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This Preface introduces the content of the BioMed Central journal Supplements related to BITS2014 meeting, held in Rome, Italy, from the 26th to the 28th of February, 2014.

RNA alignment is an important step in the annotation and characterization of unknown RNAs, and several methods have been developed to meet the need of fast and accurate alignments. Being the performances of the aligning methods affected by the input RNA features, finding the most suitable method is not trivial. Indeed, no available method clearly outperforms the others. Here we present a simple workflow to help choosing the more suitable method for RNA pairwise alignment. We tested the performances of six algorithms, based on different approaches, on datasets created by merging publicly available datasets of known or curated RNA secondary structure annotations with datasets of curated RNA alignments. Then, we simulated the frequent case where the secondary structure is unknown by using the same alignment datasets but ignoring the known structure and instead predicting it. In conclusion, the proposed workflow for pairwise RNA alignment depends on the input RNA primary sequence identity and the availability of reliable secondary structures.

Phosphate plays a chemically unique role in shaping cellular signaling of all current living systems, especially eukaryotes. Protein phosphorylation has been studied at several levels, from the near-site context, both in sequence and structure, to the crowded cellular environment, and ultimately to the systems-level perspective. Despite the tremendous advances in mass spectrometry and efforts dedicated to the development of ad hoc highly sophisticated methods, phosphorylation site inference and associated kinase identification are still unresolved problems in kinome biology. The sequence and structure of the substrate near-site context are not sufficient alone to model the in vivo phosphorylation rules, and they should be integrated with orthogonal information in all possible applications. Here we provide an overview of the different contexts that contribute to protein phosphorylation, discussing their potential impact in phosphorylation site annotation and in predicting kinase-substrate specificity.

Phosphorylation is a widespread post-translational modification that modulates the function of a large number of proteins. Here we show that a significant proportion of all the domains in the human proteome is significantly enriched or depleted in phosphorylation events. A substantial improvement in phosphosites prediction is achieved by leveraging this observation, which has not been tapped by existing methods. Phosphorylation sites are often not shared between multiple occurrences of the same domain in the proteome, even when the phosphoacceptor residue is conserved. This is partly because of different functional constraints acting on the same domain in different protein contexts. Moreover, by augmenting domain alignments with structural information, we were able to provide direct evidence that phosphosites in protein-protein interfaces need not be positionally conserved, likely because they can modulate interactions simply by sitting in the same general surface area., (© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.)

Leishmania are obligatory intracellular parasitic protozoa that cause a wide range of diseases in humans, cycling between extracellular promastigotes in the mid-gut of sand flies and intracellular amastigotes in the phagolysosomes of mammalian macrophages. Although many of the molecular mechanisms of development inside macrophages remain a mystery, the development of a host-free system that simulates phagolysosome conditions (37 °C and pH 5.5) has provided new insights into these processes. The time course of promastigote-to-amastigote differentiation can be divided into four morphologically distinct phases: I, signal perception (0-5 h after exposure); II, movement cessation and aggregation (5-10 h); III, amastigote morphogenesis (10-24 h); and IV, maturation (24-120 h). Transcriptomic and proteomic analyses have indicated that differentiation is a coordinated process that results in adaptation to life inside phagolysosomes. Recent phosphoproteomic analysis revealed extensive differences in phosphorylation between promastigotes and amastigotes and identified stage-specific phosphorylation motifs. We hypothesized that the differentiation signal activates a phosphorylation pathway that initiates Leishmania transformation, and here we used isobaric tags for relative and absolute quantitation to interrogate the dynamics of changes in the phosphorylation profile during Leishmania donovani promastigote-to-amastigote differentiation. Analysis of 163 phosphopeptides (from 106 proteins) revealed six distinct kinetic profiles; with increases in phosphorylation predominated during phases I and III, whereas phases II and IV were characterized by greater dephosphorylation. Several proteins (including a protein kinase) were phosphorylated in phase I after exposure to the complete differentiation signal (i.e. signal-specific; 37 °C and pH 5.5), but not after either of the physical parameters separately. Several other protein kinases (including regulatory subunits) and phosphatases also showed changes in phosphorylation during differentiation. This work constitutes the first genome-scale interrogation of phosphorylation dynamics in a parasitic protozoa, revealing the outline of a signaling pathway during Leishmania differentiation. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (identifier PXD000671). Data can be viewed using ProteinPilot™ software., (© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.)

The central role of kinases in virtually all signal transduction networks is the driving motivation for the development of compounds modulating their activity. ATP-mimetic inhibitors are essential tools for elucidating signaling pathways and are emerging as promising therapeutic agents. However, off-target ligand binding and complex and sometimes unexpected kinase/inhibitor relationships can occur for seemingly unrelated kinases, stressing that computational approaches are needed for learning the interaction determinants and for the inference of the effect of small compounds on a given kinase. Recently published high-throughput profiling studies assessed the effects of thousands of small compound inhibitors, covering a substantial portion of the kinome. This wealth of data paved the road for computational resources and methods that can offer a major contribution in understanding the reasons of the inhibition, helping in the rational design of more specific molecules, in the in silico prediction of inhibition for those neglected kinases for which no systematic analysis has been carried yet, in the selection of novel inhibitors with desired selectivity, and offering novel avenues of personalized therapies.

Structural information is crucial in ribonucleic acid (RNA) analysis and functional annotation; nevertheless, how to include such structural data is still a debated problem. Dot-bracket notation is the most common and simple representation for RNA secondary structures but its simplicity leads also to ambiguity requiring further processing steps to dissolve. Here we present BEAR (Brand nEw Alphabet for RNA), a new context-aware structural encoding represented by a string of characters. Each character in BEAR encodes for a specific secondary structure element (loop, stem, bulge and internal loop) with specific length. Furthermore, exploiting this informative and yet simple encoding in multiple alignments of related RNAs, we captured how much structural variation is tolerated in RNA families and convert it into transition rates among secondary structure elements. This allowed us to compute a substitution matrix for secondary structure elements called MBR (Matrix of BEAR-encoded RNA secondary structures), of which we tested the ability in aligning RNA secondary structures. We propose BEAR and the MBR as powerful resources for the RNA secondary structure analysis, comparison and classification, motif finding and phylogeny., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The use of high-throughput RNA sequencing technology (RNA-seq) allows whole transcriptome analysis, providing an unbiased and unabridged view of alternative transcript expression. Coupling splicing variant-specific expression with its functional inference is still an open and difficult issue for which we created the DataBase of Alternative Transcripts Expression (DBATE), a web-based repository storing expression values and functional annotation of alternative splicing variants. We processed 13 large RNA-seq panels from human healthy tissues and in disease conditions, reporting expression levels and functional annotations gathered and integrated from different sources for each splicing variant, using a variant-specific annotation transfer pipeline. The possibility to perform complex queries by cross-referencing different functional annotations permits the retrieval of desired subsets of splicing variant expression values that can be visualized in several ways, from simple to more informative. DBATE is intended as a novel tool to help appreciate how, and possibly why, the transcriptome expression is shaped. DATABASE URL: http://bioinformatica.uniroma2.it/DBATE/.

