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Antimicrobial peptides (AMPs) were long thought to kill bacteria by a general mechanism; disrupting their membranes leading to cell lysis and death. However, some AMPs are lacking membranolytic activity and act on membrane-associated proteins or cytoplasmic targets. While the global cationic and amphipathic characters of AMPs, most alpha-helical structures, are considered essential to their electrostatic interactions with bacterial and/or eukaryotic membranes, it remains unclear what (local) physicochemical properties favour membranolytic disruption over passive insertion into lipid bilayers. Using a manually curated dataset of 300 (non-)-membranolytic AMPs and 77 physicochemical descriptors, we developed cross-validated binary classifiers including random forest to predict membranolysis with 82-86% accuracies. Our best models were used to discover novel membranolytic AMPs of different source organisms and, designing novel peptide sequences. Some AMPs are being produced and tested to validate our predictions.
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