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    Natural products offer an important avenue to novel therapeutics against drug-resistant bacteria, viruses, fungi, parasites, and cancer. However, there are numerous hurdles and challenges in discovering such molecules, including antimicrobial peptides (AMPs). While a thorough characterization of AMPs is limited by the amount of material, existing technology, and researcher's expertise, peptide classification is complicated by incomplete information as well as different methods proposed for AMPs from bacteria, plants, and animals. This article describes unified classification schemes for natural AMPs on a common platform: the Antimicrobial Peptide Database (APD; https://aps.unmc.edu). The various criteria for these unified classifications include peptide biological source, biosynthesis machinery, biological activity, amino acid sequence, mechanism of action, and three-dimensional structure. To overcome the problem with a limited number of known 3D structures, a universal peptide classification has also been refined and executed in the APD database. This universal method, based on the spatial connection patterns of polypeptide chains, is independent of peptide source, size, activity, 3D structure, or mechanism of action. It facilitates information registration, naming, exchange, decoding, prediction, and design of novel antimicrobial peptides. Copyright © 2022 Elsevier Inc. All rights reserved.

    Citation

    Guangshun Wang. Unifying the classification of antimicrobial peptides in the antimicrobial peptide database. Methods in enzymology. 2022;663:1-18

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    PMID: 35168785

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