Protists of the genus Leishmania are obligatory intracellular parasites that cause a wide range of cutaneous, mucocutaneous, and visceral diseases in humans. They cycle between phagolysosomes of mammalian macrophages and the sand fly midgut, proliferating as intracellular amastigotes and extracellular promastigotes, respectively. Exposure to a lysosomal environment, i.e. acidic pH and body temperature, signals promastigotes to differentiate into amastigotes. Time course analyses indicated that Leishmania differentiation is a highly regulated and coordinated process. However, the role of posttranslational events such as protein phosphorylation in this process is still unknown. Herein, we analyzed and compared the phosphoproteomes of L. donovani amastigotes and promastigotes using an axenic host-free system that simulates parasite differentiation. Shotgun phosphopeptide analysis revealed 1614 phosphorylation residues (p-sites) corresponding to 627 proteins. The analysis indicated that the majority of the p-sites are stage-specific. Serine phosphorylation in a previously identified trypanosomatid-specific "SF" motif was significantly enriched in amastigotes. We identified a few phosophotyrosines (pY), mostly in proteins known to participate in signal transduction pathways. The analysis indicated that Leishmania contains proteins with multiple p-sites that are phosphorylated at distinct stages of the life cycle. For over half of the phosphorylation events, changes in phosphoprotein abundance did not positively correlate with changes in protein abundance, suggesting functional regulation. This study compares, for the first time, the phosphoproteins of L. donovani axenic promastigotes and amastigotes and provides the largest data set of the Leishmania phosphoproteome to date.

Nucleos is a web server for the identification of nucleotide-binding sites in protein structures. Nucleos compares the structure of a query protein against a set of known template 3D binding sites representing nucleotide modules, namely the nucleobase, carbohydrate and phosphate. Structural features, clustering and conservation are used to filter and score the predictions. The predicted nucleotide modules are then joined to build whole nucleotide-binding sites, which are ranked by their score. The server takes as input either the PDB code of the query protein structure or a user-submitted structure in PDB format. The output of Nucleos is composed of ranked lists of predicted nucleotide-binding sites divided by nucleotide type (e.g. ATP-like). For each ranked prediction, Nucleos provides detailed information about the score, the template structure and the structural match for each nucleotide module composing the nucleotide-binding site. The predictions on the query structure and the template-binding sites can be viewed directly on the web through a graphical applet. In 98% of the cases, the modules composing correct predictions belong to proteins with no homology relationship between each other, meaning that the identification of brand-new nucleotide-binding sites is possible using information from non-homologous proteins. Nucleos is available at http://nucleos.bio.uniroma2.it/nucleos/.

The webPDBinder (http://pdbinder.bio.uniroma2.it/PDBinder) is a web server for the identification of small ligand-binding sites in a protein structure. webPDBinder searches a protein structure against a library of known binding sites and a collection of control non-binding pockets. The number of similarities identified with the residues in the two sets is then used to derive a propensity value for each residue of the query protein associated to the likelihood that the residue is part of a ligand binding site. The predicted binding residues can be further refined using conservation scores derived from the multiple alignment of the PFAM protein family. webPDBinder correctly identifies residues belonging to the binding site in 77% of the cases and is able to identify binding pockets starting from holo or apo structures with comparable performances. This is important for all the real world cases where the query protein has been crystallized without a ligand and is also difficult to obtain clear similarities with bound pockets from holo pocket libraries. The input is either a PDB code or a user-submitted structure. The output is a list of predicted binding pocket residues with propensity and conservation values both in text and graphical format.

Trypanosomatid parasites of the genus Leishmania cause severe human diseases collectively termed leishmaniasis. Parasite ATP-binding proteins have emerged as potent targets for chemotherapeutic intervention. However, many parasite-specific ATP-binding proteins may escape current efforts in drug target identification, validation and deconvolution due to the lack of sequence conservation and functional annotation of these proteins in early branching eukaryotic trypanosomatids. Here, we selectively enriched for ATP-binding proteins from Leishmania donovani axenic promastigote and amastigote total protein extracts utilizing a Capture Compound™ (CC) linked to the ATP-competitive inhibitor staurosporine. As judged by in-gel kinase activity assay and competitive inhibition with free staurosporine, the CC specifically enriched for parasite phosphotransferases. Comparative nanoLC-MS(n) analysis identified 70 captured proteins, including 24 conserved protein kinases, and 32 hypothetical proteins with potential ATP-binding function. We identified conserved signature sequence motifs characteristic for staurosporine-binding protein kinases, and identified the hypothetical proteins LinJ.20.0280 and LinJ.09.1630 as novel ATP-binding proteins. Thus, functional enrichment procedures such as described here, combined with bio-informatics analyses and activity assays, provide powerful tools for the discovery of parasite-specific ATP-binding proteins that escape homology-based identification, which can be subsequently targeted for pharmacological intervention., Biological Significance: Functional enrichment using a Capture Compound™ linked to the ATP-competitive inhibitor staurosporine provides a powerful new tool for the discovery of parasite-specific ATP-binding proteins that escape homology-based identification, which can be subsequently targeted for pharmacological intervention., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Background: Anecdotal evidence of the involvement of alternative splicing (AS) in the regulation of protein-protein interactions has been reported by several studies. AS events have been shown to significantly occur in regions where a protein interaction domain or a short linear motif is present. Several AS variants show partial or complete loss of interface residues, suggesting that AS can play a major role in the interaction regulation by selectively targeting the protein binding sites. In the present study we performed a statistical analysis of the alternative splicing of a non-redundant dataset of human protein-protein interfaces known at molecular level to determine the importance of this way of modulation of protein-protein interactions through AS., Results: Using a Cochran-Mantel-Haenszel chi-square test we demonstrated that the alternative splicing-mediated partial removal of both heterodimeric and homodimeric binding sites occurs at lower frequencies than expected, and this holds true even if we consider only those isoforms whose sequence is less different from that of the canonical protein and which therefore allow to selectively regulate functional regions of the protein. On the other hand, large removals of the binding site are not significantly prevented, possibly because they are associated to drastic structural changes of the protein. The observed protection of the binding sites from AS is not preferentially directed towards putative hot spot interface residues, and is widespread to all protein functional classes., Conclusions: Our findings indicate that protein-protein binding sites are generally protected from alternative splicing-mediated partial removals. However, some cases in which the binding site is selectively removed exist, and here we discuss one of them.

