This study discusses a new approach to aid in exploring and describing the activity landscape of peptides. As a case study, we use an exemplary data set of 165 peptides with reported activity against methicillin-resistant Staphylococcus aureus (MRSA) strains (one of the most important endpoints to developing new drug candidates according to the WHO) , including identifying anti-MRSA peptide activity cliffs. To this end, we employed an atom-connectivity fingerprint recently developed and wellsuited to represent peptides. Finally, we discuss an interpretation of the peptide activity cliffs.