Antimicrobial, Antidiabetic, Antioxidant, and Anticoagulant Activities of In Vitro and In Silico.

In the last decade, the urgent need to explore medicinal plants or drug development has increased enormously around the world to overcome numerous health problems. In the present investigation, HPLC indicated the existence of 18 phenolic and flavonoid compounds in the extract. Hesperetin represents the greatest concentration (25,579.57 µg/mL), while other compounds, such as pyro catechol, rutin, gallic acid, chlorogenic acid, naringenin, and quercetin, were recognized in concentrations of 2922.53 µg/mL, 1313.26 µg/mL, 1107.26 µg/mL, 389.09 µg/mL, 156.53 µg/mL, and 97.56 µg/mL, respectively. The well diffusion method documented the antibacterial/antifungal activity of extract against , , , , , and with 35, 33, 32, 25, 23, and 21 mm inhibition zones, respectively, more than the standard antibiotic/antifungal agent. Low values ranging from 7.80 to 15.62 µg/mL of MIC and MBC were recorded for , , and . From the 1- diphenyl-2-picryl hydrazyl (DPPH) assay, promising antioxidant activity was recorded for extract with IC of an 8.97 µg/mL. Moreover, ferric reducing antioxidant power (FRAP) and total antioxidant capacity assays (TAC) confirmed the antioxidant activity of the extract, which was expressed as the ascorbic acid equivalent (AAE) of 366.9 ± 0.2 µg/mg and 102 ± 0.2 µg/mg of extracts, respectively. α-amylase and α-glucosidase inhibition % were determined to express the antidiabetic activity of the extract in vitro, with promising IC value (27.01 µg/mL) for α-amylase compared to that of acarbose (50.93 µg/mL), while IC value of the extract for α-glucosidase was 19.21µg/mL compared to that of acarbose 4.13 µg/mL. Prothrombin time (PT) and activated partial thromboplastin time (APTT) revealed the role of extract as an anticoagulant agent if compared with the activity of heparin. Binding interactions of hesperetin and gallic acid were examined via the Molecular Operating Environment (MOE) Dock software against (PDB ID: 3CLQ), (PDB ID: 7RJC), α-amylase (PDB ID: 4W93), and α-glucosidase (PDB ID: 3TOP). The obtained results shed light on how molecular modeling methods might inhibit the tested compounds, which have the potential to be useful in the treatment of target proteins.