External cues are processed and integrated by signal transduction networks that drive appropriate cellular responses. Characterizing these programs, as well as how their deregulation leads to disease, is crucial for our understanding of cell biology. The past ten years have witnessed a gradual increase in the number of molecular parameters that can be simultaneously measured in a sample. Moreover our capacity to handle multiple samples in parallel has expanded, thus allowing a deeper profiling of cellular states under diverse experimental conditions. These technological advances have been complemented by the development of computational methods aimed at mining, analyzing and modeling these data. In this review we give a general overview of the most important experimental and computational techniques used in the field and describe several interesting application of these methodologies. We conclude by highlighting the issues that we think will keep researchers in the field busy in the next few years., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The BITS2012 meeting, held in Catania on May 2-4, 2012, brought together almost 100 Italian researchers working in the field of Bioinformatics, as well as students in the same or related disciplines. About 90 original research works were presented either as oral communication or as posters, representing a landscape of Italian current research in bioinformatics. This preface provides a brief overview of the meeting and introduces the manuscripts that were accepted for publication in this supplement, after a strict and careful peer-review by an International board of referees.

Fragile X syndrome (FXS), the leading cause of inherited intellectual disability, is caused by epigenetic silencing of the FMR1 gene, through expansion and methylation of a CGG triplet repeat (methylated full mutation). An antisense transcript (FMR1-AS1), starting from both promoter and intron 2 of the FMR1 gene, was demonstrated in transcriptionally active alleles, but not in silent FXS alleles. Moreover, a DNA methylation boundary, which is lost in FXS, was recently identified upstream of the FMR1 gene. Several nuclear proteins bind to this region, like the insulator protein CTCF. Here we demonstrate for the first time that rare unmethylated full mutation (UFM) alleles present the same boundary described in wild type (WT) alleles and that CTCF binds to this region, as well as to the FMR1 gene promoter, exon 1 and intron 2 binding sites. Contrariwise, DNA methylation prevents CTCF binding to FXS alleles. Drug-induced CpGs demethylation does not restore this binding. CTCF knock-down experiments clearly established that CTCF does not act as insulator at the active FMR1 locus, despite the presence of a CGG expansion. CTCF depletion induces heterochromatinic histone configuration of the FMR1 locus and results in reduction of FMR1 transcription, which however is not accompanied by spreading of DNA methylation towards the FMR1 promoter. CTCF depletion is also associated with FMR1-AS1 mRNA reduction. Antisense RNA, like sense transcript, is upregulated in UFM and absent in FXS cells and its splicing is correlated to that of the FMR1-mRNA. We conclude that CTCF has a complex role in regulating FMR1 expression, probably through the organization of chromatin loops between sense/antisense transcriptional regulatory regions, as suggested by bioinformatics analysis., Competing Interests: The authors have declared that no competing interests exist.

The SPla/Ryanodine receptor (SPRY)/B30.2 domain is one of the most common folds in higher eukaryotes. The human genome encodes 103 SPRY/B30.2 domains, several of which are involved in the immune response. Approximately 45% of human SPRY/B30.2-containing proteins are E3 ligases. The role and function of the majority of SPRY/B30.2 domains are still poorly understood, however, in several cases mutations in this domain have been linked to congenital disorders. The recent characterization of SPRY/B30.2-mediated protein interactions has provided evidence for a role of this domain as an adaptor module to assemble macromolecular complexes, analogous to Src homology (SH)2, SH3, and WW domains. However, functional and structural evidence suggests that SPRY/B30.2 is a more versatile fold, allowing a wide range of binding modes., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Leishmania are obligatory intracellular parasitic protozoa that cycle between sand fly mid-gut and phagolysosomes of mammalian macrophages. They have developed genetically programmed changes in gene and protein expression that enable rapid optimization of cell function according to vector and host environments. During the last two decades, host-free systems that mimic intra-lysosomal environments have been devised in which promastigotes differentiate into amastigotes axenically. These cultures have facilitated detailed investigation of the molecular mechanisms underlying Leishmania development inside its host. Axenic promastigotes and amastigotes have been subjected to transcriptome and proteomic analyses. Development had appeared somewhat variable but was revealed by proteomics to be strictly coordinated and regulated. Here we summarize the current understanding of Leishmania promastigote to amastigote differentiation, highlighting the data generated by proteomics.

Various post-translational modifications (PTMs) fine-tune the functions of almost all eukaryotic proteins, and co-regulation of different types of PTMs has been shown within and between a number of proteins. Aiming at a more global view of the interplay between PTM types, we collected modifications for 13 frequent PTM types in 8 eukaryotes, compared their speed of evolution and developed a method for measuring PTM co-evolution within proteins based on the co-occurrence of sites across eukaryotes. As many sites are still to be discovered, this is a considerable underestimate, yet, assuming that most co-evolving PTMs are functionally associated, we found that PTM types are vastly interconnected, forming a global network that comprise in human alone >50,000 residues in about 6000 proteins. We predict substantial PTM type interplay in secreted and membrane-associated proteins and in the context of particular protein domains and short-linear motifs. The global network of co-evolving PTM types implies a complex and intertwined post-translational regulation landscape that is likely to regulate multiple functional states of many if not all eukaryotic proteins.

Background: Gene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks.For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs., Results: We present an improved method for modeling gene regulatory network motifs using Statecharts and we describe the successful modeling of several motifs, including those which could not be modeled or whose models could not be distinguished using the method of a previous proposal.We model motifs in an easy and intuitive way by taking advantage of the visual features of Statecharts. Our modeling approach is able to simulate some interesting temporal properties of gene regulatory network motifs: the delay in the activation and the deactivation of the "output" gene in the coherent type-1 feedforward loop, the pulse in the incoherent type-1 feedforward loop, the bistability nature of double positive and double negative feedback loops, the oscillatory behavior of the negative feedback loop, and the "lock-in" effect of positive autoregulation., Conclusions: We present a Statecharts-based approach for the modeling of gene regulatory network motifs in biological systems. The basic motifs used to build more complex networks (that is, simple regulation, reciprocal regulation, feedback loop, feedforward loop, and autoregulation) can be faithfully described and their temporal dynamics can be analyzed.

