Academic Journal
Food-derived antimicrobial peptides: advances in sources, mechanisms, structure-activity relationships, and AI-assisted design.
| Τίτλος: | Food-derived antimicrobial peptides: advances in sources, mechanisms, structure-activity relationships, and AI-assisted design. |
|---|---|
| Συγγραφείς: | Zhang Y; College of Food Science and Engineering, Henan University of Technology, Zhengzhou, China. Electronic address: zhangyx268825@126.co., An JL; National Soybean Processing Industry Technology Innovation Center, Beijing Engineering and Technology Research Center of Food Additives, Key Laboratory of Geriatric Nutrition and Health (Beijing Technology and Business University), Ministry of Education, Beijing, China., Li W; Global R&D Innovation Center, Inner Mongolia Mengniu Dairy (Group) Co. Ltd., Hohhot, Inner Mongolia, China; Inner Mongolia Enterprise Key Laboratory of Dairy Nutrition, Health & Safety, China., Xi J; College of Food Science and Engineering, Henan University of Technology, Zhengzhou, China., Liu K; College of Food Science and Engineering, Henan University of Technology, Zhengzhou, China., Li H; National Soybean Processing Industry Technology Innovation Center, Beijing Engineering and Technology Research Center of Food Additives, Key Laboratory of Geriatric Nutrition and Health (Beijing Technology and Business University), Ministry of Education, Beijing, China., Liu X; National Soybean Processing Industry Technology Innovation Center, Beijing Engineering and Technology Research Center of Food Additives, Key Laboratory of Geriatric Nutrition and Health (Beijing Technology and Business University), Ministry of Education, Beijing, China. |
| Πηγή: | Food research international (Ottawa, Ont.) [Food Res Int] 2026 Sep 30; Vol. 240, pp. 119610. Date of Electronic Publication: 2026 Jun 03. |
| Τύπος έκδοσης: | Journal Article; Review |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Published on behalf of the Canadian Institute of Food Science and Technology by Elsevier Applied Science Country of Publication: Canada NLM ID: 9210143 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-7145 (Electronic) Linking ISSN: 09639969 NLM ISO Abbreviation: Food Res Int Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Ottawa, Ontario, Canada : Published on behalf of the Canadian Institute of Food Science and Technology by Elsevier Applied Science, c1992- |
| Ιατρικοί όροι (MeSH): | Antimicrobial Peptides*/chemistry , Antimicrobial Peptides*/pharmacology , Food Preservatives*/pharmacology , Food Preservatives*/chemistry , Artificial Intelligence*, Biofilms/drug effects ; Food Preservation/methods ; Structure-Activity Relationship ; Food Microbiology ; Humans |
| Περίληψη: | The persistent issues of food spoilage caused by microorganisms and the escalating challenge of antimicrobial resistance drive the need for novel, safe, and sustainable preservatives. Food-derived antimicrobial peptides (AMPs) have attracted considerable attention due to their natural origin, multifunctional properties, and low propensity for inducing resistance. This review offers a comprehensive and systematic analysis of food-derived AMPs, encompassing their diverse sources, preparation methods, mechanisms of action, and complex structure-activity relationships. It critically examines how these peptides disrupt microbial membranes, interfere with intracellular functions, modulate immunity, and combat biofilms. Furthermore, the review highlights the transformative role of artificial intelligence (AI) in overcoming the limitations of traditional research and development approaches, detailing AI-driven progress in virtual screening, activity prediction, de novo design, and mechanistic interpretation. Food-derived AMPs thus represent a promising, safe, and sustainable class of preservatives. They act through multiple mechanisms, including membrane disruption, intracellular targeting, immunomodulation, and biofilm inhibition. Their activity is governed by key structural determinants, such as net charge, hydrophobicity, amphipathicity, and specific amino acid residues, which define their structure-activity relationships. The integration of AI significantly accelerates the discovery and rational design of AMPs by deciphering these complex relationships. When combined with experimental methods, AI provides a powerful framework for developing next-generation intelligent preservatives and functional ingredients, thus ultimately enhancing food safety and health. (Copyright © 2026. Published by Elsevier Ltd.) |
| Competing Interests: | Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Contributed Indexing: | Keywords: AI; Antimicrobial peptides; Food preservation; Structure-activity relationship; Sustainable preservatives; Virtual screening |
| Substance Nomenclature: | 0 (Antimicrobial Peptides) 0 (Food Preservatives) |
| Entry Date(s): | Date Created: 20260706 Date Completed: 20260707 Latest Revision: 20260706 |
| Update Code: | 20260707 |
| DOI: | 10.1016/j.foodres.2026.119610 |
| PMID: | 42409550 |
| Βάση Δεδομένων: | MEDLINE |
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