Membranolytic ACPs presented high levels of lysine, leucine, alanine, glycine, isoleucine, and valine (Table ). Some of these residues appear more frequently in αhelical ACPs than in non-anticancer and antimicrobial sequences . Raghava's research group has notably used the different amino acid frequencies and k-mers to develop early machine-learning predictors of anticancer activity . Looking at differences between cell-line selective and non-selective mACPs, we noted that the former group included many more small residues (i.e., alanine, valine). In contrast, the latter contained higher levels of phenylalanine, leucine and positively charged residues such as lysine (Table ). These differences translated into bulkier and more hydrophobic non-selective peptides in terms of global physicochemical properties. However, these observations did not hold across all 11 cancer cell lines (Figure ). Our sequence analyses using the MEME suite and the Optimal String Alignment distance revealed that such characteristics could be reduced to a handful of mACP families (Figures ).