Large-scale siRNA screenings allow linking the function of poorly characterized genes to phenotypic readouts. According to this strategy, genes are associated with a function of interest if the alteration of their expression perturbs the phenotypic readouts. However, given the intricacy of the cell regulatory network, the mapping procedure is low resolution and the resulting models provide little mechanistic insights. We have developed a new strategy that combines multiparametric analysis of cell perturbation with logic modeling to achieve a more detailed functional mapping of human genes onto complex pathways. A literature-derived optimized model is used to infer the cell activation state following upregulation or downregulation of the model entities. By matching this signature with the experimental profile obtained in the high-throughput siRNA screening it is possible to infer the target of each protein, thus defining its 'entry point' in the network. By this novel approach, 41 phosphatases that affect key growth pathways were identified and mapped onto a human epithelial cell-specific growth model, thus providing insights into the mechanisms underlying their function.

Nucleotides are involved in several cellular processes, ranging from the transmission of genetic information, to energy transfer and storage. Both sequence and structure based methods have been developed to predict the location of nucleotide-binding sites in proteins. Here we propose a novel methodology that leverages the observation that nucleotide-binding sites have a modular structure. Nucleotides are composed of identifiable fragments, i.e. the phosphate, the nucleobase and the carbohydrate moieties. These fragments are bound by specific structural motifs that recur in proteins of different fold. Moreover these motifs behave as modules and are found in different combinations across fold space. Our method predicts binding sites for each nucleotide fragment by comparing a query protein with a database of templates extracted from proteins of known structure. Whenever a similarity is found the fragment bound by the template is transferred on the query protein, thus identifying a putative binding site. Predictions falling inside the surface of the protein are discarded, and the remaining ones are scored using clustering and conservation. The method is able to rank as first a correct prediction in the 48%, 48% and 68% of the analyzed proteins for the nucleobase, carbohydrate and phosphate respectively, while considering the first five predictions the performances change to 71%, 65% and 86% respectively. Furthermore we attempted to reconstruct the full structure of the binding site, starting from the predicted positions of the fragments. We calculated that in the 59% of the analyzed proteins the method ranks as first a reconstructed binding site or a part of it. Finally we tested the reliability of our method in a real world case in which it has to predict nucleotide-binding sites in unbound proteins. We analyzed proteins whose structure has been solved with and without the nucleotide and observed only little variations in the method performance.

The protozoan parasite Leishmania donovani undergoes various developmental transitions during its infectious cycle that are triggered by environmental signals encountered inside insect and vertebrate hosts. Intracellular differentiation of the pathogenic amastigote stage is induced by pH and temperature shifts that affect protein kinase activities and downstream protein phosphorylation. Identification of parasite proteins with phosphotransferase activity during intracellular infection may reveal new targets for pharmacological intervention. Here we describe an improved protocol to trace this activity in L. donovani extracts at high resolution combining in-gel kinase assay and two-dimensional gel electrophoresis. This 2D procedure allowed us to identify proteins that are associated with amastigote ATP-binding, ATPase, and phosphotransferase activities. The 2D in-gel kinase assay, in combination with recombinant phospho-protein substrates previously identified by phospho-proteomics analyses, provides a novel tool to establish specific protein kinase-substrate relationships thus improving our understanding of Leishmania signal transduction with relevance for future drug development., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Nearly half of known protein structures interact with phosphate-containing ligands, such as nucleotides and other cofactors. Many methods have been developed for the identification of metal ions-binding sites and some for bigger ligands such as carbohydrates, but none is yet available for the prediction of phosphate-binding sites. Here we describe Pfinder, a method that predicts binding sites for phosphate groups, both in the form of ions or as parts of other non-peptide ligands, in proteins of known structure. Pfinder uses the Query3D local structural comparison algorithm to scan a protein structure for the presence of a number of structural motifs identified for their ability to bind the phosphate chemical group. Pfinder has been tested on a data set of 52 proteins for which both the apo and holo forms were available. We obtained at least one correct prediction in 63% of the holo structures and in 62% of the apo. The ability of Pfinder to recognize a phosphate-binding site in unbound protein structures makes it an ideal tool for functional annotation and for complementing docking and drug design methods. The Pfinder program is available at http://pdbfun.uniroma2.it/pfinder.

Phospho3D is a database of three-dimensional (3D) structures of phosphorylation sites (P-sites) derived from the Phospho.ELM database, which also collects information on the residues surrounding the P-site in space (3D zones). The database also provides the results of a large-scale structural comparison of the 3D zones versus a representative dataset of structures, thus associating to each P-site a number of structurally similar sites. The new version of Phospho3D presents an 11-fold increase in the number of 3D sites and incorporates several additional features, including new structural descriptors, the possibility of selecting non-redundant sets of 3D structures and the availability for download of non-redundant sets of structurally annotated P-sites. Moreover, it features P3Dscan, a new functionality that allows the user to submit a protein structure and scan it against the 3D zones collected in the Phospho3D database. Phospho3D version 2.0 is available at: http://www.phospho3d.org/.

Phosphorylation is the most widely studied post-translational modification occurring in cells. While mass spectrometry-based proteomics experiments are uncovering thousands of novel in vivo phosphorylation sites, the identification of kinase specificity rules still remains a relatively slow and often inefficacious task. In the last twenty years, many efforts have being devoted to the experimental and computational identification of sequence and structural motifs encoding kinase-substrate interaction key residues and the phosphorylated amino acid itself. In this review, we retrace the road to the discovery of phosphorylation sequence motifs, examine the progresses achieved in the detection of three-dimensional motifs and discuss their importance in the understanding of regulation and de-regulation of many cellular processes.

Human pathogenic protozoa of the genus Leishmania undergo various developmental transitions during the infectious cycle that are triggered by changes in the host environment. How these parasites sense, transduce, and respond to these signals is only poorly understood. Here we used phosphoproteomic approaches to monitor signaling events in L. donovani axenic amastigotes, which may be important for intracellular parasite survival. LC-ESI-MS/MS analysis of IMAC-enriched phosphoprotein extracts identified 445 putative phosphoproteins in two independent biological experiments. Functional enrichment analysis allowed us to gain insight into parasite pathways that are regulated by protein phosphorylation and revealed significant enrichment in our data set of proteins whose biological functions are associated with protein turn-over, stress response, and signal transduction. LC-ESI-MS/MS analysis of TiO(2)-enriched phosphopeptides confirmed these results and identified 157 unique phosphopeptides covering 181 unique phosphorylation sites in 126 distinct proteins. Investigation of phosphorylation site conservation across related trypanosomatids and higher eukaryotes by multiple sequence alignment and cluster analysis revealed L. donovani-specific phosphoresidues in highly conserved proteins that share significant sequence homology to orthologs of the human host. These unique phosphorylation sites reveal important differences between host and parasite biology and post-translational protein regulation, which may be exploited for the design of novel anti-parasitic interventions.

