Identification of a Novel Peptide with Alcohol Dehydrogenase Activating Ability from Ethanol-Induced Lactococcus lactis: A Combined In Silico Prediction and In Vivo Validation
Alcohol dehydrogenase (ADH) is a crucial rate-limiting enzyme in alcohol metabolism. Our previous research found that ethanol-induced intracellular extracts of Lactococcus lactis (L. lactis) could enhance alcohol metabolism in mice, but the responsible compounds remain unidentified. The study aimed...
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Published in | Journal of agricultural and food chemistry Vol. 72; no. 11; pp. 5746 - 5756 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Chemical Society
20.03.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Alcohol dehydrogenase (ADH) is a crucial rate-limiting enzyme in alcohol metabolism. Our previous research found that ethanol-induced intracellular extracts of Lactococcus lactis (L. lactis) could enhance alcohol metabolism in mice, but the responsible compounds remain unidentified. The study aimed to screen potential ADH-activating peptides from ethanol-induced L. lactis using virtual screening and molecular docking calculation. Among them, the pentapeptide FAPEG might bind to ADH through hydrophobic interaction and hydrogen bonds, then enhancing ADH activity. Spectroscopy analysis further investigated the peptide-enzyme interaction between FAPEG and ADH, including changes in the amino acid residue microenvironment and secondary structural alterations. Furthermore, FAPEG could protect against alcoholic liver injury (ALI) in mice by reducing blood alcohol concentration, enhancing the activity of antioxidant and alcohol metabolism enzymes, and attenuating alcohol-induced hepatotoxicity, which was related to the activation of the Nrf2/keap1/HO-1 signaling pathway. The study provided preliminary evidence that the generation of ADH-activating peptides in ethanol-induced L. lactis has the potential in preventing ALI in mice using in silico prediction and in vivo validation approaches. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0021-8561 1520-5118 |
DOI: | 10.1021/acs.jafc.3c07632 |