Multiple linear regression was used to quantify the dependence of the antimicrobial activity of 13 peptides upon three calculated or experimentally determined parameters: mean hydrophobicity, mean hydrophobic moment, and α‐helix content. Mean hydrophobic moment is a measure of the amphiphilicity of peptides in an α‐helical conformation. Antimicrobial activity was quantified as the reciprocal of the measured minimal inhibitory concentration (MIC) against Escherichia coli. One of the peptides was magainin 2, and the remainder were novel peptides designed for this study. The multiple linear regression results revealed that the amphiphilicity of the peptides was the most important factor governing anti‐microbial activity compared to mean hydrophobicity orα‐helix content. A better regression cf the data was obtained using In(1/MIC + constant) as the dependent variable than with either 1/MIC or In(1/MIC). These results should be useful in designing peptides with higher antimicrobial activity. © 1995 Wiley‐Liss, Inc.