Local structural comparison methods can be used to find structural similarities involving functional protein patches such as enzyme active sites and ligand binding sites. The outcome of such analyses is critically dependent on the representation used to describe the structure. Indeed different categories of functional sites may require the comparison program to focus on different characteristics of the protein residues. We have therefore developed superpose3D, a novel structural comparison software that lets users specify, with a powerful and flexible syntax, the structure description most suited to the requirements of their analysis. Input proteins are processed according to the user's directives and the program identifies sets of residues (or groups of atoms) that have a similar 3D position in the two structures. The advantages of using such a general purpose program are demonstrated with several examples. These test cases show that no single representation is appropriate for every analysis, hence the usefulness of having a flexible program that can be tailored to different needs. Moreover we also discuss how to interpret the results of a database screening where a known structural motif is searched against a large ensemble of structures. The software is written in C++ and is released under the open source GPL license. Superpose3D does not require any external library, runs on Linux, Mac OSX, Windows and is available at http://cbm.bio.uniroma2.it/superpose3D.

Background: Cyclosporin A (CsA) has important anti-microbial activity against parasites of the genus Leishmania, suggesting CsA-binding cyclophilins (CyPs) as potential drug targets. However, no information is available on the genetic diversity of this important protein family, and the mechanisms underlying the cytotoxic effects of CsA on intracellular amastigotes are only poorly understood. Here, we performed a first genome-wide analysis of Leishmania CyPs and investigated the effects of CsA on host-free L. donovani amastigotes in order to elucidate the relevance of these parasite proteins for drug development., Methodology/principal Findings: Multiple sequence alignment and cluster analysis identified 17 Leishmania CyPs with significant sequence differences to human CyPs, but with highly conserved functional residues implicated in PPIase function and CsA binding. CsA treatment of promastigotes resulted in a dose-dependent inhibition of cell growth with an IC50 between 15 and 20 microM as demonstrated by proliferation assay and cell cycle analysis. Scanning electron microscopy revealed striking morphological changes in CsA treated promastigotes reminiscent to developing amastigotes, suggesting a role for parasite CyPs in Leishmania differentiation. In contrast to promastigotes, CsA was highly toxic to amastigotes with an IC50 between 5 and 10 microM, revealing for the first time a direct lethal effect of CsA on the pathogenic mammalian stage linked to parasite thermotolerance, independent from host CyPs. Structural modeling, enrichment of CsA-binding proteins from parasite extracts by FPLC, and PPIase activity assays revealed direct interaction of the inhibitor with LmaCyP40, a bifunctional cyclophilin with potential co-chaperone function., Conclusions/significance: The evolutionary expansion of the Leishmania CyP protein family and the toxicity of CsA on host-free amastigotes suggest important roles of PPIases in parasite biology and implicate Leishmania CyPs in key processes relevant for parasite proliferation and viability. The requirement of Leishmania CyP functions for intracellular parasite survival and their substantial divergence form host CyPs defines these proteins as prime drug targets.

Recently, modularity has emerged as a general attribute of complex biological systems. This is probably because modular systems lend themselves readily to optimization via random mutation followed by natural selection. Although they are not traditionally considered to evolve by this process, biological ligands are also modular, being composed of recurring chemical fragments, and moreover they exhibit similarities reminiscent of mutations (e.g. the few atoms differentiating adenine and guanine). Many ligands are also promiscuous in the sense that they bind to many different protein folds. Here, we investigated whether ligand chemical modularity is reflected in an underlying modularity of binding sites across unrelated proteins. We chose nucleotides as paradigmatic ligands, because they can be described as composed of well-defined fragments (nucleobase, ribose and phosphates) and are quite abundant both in nature and in protein structure databases. We found that nucleotide-binding sites do indeed show a modular organization and are composed of fragment-specific protein structural motifs, which parallel the modular structure of their ligands. Through an analysis of the distribution of these motifs in different proteins and in different folds, we discuss the evolutionary implications of these findings and argue that the structural features we observed can arise both as a result of divergence from a common ancestor or convergent evolution.

Linear motifs are short segments of multidomain proteins that provide regulatory functions independently of protein tertiary structure. Much of intracellular signalling passes through protein modifications at linear motifs. Many thousands of linear motif instances, most notably phosphorylation sites, have now been reported. Although clearly very abundant, linear motifs are difficult to predict de novo in protein sequences due to the difficulty of obtaining robust statistical assessments. The ELM resource at http://elm.eu.org/ provides an expanding knowledge base, currently covering 146 known motifs, with annotation that includes >1300 experimentally reported instances. ELM is also an exploratory tool for suggesting new candidates of known linear motifs in proteins of interest. Information about protein domains, protein structure and native disorder, cellular and taxonomic contexts is used to reduce or deprecate false positive matches. Results are graphically displayed in a 'Bar Code' format, which also displays known instances from homologous proteins through a novel 'Instance Mapper' protocol based on PHI-BLAST. ELM server output provides links to the ELM annotation as well as to a number of remote resources. Using the links, researchers can explore the motifs, proteins, complex structures and associated literature to evaluate whether candidate motifs might be worth experimental investigation.

Background: Many proteins are highly modular, being assembled from globular domains and segments of natively disordered polypeptides. Linear motifs, short sequence modules functioning independently of protein tertiary structure, are most abundant in natively disordered polypeptides but are also found in accessible parts of globular domains, such as exposed loops. The prediction of novel occurrences of known linear motifs attempts the difficult task of distinguishing functional matches from stochastically occurring non-functional matches. Although functionality can only be confirmed experimentally, confidence in a putative motif is increased if a motif exhibits attributes associated with functional instances such as occurrence in the correct taxonomic range, cellular compartment, conservation in homologues and accessibility to interacting partners. Several tools now use these attributes to classify putative motifs based on confidence of functionality., Results: Current methods assessing motif accessibility do not consider much of the information available, either predicting accessibility from primary sequence or regarding any motif occurring in a globular region as low confidence. We present a method considering accessibility and secondary structural context derived from experimentally solved protein structures to rectify this situation. Putatively functional motif occurrences are mapped onto a representative domain, given that a high quality reference SCOP domain structure is available for the protein itself or a close relative. Candidate motifs can then be scored for solvent-accessibility and secondary structure context. The scores are calibrated on a benchmark set of experimentally verified motif instances compared with a set of random matches. A combined score yields 3-fold enrichment for functional motifs assigned to high confidence classifications and 2.5-fold enrichment for random motifs assigned to low confidence classifications. The structure filter is implemented as a pipeline with both a graphical interface via the ELM resource http://elm.eu.org/ and through a Web Service protocol., Conclusion: New occurrences of known linear motifs require experimental validation as the bioinformatics tools currently have limited reliability. The ELM structure filter will aid users assessing candidate motifs presenting in globular structural regions. Most importantly, it will help users to decide whether to expend their valuable time and resources on experimental testing of interesting motif candidates.

