The IntAct database: efficient access to fine-grained molecular interaction data

The IntAct molecular interaction database (https://www.ebi.ac.uk/intact) is a curated resource of molecular interactions, derived from the scientific literature and from direct data depositions. As of August 2021, IntAct provides more than one million binary interactions, curated by twelve global partners of the International Molecular Exchange consortium, for which the IntAct database provides a shared curation and dissemination platform. The IMEx curation policy has always emphasised a fine-grained data and curation model, aiming to capture the relevant experimental detail essential for the interpretation of the provided molecular interaction data. Here, we present recent curation focus and progress, as well as a completely redeveloped website which presents IntAct data in a much more user-friendly and detailed way.

The Gene Regulation Knowledge Commons: The action area of GREEKC

The COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various parts of the knowledge cycle that is central to understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to update and standardise existing knowledge management workflows, encourage new experimental approaches and thoroughly involve end-users in the process to design the Gene Regulation Knowledge Commons (GRKC). The GREEKC consortium describes its main achievements, contextualised in a state-of-the-art of current tools and resources that today represent the GRKC.

The Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST)

Motivation

A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called ‘causal interaction’ takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g. gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources.

Results

Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources.

Availability and implementation

The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST

Supplementary information

Supplementary data are available at Bioinformatics online.

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world's largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

Towards a unified open access dataset of molecular interactions

The International Molecular Exchange (IMEx) Consortium provides scientists with a single body of experimentally verified protein interactions curated in rich contextual detail to an internationally agreed standard. In this update to the work of the IMEx Consortium, we discuss how this initiative has been working in practice, how it has ensured database sustainability, and how it is meeting emerging annotation challenges through the introduction of new interactor types and data formats. Additionally, we provide examples of how IMEx data are being used by biomedical researchers and integrated in other bioinformatic tools and resources.

The IMEx Coronavirus interactome: an evolving map of Coronaviridae-Host molecular interactions

The current Coronavirus Disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions enables studying fine-grained resolution of the mechanisms behind the virus biology and the human organism response. Here we present a curated dataset of physical molecular interactions, manually extracted by IMEx Consortium curators focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family. Currently, the dataset comprises over 2,200 binarized interactions extracted from 86 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website ( www.ebi.ac.uk/intact ), and will be continuously updated as research on COVID-19 progresses.

The IMEx coronavirus interactome: an evolving map of Coronaviridae-host molecular interactions

The current coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions can provide fine-grained resolution of the mechanisms behind the virus biology and the human organism response. We present a curated dataset of physical molecular interactions focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family that has been manually extracted by International Molecular Exchange (IMEx) Consortium curators. Currently, the dataset comprises over 4400 binarized interactions extracted from 151 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (https://www.ebi.ac.uk/intact) and will be continuously updated as research on COVID-19 progresses.

Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions

BACKGROUND

Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes.

RESULTS

The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal.

CONCLUSIONS

PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download.

The yeast noncoding RNA interaction network

This article describes the creation of the first expert manually curated noncoding RNA interaction networks for S. cerevisiae The RNA-RNA and RNA-protein interaction networks have been carefully extracted from the experimental literature and made available through the IntAct database (www.ebi.ac.uk/intact). We provide an initial network analysis and compare their properties to the much larger protein-protein interaction network. We find that the proteins that bind to ncRNAs in the network contain only a small proportion of classical RNA binding domains. We also see an enrichment of WD40 domains suggesting their direct involvement in ncRNA interactions. We discuss the challenges in collecting noncoding RNA interaction data and the opportunities for worldwide collaboration to fill the unmet need for this data.

Profiling Phosphopeptide-Binding Domain Recognition Specificity Using Peptide Microarrays

Cellular organization and response to internal and external stimuli are mediated by an intricate web of protein interactions. Some of these interactions are regulated by covalent posttranslational modifications such as phosphorylation and acetylation. These modifications can change the chemical nature of the interaction interfaces and modulate the binding affinity of the interacting partners. In signal transduction, the most frequent modification is reversible phosphorylation of tyrosine, serine or threonine residues. Protein phosphorylation may modulate the activity of enzymes by modifying their conformation, or regulate the formation of complexes by creating docking sites to recruit downstream effectors. Families of modular domains, such as SH2, PTB, and 14-3-3, act as "readers" of the modification event. Specificity between closely related domains of the same family is mediated by the chemical properties of the domain binding surface that, aside from offering a hydrophilic pocket for the phosphorylated residue, shows preference for specific sequences. Although the protein structure and the cell context are also important to ensure specificity, the amino acid sequence flanking the phosphorylation site defines the accuracy of the recognition process, and it is therefore essential to define the binding specificity of phosphopeptide binding domains in order to understand and to infer the interaction web mediated by phosphopeptides. Methods commonly used to discover new interactions (such as yeast two hybrid and phage display) are not suited to study interactions with phosphorylated proteins. On the other hand, peptide arrays are a powerful approach to precisely identify the binding preference of phosphopeptide recognition domains. Here we describe a detailed protocol to assemble arrays of hundreds to thousands phospho-peptides and to screen them with any modular domain of interest.

