-dimensional structure of the ligands was obtained from PubChem, whereas the DNA gyrase B structures from Escherichia coli (PDB: 1KZN) and Staphylococcus aureus (PDB: 3G7B) were downloaded from the Protein Data Bank. AutoDock Vina software was used for molecular docking and Discovery Studio Visualizer and PyMOL software was used for structural and interaction analysis. Results: GC–MS analysis revealed a number of metabolites, 2,6-dimethoxyphenol (12.6%) being the highest peak. Molecular docking showed good predicted binding of 2,6-dimethoxyphenol to both bacterial DNA gyrase B targets. The binding affinity of the compound was −5.3 kcal/mol for E. coli GyrB (1KZN) and −4.3 kcal/mol for S. aureus GyrB (3G7B). The ligand was placed in the expected binding sites of both target proteins. Conclusion: These results show that the compound 2,6-dimethoxyphenol is a promising compound that computationally was predicted to be antibacterial and could interact with bacterial DNA gyrase B, which is also known as GyrB. More favorable binding under the applied docking conditions is indicated by the greater predicted affinity towards E. coli GyrB. These computational studies need to be further confirmed in vitro using specific biochemical assays and further antibacterial studies.