Background: The structural analysis of protein ligand binding sites can provide information relevant for assigning functions to unknown proteins, to guide the drug discovery process and to infer relations among distant protein folds. Previous approaches to the comparative analysis of binding pockets have usually been focused either on the ligand or the protein component. Even though several useful observations have been made with these approaches they both have limitations. In the former case the analysis is restricted to binding pockets interacting with similar ligands, while in the latter it is difficult to systematically check whether the observed structural similarities have a functional significance., Results: Here we propose a novel methodology that takes into account the structure of both the binding pocket and the ligand. We first look for local similarities in a set of binding pockets and then check whether the bound ligands, even if completely different, share a common fragment that can account for the presence of the structural motif. Thanks to this method we can identify structural motifs whose functional significance is explained by the presence of shared features in the interacting ligands., Conclusion: The application of this method to a large dataset of binding pockets allows the identification of recurring protein motifs that bind specific ligand fragments, even in the context of molecules with a different overall structure. In addition some of these motifs are present in a high number of evolutionarily unrelated proteins.

Background: The occurrence of very similar structural motifs brought about by different parts of non homologous proteins is often indicative of a common function. Indeed, relatively small local structures can mediate binding to a common partner, be it a protein, a nucleic acid, a cofactor or a substrate. While it is relatively easy to identify short amino acid or nucleotide sequence motifs in a given set of proteins or genes, and many methods do exist for this purpose, much more challenging is the identification of common local substructures, especially if they are formed by non consecutive residues in the sequence., Results: Here we describe a publicly available tool, able to identify common structural motifs shared by different non homologous proteins in an unsupervised mode. The motifs can be as short as three residues and need not to be contiguous or even present in the same order in the sequence. Users can submit a set of protein structures deemed or not to share a common function (e.g. they bind similar ligands, or share a common epitope). The server finds and lists structural motifs composed of three or more spatially well conserved residues shared by at least three of the submitted structures. The method uses a local structural comparison algorithm to identify subsets of similar amino acids between each pair of input protein chains and a clustering procedure to group similarities shared among different structure pairs., Conclusions: FunClust is fast, completely sequence independent, and does not need an a priori knowledge of the motif to be found. The output consists of a list of aligned structural matches displayed in both tabular and graphical form. We show here examples of its usefulness by searching for the largest common structural motifs in test sets of non homologous proteins and showing that the identified motifs correspond to a known common functional feature.

Background: DNA microarrays are among the most widely used technical platforms for DNA and RNA studies, and issues related to microarrays sensitivity and specificity are therefore of general importance in life sciences. Compatible solutes are derived from hyperthermophilic microorganisms and allow such microorganisms to survive in environmental and stressful conditions. Compatible solutes show stabilization effects towards biological macromolecules, including DNA., Results: We report here that compatible solutes from hyperthermophiles increased the performance of the hybridization buffer for Affymetrix GeneChip(R) arrays. The experimental setup included independent hybridizations with constant RNA over a wide range of compatible solute concentrations. The dependence of array quality and compatible solute was assessed using specialized statistical tools provided by both the proprietary Affymetrix quality control system and the open source Bioconductor suite., Conclusion: Low concentration (10 to 25 mM) of hydroxyectoine, potassium mannosylglycerate and potassium diglycerol phosphate in hybridization buffer positively affected hybridization parameters and enhanced microarrays outcome. This finding harbours a strong potential for the improvement of DNA microarray experiments.

Since convergent evolution of enzyme active sites was first identified in serine proteases, other individual instances of this phenomenon have been documented. However, a systematic analysis assessing the frequency of this phenomenon across enzyme space is still lacking. This work uses the Query3d structural comparison algorithm to integrate for the first time detailed knowledge about catalytic residues, available through the Catalytic Site Atlas (CSA), with the evolutionary information provided by the Structural Classification of Proteins (SCOP) database. This study considers two modes of convergent evolution: (i) mechanistic analogues which are enzymes that use the same mechanism to perform related, but possibly different, reactions (considered here as sharing the first three digits of the EC number); and (ii) transformational analogues which catalyse exactly the same reaction (identical EC numbers), but may use different mechanisms. Mechanistic analogues were identified in 15% (26 out of 169) of the three-digit EC groups considered, showing that this phenomenon is not rare. Furthermore 11 of these groups also contain transformational analogues. The catalytic triad is the most widespread active site; the results of the structural comparison show that this mechanism, or variations thereof, is present in 23 superfamilies. Transformational analogues were identified for 45 of the 951 four-digit EC numbers present within the CSA and about half of these were also mechanistic analogues exhibiting convergence of their active sites. This analysis has also been extended to the whole Protein Data Bank to provide a complete and manually curated list of the all the transformational analogues whose structure is classified in SCOP. The results of this work show that the phenomenon of convergent evolution is not rare, especially when considering large enzymatic families.

Objective: Rat alpha adducin point mutation (F316Y) has been associated with primary systemic arterial hypertension. As microcirculatory abnormalities are present in most forms of hypertension, the aim of the present study was to investigate whether rat alpha adducin may regulate endothelial cell (EC) functions in vitro and in vivo., Methods and Results: The overexpression of rat wild type alpha adducin (WT-Add1) in ECs induced capillary-like structure development in Matrigel in vitro and enhanced capillary formation in Matrigel implants in vivo in CD1 mice. In contrast, the overexpression of the mutated form (MUT-Add1) of rat alpha adducin had a Null effect in vitro and lacked any significant activity in vivo. Further, adenovirus-mediated rat WT-Add1 but not MUT-Add1 gene transfer to murine ischemic hindlimb enhanced capillary formation in skeletal muscles. Gene profiling of human umbilical vein endothelial cells overexpressing alpha adducin was performed in order to identify putative effector molecules of alpha adducin-mediated activities on ECs. Interestingly, among a number of genes involved in angiogenesis regulation, retinoic acid-induced protein (RAI17) was found to be upregulated in WT-Add1 vs MUT-Add1 overexpressing cells, possibly representing a key molecule/axis for the functional Add1-induced effect., Conclusions: Rat WT alpha adducin enhanced EC functions both in vitro and in vivo. The expression of the F316Y variant, associated with the hypertensive phenotype, had a Null effect and might contribute to endothelial rarefaction/dysfunction in hypertension. RAI17 was found to be a putative effector molecule differentially regulated by the overexpression of the two forms of Add1 in endothelial cells.