The adapter protein CD2AP binds to p53 protein in the cytoplasm and can discriminate its polymorphic variants P72R

Proline-rich motifs are widely distributed in eukaryotic proteomes and are usually involved in the assembly of functional complexes through interaction with specific binding modules. The tumour-suppressor p53 protein presents a proline-rich region that is crucial for regulating apoptosis by connecting the p53 with a complex protein network. In humans, a common polymorphism determines the identity of residue 72, either proline or arginine, and affects the features of the motifs present in the polyproline domain. The two isoforms have different biochemical properties and markedly influence cancer onset and progression. In this article, we analyse the binding of the p53 proline-rich region with a pool of selected polyproline binding domains (i.e. SH3 and WW), and we present the first demonstration that the purified SH3 domains of the CD2AP/Cin85 protein family are able to directly bind the p53 protein, and to discriminate between the two polymorphic variants P72R.

Combining affinity proteomics and network context to identify new phosphatase substrates and adapters in growth pathways

Protein phosphorylation homoeostasis is tightly controlled and pathological conditions are caused by subtle alterations of the cell phosphorylation profile. Altered levels of kinase activities have already been associated to specific diseases. Less is known about the impact of phosphatases, the enzymes that down-regulate phosphorylation by removing the phosphate groups. This is partly due to our poor understanding of the phosphatase-substrate network. Much of phosphatase substrate specificity is not based on intrinsic enzyme specificity with the catalytic pocket recognizing the sequence/structure context of the phosphorylated residue. In addition many phosphatase catalytic subunits do not form a stable complex with their substrates. This makes the inference and validation of phosphatase substrates a non-trivial task. Here, we present a novel approach that builds on the observation that much of phosphatase substrate selection is based on the network of physical interactions linking the phosphatase to the substrate. We first used affinity proteomics coupled to quantitative mass spectrometry to saturate the interactome of eight phosphatases whose down regulations was shown to affect the activation of the RAS-PI3K pathway. By integrating information from functional siRNA with protein interaction information, we develop a strategy that aims at inferring phosphatase physiological substrates. Graph analysis is used to identify protein scaffolds that may link the catalytic subunits to their substrates. By this approach we rediscover several previously described phosphatase substrate interactions and characterize two new protein scaffolds that promote the dephosphorylation of PTPN11 and ERK by DUSP18 and DUSP26, respectively.

Specificity of ε and non-ε isoforms of arabidopsis 14-3-3 proteins towards the H+-ATPase and other targets

14-3-3 proteins are a family of ubiquitous dimeric proteins that modulate many cellular functions in all eukaryotes by interacting with target proteins. 14-3-3s exist as a number of isoforms that in Arabidopsis identifies two major groups named ε and non-ε. Although isoform specificity has been demonstrated in many systems, the molecular basis for the selection of specific sequence contexts has not been fully clarified. In this study we have investigated isoform specificity by measuring the ability of different Arabidopsis 14-3-3 isoforms to activate the H⁺-ATPase. We observed that GF14 isoforms of the non-ε group were more effective than ε group isoforms in the interaction with the H⁺-ATPase and in the stimulation of its activity. Kinetic and thermodynamic parameters of the binding of GF14ε and GF14ω isoforms, representative of ε and non-ε groups respectively, with the H⁺-ATPase, have been determined by Surface Plasmon Resonance analysis demonstrating that the higher affinity of GF14ω is mainly due to slower dissociation. The role of the C-terminal region and of a Gly residue located in the loop 8 and conserved in all non-ε isoforms has also been studied by deletion and site-specific mutagenesis. The C-terminal domains, despite their high divergence, play an auto-inhibitory role in both isoforms and they, in addition to a specific residue located in the loop 8, contribute to isoform specificity. To investigate the generality of these findings, we have used the SPOT-synthesis technology to array a number of phosphopeptides matching known or predicted 14-3-3 binding sites present in a number of clients. The results of this approach confirmed isoform specificity in the recognition of several target peptides, suggesting that the isoform specificity may have an impact on the modulation of a variety of additional protein activities, as suggested by probing of a phosphopeptide array with members of the two 14-3-3 groups.

