PDZ domains are protein-protein interaction modules that typically bind to short peptide sequences at the carboxyl terminus of target proteins. Proteins containing multiple PDZ domains often bind to different trans-membrane and intracellular proteins, playing a central role as organizers of multimeric complexes. To characterize the rules underlying the binding specificity of different PDZ domains, we have assembled a novel repertoire of random peptides that are displayed at high density at the carboxyl terminus of the capsid D protein of bacteriophage lambda. We have exploited this combinatorial library to determine the peptide binding preference of the seven PDZ domains of human INADL, a multi-PDZ protein that is homologous to the INAD protein of Drosophila melanogaster. This approach has permitted the determination of the consensus ligand for each PDZ domain and the assignment to class I, class II, and to a new specificity class, class IV, characterized by the presence of an acidic residue at the carboxyl-terminal position. Homology modeling and site-directed mutagenesis experiments confirmed the involvement of specific residues at contact positions in determining the domain binding preference. However, these experiments failed to reveal simple rules that would permit the association of the chemical characteristics of any given residue in the peptide binding pocket to the preference for specific amino acid sequences in the ligand peptide. Rather, they suggested that to infer the binding preference of any PDZ domain, it is necessary to simultaneously take into account all contact positions by using computational procedures. For this purpose we extended the SPOT algorithm, originally developed for SH3 domains, to evaluate the probability that any peptide would bind to any given PDZ domain.