Background: We performed an exhaustive search for local structural similarities in an ensemble of non-redundant protein functional sites. With the purpose of finding new examples of convergent evolution, we selected only those matching sites composed of structural regions whose residue order is inverted in the relative protein sequences., Results: A novel case of local analogy was detected between members of the ABC transporter and of the HprK/P families in their ATP binding site. This case cannot be derived by events of circular permutation since the residues of one of the region pairs are located in reverse order in the sequence of the two protein families. One of the analogous binding sites, the one identified in HprK/P, is known to also bind pyrophosphate, which is used as preferred energy source in its kinase and phosphorylase activity., Conclusion: The discovery of this striking molecular similarity, also associated to a functional similarity, may help in suggesting new experiments aimed at a deeper understanding of members of the ABC transporter family known to be involved in many serious human diseases.

Background: False occurrences of functional motifs in protein sequences can be considered as random events due solely to the sequence composition of a proteome. Here we use a numerical approach to investigate the random appearance of functional motifs with the aim of addressing biological questions such as: How are organisms protected from undesirable occurrences of motifs otherwise selected for their functionality? Has the random appearance of functional motifs in protein sequences been affected during evolution?, Results: Here we analyse the occurrence of functional motifs in random sequences and compare it to that observed in biological proteomes; the behaviour of random motifs is also studied. Most motifs exhibit a number of false positives significantly similar to the number of times they appear in randomized proteomes (=expected number of false positives). Interestingly, about 3% of the analysed motifs show a different kind of behaviour and appear in biological proteomes less than they do in random sequences. In some of these cases, a mechanism of evolutionary negative selection is apparent; this helps to prevent unwanted functionalities which could interfere with cellular mechanisms., Conclusion: Our thorough statistical and biological analysis showed that there are several mechanisms and evolutionary constraints both of which affect the appearance of functional motifs in protein sequences.

The histopathologic and molecular heterogeneity of prostate cancer and the limited availability of human tumor tissue make unraveling the mechanisms of prostate carcinogenesis a challenging task. Our goal was to develop an ex vivo model that could be reliably used to define a prognostic signature based on gene expression profiling of cell cultures that maintained the tumor phenotype. To this end, we derived epithelial cultures from tissue explanted from 59 patients undergoing radical prostatectomy or cistoprostatectomy because of prostate benign hyperplasia/prostate cancer or bladder carcinoma. Patient selection criteria were absence of hormonal neoadjuvant treatment before surgery and diagnosis of clinically localized disease. Using this unique experimental material, we analyzed expression of 22,500 transcripts on the Affymetrix Human U133A GeneChip platform (Affymetrix, Inc., High Wycombe, United Kingdom). Cultures from normal/hyperplastic tissues with a prevalent luminal phenotype and from normal prostate epithelial tissue with basal phenotype (PrEC) served as controls. We have established a large number of prostate primary cultures highly enriched in the secretory phenotype. From them, we derived an epithelial-restricted transcriptional signature that (a) differentiated normal from tumor cells and (b) clearly separated cancer-derived lines into two distinct groups, which correlated with indolent or aggressive clinical behavior of the disease. Our findings provide (a) a method to expand human primary prostate carcinoma cells with a luminal phenotype, (b) a powerful experimental model to study primary prostate cancer biology, and (c) a novel means to characterize these tumors from a molecular genetic standpoint for prognostic and/or predictive purposes.

Background: The identification of local similarities between two protein structures can provide clues of a common function. Many different methods exist for searching for similar subsets of residues in proteins of known structure. However, the lack of functional and structural information on single residues, together with the low level of integration of this information in comparison methods, is a limitation that prevents these methods from being fully exploited in high-throughput analyses., Results: Here we describe Query3d, a program that is both a structural DBMS (Database Management System) and a local comparison method. The method conserves a copy of all the residues of the Protein Data Bank annotated with a variety of functional and structural information. New annotations can be easily added from a variety of methods and known databases. The algorithm makes it possible to create complex queries based on the residues' function and then to compare only subsets of the selected residues. Functional information is also essential to speed up the comparison and the analysis of the results., Conclusion: With Query3d, users can easily obtain statistics on how many and which residues share certain properties in all proteins of known structure. At the same time, the method also finds their structural neighbours in the whole PDB. Programs and data can be accessed through the PdbFun web interface.

Background: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that generally characterizes its ligands does not reflect the complex interaction spectrum of the over 1500 different SH3 domains, and the requirement of a more refined knowledge of their specificity implies the setting up of appropriate experimental and theoretical strategies. Due to the limitations of the current technology for peptide synthesis, several experimental high-throughput approaches have been devised to elucidate protein-protein interaction mechanisms. Such approaches can rely on and take advantage of computational techniques, such as regular expressions or position specific scoring matrices (PSSMs) to pre-process entire proteomes in the search for putative SH3 targets. In this regard, a reliable inference methodology to be used for reducing the sequence space of putative binding peptides represents a valuable support for molecular and cellular biologists., Results: Using as benchmark the peptide sequences obtained from in vitro binding experiments, we set up a neural network model that performs better than PSSM in the detection of SH3 domain interactors. In particular our model is more precise in its predictions, even if its performance can vary among different SH3 domains and is strongly dependent on the number of binding peptides in the benchmark., Conclusion: We show that a neural network can be more effective than standard methods in SH3 domain specificity detection. Neural classifiers identify general SH3 domain binders and domain-specific interactors from a PxxP peptide population, provided that there are a sufficient proportion of true positives in the training sets. This capability can also improve peptide selection for library definition in array experiments. Further advances can be achieved, including properly encoded domain sequences and structural information as input for a global neural network.

Background: Protein function is often dependent on subsets of solvent-exposed residues that may exist in a similar three-dimensional configuration in non homologous proteins thus having different order and/or spacing in the sequence. Hence, functional annotation by means of sequence or fold similarity is not adequate for such cases., Results: We describe a method for the function-related annotation of protein structures by means of the detection of local structural similarity with a library of annotated functional sites. An automatic procedure was used to annotate the function of local surface regions. Next, we employed a sequence-independent algorithm to compare exhaustively these functional patches with a larger collection of protein surface cavities. After tuning and validating the algorithm on a dataset of well annotated structures, we applied it to a list of protein structures that are classified as being of unknown function in the Protein Data Bank. By this strategy, we were able to provide functional clues to proteins that do not show any significant sequence or global structural similarity with proteins in the current databases., Conclusion: This method is able to spot structural similarities associated to function-related similarities, independently on sequence or fold resemblance, therefore is a valuable tool for the functional analysis of uncharacterized proteins. Results are available at http://cbm.bio.uniroma2.it/surface/structuralGenomics.html.

