Machine Learning-Identified Potent Antimicrobial Peptides Against Multidrug-Resistant Bacteria and Skin Infections

URN to cite this document:: urn:nbn:de:bvb:355-epub-782156
DOI to cite this document:: 10.5283/epub.78215

Babuççu, Gizem ; Vavilthota, Nikitha ; Bournez, Colin ; de Boer, Leonie ; Cordfunke, Robert A. ; Nibbering, Peter H. ; van Westen, Gerard J. P. ; Drijfhout, Jan W. ; Zaat, Sebastian A. J. ; Riool, Martijn

License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 26 Nov 2025 06:29

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Abstract

Background: The escalating global crisis of antibiotic resistance necessitates the discovery of novel antimicrobial agents. Antimicrobial peptides (AMPs) represent a promising alternative to combat multidrug-resistant (MDR) pathogens. Because traditional AMP discovery is labour-intensive and costly, machine learning (ML) is applied to identify AMPs effective against MDR bacteria and skin ...