The global escalation of antibiotic-resistant bacteria, intensified by the limited availability of new classes of antibiotics, calls for alternative solutions to be developed (Shore and Coukell, 2016; WHO, n.d.). Antimicrobial peptides (AMPs) are small peptides characterized by a net positive charge and a substantial number of hydrophobic residues. AMPs directly target and insert into the anionic bacterial cell membranes, demonstrating efficacy even against multi-drug resistant (MDR) bacteria and offering promise for treating biofilm-forming wound infections (Browne et al., 2020; Chung et al., 2017).

AMPs interact preferentially with bacteria than with mammalian cells due to differences in biophysical and biochemical properties including net charge and the presence of cholesterol in mammalian cell membranes (Bechinger et al., 2020; Bechinger, 2009; Xhindoli et al., 2016). This results in a relatively high selectivity for bacterial cells. However, this selectivity can come with varying degrees of toxicity—membranous, cellular, and systemic.

While AMPs favor bacterial membranes over eukaryotic ones (Bechinger, 2009; Xhindoli et al., 2016), balancing their efficacy against safety for host cells is challenging during peptide design and pre-clinical studies. Historically, the toxicity of cyclic peptide antibiotics like colistin toward mammalian cells has been an impediment for their clinical application (Nang et al., 2021). Toxic effects can range from local irritation to life-threatening events such as organ failure or death (Nang et al., 2021). The challenge, therefore, lies in optimizing the therapeutic concentration vis-à-vis toxicity levels. Hemolysis, a primary cytotoxicity assessment tool, assesses the AMPs' ability to cause the release of hemoglobin when incubated in a specifically prepared solution of red blood cells (RBCs). Many computational algorithms have been proposed which claim to accurately predict the hemolytic potential of AMP sequences. High hemolytic activity is a significantly negative attribute and informs our go/no-go decision making on the continued pre-clinical development of any one peptide. In this study, we compare computational hemolytic predictors against empirical data and find that they are highly variable and inconsistent with published hemolytic data. We then develop and introduce a streamlined hemolysis assay employing defibrinated human red blood cells. This new assay method is proposed as a standard for evaluating the hemolytic risks of AMPs or other drug candidates.