Unlabelled: Several methods for establishing cross-links between Protein Data Bank (PDB) structures or Structural Classification of Proteins (SCOP) domains and Swiss-Prot + TrEMBL sequences (or vice versa) rely on database annotations. Alternatively, sequence alignment procedures can be used. In this study, we describe Seq2Struct, a web resource for the identification of sequence-structure links. The resource consists of an exhaustive collection of annotated links between Swiss-Prot + TrEMBL and PDB + SCOP database entries. Links are based on pre-established highly reliable thresholds and stored in a relational database, which has been enhanced using annotations derived from Swiss-Prot, PDB, SCOP, GOA and DSSP databases. The Seq2Struct database contents, supported by a WWW web interface, can be queried both online and downloaded., Availability: The Seq2Struct resource, with related documentation, is available at http://surface.bio.uniroma2.it/seq2struct/, Contact: seq2struct@cbm.bio.uniroma2.it.

Background: A large number of PROSITE patterns select false positives and/or miss known true positives. It is possible that--at least in some cases--the weak specificity and/or sensitivity of a pattern is due to the fact that one, or maybe more, functional and/or structural key residues are not represented in the pattern. Multiple sequence alignments are commonly used to build functional sequence patterns. If residues structurally conserved in proteins sharing a function cannot be aligned in a multiple sequence alignment, they are likely to be missed in a standard pattern construction procedure., Results: Here we present a new procedure aimed at improving the sensitivity and/ or specificity of poorly-performing patterns. The procedure can be summarised as follows: 1. residues structurally conserved in different proteins, that are true positives for a pattern, are identified by means of a computational technique and by visual inspection. 2. the sequence positions of the structurally conserved residues falling outside the pattern are used to build extended sequence patterns. 3. the extended patterns are optimised on the SWISS-PROT database for their sensitivity and specificity. The method was applied to eight PROSITE patterns. Whenever structurally conserved residues are found in the surface region close to the pattern (seven out of eight cases), the addition of information inferred from structural analysis is shown to improve pattern selectivity and in some cases selectivity and sensitivity as well. In some of the cases considered the procedure allowed the identification of functionally interesting residues, whose biological role is also discussed., Conclusion: Our method can be applied to any type of functional motif or pattern (not only PROSITE ones) which is not able to select all and only the true positive hits and for which at least two true positive structures are available. The computational technique for the identification of structurally conserved residues is already available on request and will be soon accessible on our web server. The procedure is intended for the use of pattern database curators and of scientists interested in a specific protein family for which no specific or selective patterns are yet available.

The SURFACE (SUrface Residues and Functions Annotated, Compared and Evaluated, URL http://cbm.bio.uniroma2.it/surface/) database is a repository of annotated and compared protein surface regions. SURFACE contains the results of a large-scale protein annotation and local structural comparison project. A non-redundant set of protein chains is used to build a database of protein surface patches, defined as putative surface functional sites. Each patch is annotated with sequence and structure-derived information about function or interaction abilities. A new procedure for structure comparison is used to perform an all-versus-all patches comparison. Selection of the results obtained with stringent parameters offers a similarity score that can be used to associate different patches and allows reliable annotation by similarity. Annotation exerted through the comparison of regions of protein surface allows the highlighting of similarities that cannot be recognized by other methods of sequence or structure comparison. A graphic representation of the surface patches, functional annotations and the structural superpositions is available through the web interface.

The Molecular Interactions Database (MINT) is a relational database designed to store information about protein interactions. Expert curators extract the relevant information from the scientific literature and deposit it in a computer readable form. Currently (April 2003) MINT contains information on 4300 proteins and >3000 interactions. Although MINT contains interactions among proteins for several different species, the curators have initially focused on protein interactions in mammalian species. Protocols are provided here for searching MINT over the Internet, using the MINT Viewer.

iSPOT (http://cbm.bio.uniroma2.it/ispot) is a web tool developed to infer the recognition specificity of protein module families; it is based on the SPOT procedure that utilizes information from position-specific contacts, derived from the available domain/ligand complexes of known structure, and experimental interaction data to build a database of residue-residue contact frequencies. iSPOT is available to infer the interaction specificity of PDZ, SH3 and WW domains. For each family of protein domains, iSPOT evaluates the probability of interaction between a query domain of the specified families and an input protein/peptide sequence and makes it possible to search for potential binding partners of a given domain within the SWISS-PROT database. The experimentally derived interaction data utilized to build the PDZ, SH3 and WW databases of residue-residue contact frequencies are also accessible. Here we describe the application to the WW family of protein modules.

Multidomain proteins predominate in eukaryotic proteomes. Individual functions assigned to different sequence segments combine to create a complex function for the whole protein. While on-line resources are available for revealing globular domains in sequences, there has hitherto been no comprehensive collection of small functional sites/motifs comparable to the globular domain resources, yet these are as important for the function of multidomain proteins. Short linear peptide motifs are used for cell compartment targeting, protein-protein interaction, regulation by phosphorylation, acetylation, glycosylation and a host of other post-translational modifications. ELM, the Eukaryotic Linear Motif server at http://elm.eu.org/, is a new bioinformatics resource for investigating candidate short non-globular functional motifs in eukaryotic proteins, aiming to fill the void in bioinformatics tools. Sequence comparisons with short motifs are difficult to evaluate because the usual significance assessments are inappropriate. Therefore the server is implemented with several logical filters to eliminate false positives. Current filters are for cell compartment, globular domain clash and taxonomic range. In favourable cases, the filters can reduce the number of retained matches by an order of magnitude or more.

Relatively few protein structures are known, compared to the enormous amount of sequence data produced in the sequencing of different genomes, and relatively few protein complexes are deposited in the PDB with respect to the great amount of interaction data coming from high-throughput experiments (two-hybrid or affinity purification of protein complexes and mass spectrometry). Nevertheless, we can rely on computational techniques for the extraction of high-quality and information-rich data from the known structures and for their spreading in the protein sequence space. We describe here the ongoing research projects in our group: we analyse the protein complexes stored in the PDB and, for each complex involving one domain belonging to a family of interaction domains for which some interaction data are available, we can calculate its probability of interaction with any protein sequence. We analyse the structures of proteins encoding a function specified in a PROSITE pattern, which exhibits relatively low selectivity and specificity, and build extended patterns. To this aim, we consider residues that are well-conserved in the structure, even if their conservation cannot easily be recognized in the sequence alignment of the proteins holding the function. We also analyse protein surface regions and, through the annotation of the solvent-exposed residues, we annotate protein surface patches via a structural comparison performed with stringent parameters and independently of the residue order in the sequence. Local surface comparison may also help in identifying new sequence patterns, which could not be highlighted with other sequence-based methods.