MINT: the Molecular INTeraction database

The Molecular INTeraction database (MINT, ) aims at storing, in a structured format, information about molecular interactions (MIs) by extracting experimental details from work published in peer-reviewed journals. At present the MINT team focuses the curation work on physical interactions between proteins. Genetic or computationally inferred interactions are not included in the database. Over the past four years MINT has undergone extensive revision. The new version of MINT is based on a completely remodeled database structure, which offers more efficient data exploration and analysis, and is characterized by entries with a richer annotation. Over the past few years the number of curated physical interactions has soared to over 95 000. The whole dataset can be freely accessed online in both interactive and batch modes through web-based interfaces and an FTP server. MINT now includes, as an integrated addition, HomoMINT, a database of interactions between human proteins inferred from experiments with ortholog proteins in model organisms ()

Progress in Establishing Common Standards for Exchanging Proteomics Data: The Second Meeting of the HUPO Proteomics Standards Initiative

The Proteomics Standards Initiative (PSI) aims to define community standards for data representation in proteomics and to facilitate data comparison, exchange and verification. Rapid progress has been made in the development of common standards for data exchange in the fields of both mass spectrometry and protein–protein interactions since the first PSI meeting [1]. Both hardware and software manufacturers have agreed to work to ensure that a proteomics-specific extension is created for the emerging ASTM mass spectrometry standard and the data model for a proteomics experiment has advanced significantly. The Protein–Protein Interactions (PPI) group expects to publish the Level 1 PSI data exchange format for protein–protein interactions by early summer this year, and discussion as to the additional content of Level 2 has been initiated

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

Broadening the horizon – level 2.5 of the HUPO-PSI format for molecular interactions

BACKGROUND: Molecular interaction Information is a key resource in modern biomedical research. Publicly available data have previously been provided in a broad array of diverse formats, making access to this very difficult. The publication and wide implementation of the Human Proteome Organisation Proteomics Standards Initiative Molecular Interactions (HUPO PSI-MI) format in 2004 was a major step towards the establishment of a single, unified format by which molecular interactions should be presented, but focused purely on protein-protein interactions. RESULTS: The HUPO-PSI has further developed the PSI-MI XML schema to enable the description of interactions between a wider range of molecular types, for example nucleic acids, chemical entities, and molecular complexes. Extensive details about each supported molecular interaction can now be captured, including the biological role of each molecule within that interaction, detailed description of interacting domains, and the kinetic parameters of the interaction. The format is supported by data management and analysis tools and has been adopted by major interaction data providers. Additionally, a simpler, tab-delimited format MITAB2.5 has been developed for the benefit of users who require only minimal information in an easy to access configuration. CONCLUSION: The PSI-MI XML2.5 and MITAB2.5 formats have been jointly developed by interaction data producers and providers from both the academic and commercial sector, and are already widely implemented and well supported by an active development community. PSI-MI XML2.5 enables the description of highly detailed molecular interaction data and facilitates data exchange between databases and users without loss of information. MITAB2.5 is a simpler format appropriate for fast Perl parsing or loading into Microsoft Excel

