The information contents in previously published peptide sets was compared with smaller sets of peptides selected according to statistical designs. It was found that minimum analogue peptide sets (MAPS) constructed by factorial or fractional factorial designs in physicochemical properties contained substantial structure-activity information. Although five to six times smaller than the originally published peptide sets the MAPS resulted in QSAR models able to predict biological activity. The QSARs derived from a MAPS of nine dipeptides, and from a set of 58 dipeptides inhibiting angiotensin converting enzyme were compared and found to be of equal strength. Furthermore, for a set of bitter tasting dipeptides it was found that an incomplete MAPS of 10 dipeptides gave just as good a model as the model based on a set of 48 dipeptides. By comparison other non-designed sets of peptides gave QSARs with poor predictive power. It was also demonstrated how MAPS centered on a lead peptide can be constructed as to specifically explore the physicochemical and biological properties in the vicinity of the lead. It was concluded that small information-rich peptide sets MAPS can be constructed on the basis of statistical designs with principal properties of amino acids as design variables.