Finally, we analysed the distribution of active versus inactive (Figure ) and hemolytic versus non-hemolytic (Figure ) sequences in the MAP4C chemical space. Similarly to the visualizations of predicted fraction of helical residues and hydrophobic moment, active and inactive or hemolytic and non-hemolytic sequences are spatially separated in a large number of small, local clusters. This finding is particularly interesting as it suggests that nearest neighbor relationships in the MAP4C feature space are sufficient to separate peptide sequences based on their antimicrobial activity and hemolysis. It further provides an explanation to the good performance obtained with the MAP4C SVM, which can leverage the nearest neighbor relationships stored in the MAP4C fingerprint feature space when provided with a custom Jaccard kernel function.