Comparative genomic approach for protein-protein interaction validation

Currently, a large community effort focuses on protein interaction data as a mean to explore uncharacterized proteins function, discover new pathways and identify potential drug targets. However, the redundant screenings carried out in the past four years in Saccharomyces cerevisae show a very weak overlap and underline the need of protein interaction data validation. Here we propose a new comparative genomic validation approach based on the conservation of binding sequences within orthologs alignments of fifteen closely related yeast species. Taking the 14-3-3 domains as a study case we explore the binding specificities of their ligand peptides taking advantage of mutagenesis analysis carried out by PepSpot experiments. Using these experimental results we create a prediction tool based on regular expression combined with position specific scoring matrix able to screen the full in S. cerevisae proteome and identify putative 14-3-3 domain ligands. The comparative genomic method together with other well established protein interaction validation approaches are benchmarked as filters to increase the accuracy of this prediction. We show that the conservation across several yeast species of 14-3-3 interacting sequences successfully discriminates binding sites from spurious regions matching by chance ligand consensus and increase the prediction accuracy of a four fold. Key words : 14-3-3 domain ; Interaction networks; Protein-Protein interaction Regular expressions, PSSM, protein interaction validation Riassunto : Ad oggi una grande attenzione e’ stata dedicata ai dati di interazioni proteina-proteina che promettono di essere un mezzo molto efficace per la caratterizzazione di proteine a funzione non nota, per la scoperta di nuovi pathways metabolici ed infine per l’identificazione di potenziali bersagli farmaceutici. Ciò nonostante le successive esplorazioni dell’interattoma di Saccharomyces cerevisae pubblicate in questi ultimi anni hanno mostrato una scarsissima sovrapposizione di risultati e sottolineano il bisogno di sistemi di validazione dei dati di interazioni proteiche. In questo lavoro proponiamo un nuovo approccio per questa validazione basato sulla conservazione delle sequenze interagenti in allineamenti di proteine ortologhe derivate dai genomi di quindici specie prossime a S. cerevisae. Prendendo in considerazione le interazioni mediate dai domini 14-3-3 di lievito, abbiamo cominciato la nostra analisi esplorando la loro specificità di legame con esperimenti di mutagenesi effettuati con il metodo di PepSpot. Con questi risultati sperimentali abbiamo creato uno strumento predittivo basato su una espressione regolare e una matrice di punteggi in grado di identificare in tutto il proteoma di lievito le potenziali sequenze leganti i domini 14-3-3. Il nostro metodo di genomica comparativa insieme ad altri approcci comunemente utilizzati per la validazione delle interazioni proteina-proteina sono saggiati per la loro capacità di migliorare l’accuratezza della nostra predizione. In questo lavoro dimostriamo che la conservazione delle sequenze che legano i domini 14-3-3 permette di distinguere chiaramente i veri siti di legame da regioni che per caso contengo il consenso di legame. Infatti il criterio della conservazione migliora di un fattore quattro l’accuratezza della predizione dei ligandi delle proteine contenti domini 14-3-3 in lievito. Parole chiave : domini 14-3-3, reti di interazioni, interazioni proteina-proteina, espressioni regolari, matrice di punteggi, validazione interazioni proteich

The PSI semantic validator: a framework to check MIAPE compliance of proteomics data

The Human Proteome Organization's Proteomics Standards Initiative (PSI) promotes the development of exchange standards to improve data integration and interoperability. PSI specifies the suitable level of detail required when reporting a proteomics experiment (via the Minimum Information About a Proteomics Experiment), and provides extensible markup language (XML) exchange formats and dedicated controlled vocabularies (CVs) that must be combined to generate a standard compliant document. The framework presented here tackles the issue of checking that experimental data reported using a specific format, CVs and public bio-ontologies (e.g. Gene Ontology, NCBI taxonomy) are compliant with the Minimum Information About a Proteomics Experiment recommendations. The semantic validator not only checks the XML syntax but it also enforces rules regarding the use of an ontology class or CV terms by checking that the terms exist in the resource and that they are used in the correct location of a document. Moreover, this framework is extremely fast, even on sizable data files, and flexible, as it can be adapted to any standard by customizing the parameters it requires: an XML Schema Definition, one or more CVs or ontologies, and a mapping file describing in a formal way how the semantic resources and the format are interrelated. As such, the validator provides a general solution to the common problem in data exchange: how to validate the correct usage of a data standard beyond simple XML Schema Definition validation. The framework source code and its various applications can be found at http://psidev.info/validator

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

Inferred Protein Interaction Networks

<div><p>(A) Protein interaction network mediated by the SH3 domains of the proteins characterized in this study. The SH3-containing proteins are represented as blue dots, while the prey partner proteins are represented as black dots. The interactions mediated by each SH3 are represented in a different color, and the edge thicknesses are proportional to the BLU intensity of the corresponding interaction, according to the scale described in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0020014#pbio-0020014-g003" target="_blank">Figure 3</a>.</p> <p>(B) The graph represents the interaction network mediated by the SH3 domains of Rvs167, Ysc84, Yfr024c, Abp1, Myo5, Sho1, Boi1, and Boi2 as determined by the two-hybrid approach (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0020014#pbio-0020014-Tong1" target="_blank">Tong et al. 2002</a>). The interactions (edges) that were confirmed by our WISE method (BLU value higher than 25K) are colored in red or magenta. The interactions in magenta, differently from the ones in red, were not correctly inferred by the phage display approach. The interaction in orange was inferred by the phage display approach, but not confirmed by the WISE method. The network was visualized by the Pajek package (<a href="http://vlado.fmf.uni-lj.si/pub/networks/pajek/" target="_blank">http://vlado.fmf.uni-lj.si/pub/networks/pajek/</a>).</p></div