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Membranolytic anticancer peptides (ACPs) are drawing increasing attention as potential future therapeutics against cancer, due to their ability to hinder the development of cellular resistance and their potential to overcome common hurdles of chemotherapy, e.g., side effects and cytotoxicity. In this work, we present an ensemble machine learning model to design potent ACPs. Four counter-propagation...
In article number 1701316, by Gisbert Schneider and co‐workers, a novel peptide descriptor enables the rational design of peptides based on their topological hydrophobic distribution. Applying this descriptor, a computational method generates an innovative peptide inspired by a natural template. This peptide is then trialed and optimized for its ability to disrupt bacterial cells by forming ordered,...
Specific interactions of peptides with lipid membranes are essential for cellular communication and constitute a central aspect of the innate host defense against pathogens. A computational method for generating innovative membrane‐pore‐forming peptides inspired by natural templates is presented. Peptide representation in terms of sequence‐ and topology‐dependent hydrophobic moments is introduced...
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