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• W4224324901 abstract "The current study aimed to evaluate the naturally occurring antimicrobial and antidiabetic potential of various Echium humile (E. humile) solvent extracts (hexane, dichloromethane, ethyl acetate, methanol and aqueous). The bioactive compounds were identified using HPLC-MS, revealing the presence of sixteen phytochemical compounds, with the most abundant being p-coumaric acid, followed by 4,5-di-O-caffeoylquinic acid, trans-ferulic acid and acacetin. Furthermore, E. humile extracts showed marked antimicrobial properties against human pathogen strains, with MIC values for the most relevant extracts (methanol and ethyl acetate) ranging from 0.19 to 6.25 mg/mL and 0.39 to 12.50 mg/mL, respectively. Likewise, methanol was found to be bactericidal towards S. aureus, B. cereus and M. luteus, fungicidal against P. catenulatum and F. oxysporum and have a bacteriostatic/fungicidal effect for the other strains. In addition, the E. humile methanolic extract had the greatest α-glucosidase inhibitory effect (IC50 = 0.06 ± 0.29 mg/mL), which is higher than the standard drug, acarbose (IC50 = 0.80 ± 1.81 mg/mL) and the aqueous extract (IC50 = 0.70 ± 0.67 mg/mL). A correlation study between the major phytochemicals and the evaluated activities was investigated. Docking studies evidenced that most of the identified phenolic compounds showed strong interactions into the binding sites of S. aureus tyrosyl-tRNA synthetase and human lysosomal acid-α-glucosidase, confirming their suitable inhibitory effect. In summary, these results may provide rational support to explore the clinical efficacy of E. humile and its secondary metabolites in the treatment of dual diabetes and infections." @default.
• W4224324901 created "2022-04-26" @default.
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• W4224324901 date "2022-04-21" @default.
• W4224324901 modified "2023-10-06" @default.
• W4224324901 title "Phytochemical Profiling, Antimicrobial and α-Glucosidase Inhibitory Potential of Phenolic-Enriched Extracts of the Aerial Parts from Echium humile Desf.: In Vitro Combined with In Silico Approach" @default.
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• W4224324901 doi "https://doi.org/10.3390/plants11091131" @default.
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