Distinct binding specificity of the multiple PDZ domains of INADL, a human protein with homology to INAD from Drosophila melanogaster.

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.

iSPOT: a web tool for the analysis and recognition of protein domain specificity.

Methods that aim at predicting interaction partners are very likely to play an important role in the interpretation of genomic information. iSPOT (iSpecificity Prediction Of Target) is a web tool (accessible at http://cbm.bio.uniroma2.it/iSPOT) developed for the prediction of protein-protein interaction mediated by families of peptide recognition modules. iSPOT accesses a database of position specific residue-residue interaction frequencies for members of the SH3 and PDZ protein domain families. The software utilises this database to provide a score for any potential domain peptide interaction.ISPOT: 1. evaluates the likelihood of the interaction between any of the peptides contained in an input protein and a list of domains of the two different families; 2. searches in the SWISS-PROT database for potential partners of a query domain; and 3. has access to a repository of all the domain/target peptide interaction data.

Three-dimensional view of the surface motif associated with the P-loop structure: cis and trans cases of convergent evolution.

Here we identify the determinants of the nucleotide-binding ability associated with the P-loop-containing proteins, inferring their functional importance from their structural convergence to a unique three- dimensional (3D) motif. (1) A new surface 3D pattern is identified for the P-loop nucleotide-binding region, which is more selective than the corresponding sequence pattern; (2) the signature displays one residue that we propose is the determinant for the guanine-binding ability (the residues aligned to ras D119; this residue is known to be important only in the G-proteins, we extend the prediction to all the other P-loop- containing proteins); and (3) two cases of convergent evolution at the molecular level are highlighted in the analysis of the active site: the positive charge aligned to ras K117 and the arginine residues aligned to the GAP arginine finger. The analysis of the residues conserved on protein surfaces allows one to identify new functional or evolutionary relationships among protein structures that would not be detectable by conventional sequence or structure comparison methods.

SH3-SPOT: an algorithm to predict preferred ligands to different members of the SH3 gene family.

We have developed a procedure to predict the peptide binding specificity of an SH3 domain from its sequence. The procedure utilizes information extracted from position-specific contacts derived from six SH3/peptide or SH3/protein complexes of known structure. The framework of SH3/peptide contacts defined on the structure of the complexes is used to build a residue-residue interaction database derived from ligands obtained by panning peptide libraries displayed on filamentous phage. The SH3-specific interaction database is a multidimensional array containing frequencies of position-specific contacts. As input, SH3-SPOT requires the sequence of an SH3 domain and of a query decapeptide ligand. The array, that we call the SH3-specific matrix, is then used to evaluate the probability that the peptide would bind the given SH3 domain. This procedure is fast enough to be applied to the entire protein sequence database. Panning experiments were performed to search putative specific ligands of different SH3 domains in a database of decapeptides, or in a database of protein sequences. The procedure ranked some of the natural partners of interaction of a number of SH3 domains among the best ligands of the approximately 5. 6x10(9) different decapeptides in the SWISSPROT database. We expect the predictive power of the method to increase with the enrichment of the SH3-specific matrix by interaction data derived from new complex structures or from the characterization of new ligands. The procedure was developed using the SH3 domain family as test case but its application can easily be extended to other families of protein domains (such as, SH2, MHC, EH, PDZ, etc.).

Protein surface similarities: a survey of methods to describe and compare protein surfaces.

Many methods have been developed to analyse protein sequences and structures, although less work has been undertaken describing and comparing protein surfaces. Evolution can lead sequences to diverge or structures to change topology; nevertheless, surface determinants that are essential to protein function itself may be mantained. Moreover, different molecules could converge to similar functions by gaining specific surface determinants. In such cases, sequence or structure comparisons are likely to be inadequate in describing or identifying protein functions and evolutionary relationships among proteins. Surface analysis can identify function determinants that are independent of sequence or secondary structure and can therefore be a powerful tool to highlight cases of possible convergent or divergent evolution. This kind of approach can be useful for a better understanding of protein molecular and biochemical mechanisms of catalysis or interaction with a ligand, which are usually surface dependent. Protein surface comparison, when compared to sequence or structure comparison methods, is a hard computational challenge and evaluated methods allowing the comparison of protein surfaces are difficult to find. In this review, we will survey the current knowledge about protein surface similarity and the techniques to detect it.