Searching for repetitions in biological networks: methods, resources and tools

We present here a compact overview of the data, models and methods proposed for the analysis of biological networks based on the search for significant repetitions. In particular, we concentrate on three problems widely studied in the literature: 'network alignment', 'network querying' and 'network motif extraction'. We provide (i) details of the experimental techniques used to obtain the main types of interaction data, (ii) descriptions of the models and approaches introduced to solve such problems and (iii) pointers to both the available databases and software tools. The intent is to lay out a useful roadmap for identifying suitable strategies to analyse cellular data, possibly based on the joint use of different interaction data types or analysis techniques.

Asymmetric comparison and querying of biological networks

Comparing and querying the protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform these tasks operate symmetrically, i.e., they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how the corresponding organism is biologically well characterized. In this paper a new idea is developed, that is, to exploit differences in the characterization of organisms at hand in order to devise methods for comparing their PPI networks. We use the PPI network (called Master) of the best characterized organism as a fingerprint to guide the alignment process to the second input network (called Slave), so that generated results preferably retain the structural characteristics of the Master network. Technically, this is obtained by generating from the Master a finite automaton, called alignment model, which is then fed with (a linearization of) the Slave for the purpose of extracting, via the Viterbi algorithm, matching subgraphs. We propose an approach able to perform global alignment and network querying, and we apply it on PPI networks. We tested our method showing that the results it returns are biologically relevant.

Multiple modification and protein interaction signals drive the Ring finger protein 11 (RNF11) E3 ligase to the endosomal compartment

Ring finger protein 11 (RNF11) is a small RING E3-ligase overexpressed in numerous human prostate, colon and invasive breast cancers. Although functional studies have implicated RNF11 in a variety of biological processes, including signal transduction and apoptosis, the molecular mechanisms underlying its function are still poorly understood. In this study we show that RNF11 is a membrane-associated E3 ligase co-localizing with markers of both the early and the recycling endosomes. Several modification and protein interaction signals in the RNF11 sequence are shown to affect its compartmentalization. Membrane binding requires two acylation motifs driving the myristoylation of Gly2 and the S-palmitoylation of Cys4. Accordingly, genetic removal of the myristoylating signal results in diffuse staining, whereas an RNF11 protein mutated in the palmitoylation signal is retained in compartments of the early secretory pathway. However, amino-terminal fusion to green fluorescent protein of a 10-residue peptide containing both acylation signals re-localizes the chimera to the plasma membrane, but it is not sufficient to direct it to the recycling compartment suggesting that additional signals contribute to the correct localization. In addition, we show that membrane anchoring through acylation is necessary for RNF11 to be post-translationally modified by the addition of several ubiquitin moieties and that loss of acylation severely impairs the in vivo ubiquitination mediated by the HECT E3-ligases Itch and Nedd4. Finally, in cells transfected with RNF11 we observe a correlation between high RNF11 expression, as in tumor cells, and a swelling of the endosomal compartment suggesting a possible role of the dysregulation of the endosome compartment in tumorigenesis.

Bayesian modeling of the yeast SH3 domain interactome predicts spatiotemporal dynamics of endocytosis proteins

A genome-scale specificity and interaction map for yeast SH3 domain-containing proteins reveal how family members show selective binding to target proteins and predicts the dynamic localization of new candidate endocytosis proteins.

SH3 domains are peptide recognition modules that mediate the assembly of diverse biological complexes. We scanned billions of phage-displayed peptides to map the binding specificities of the SH3 domain family in the budding yeast, Saccharomyces cerevisiae. Although most of the SH3 domains fall into the canonical classes I and II, each domain utilizes distinct features of its cognate ligands to achieve binding selectivity. Furthermore, we uncovered several SH3 domains with specificity profiles that clearly deviate from the two canonical classes. In conjunction with phage display, we used yeast two-hybrid and peptide array screening to independently identify SH3 domain binding partners. The results from the three complementary techniques were integrated using a Bayesian algorithm to generate a high-confidence yeast SH3 domain interaction map. The interaction map was enriched for proteins involved in endocytosis, revealing a set of SH3-mediated interactions that underlie formation of protein complexes essential to this biological pathway. We used the SH3 domain interaction network to predict the dynamic localization of several previously uncharacterized endocytic proteins, and our analysis suggests a novel role for the SH3 domains of Lsb3p and Lsb4p as hubs that recruit and assemble several endocytic complexes.

Significant diversity exists in protein structure and function, yet certain structural domains are used repeatedly across species to execute similar functions. The SH3 domain is one such common structural domain. It is found in signaling proteins and mediates protein–protein interactions by binding to short peptide sequences generally composed of proline. To investigate both the generality and selectivity of peptide binding by SH3 domains, we examined peptide specificity for almost all SH3 domains encoded within the proteome of the budding yeast, Saccharomyces cerevisiae, using a range of experimental methods. We found that although most of the intrinsic binding specificity for SH3 domains can be summarized by the two previously described canonical binding modes, each individual SH3 domain that we studied utilizes unique features of its cognate ligand to achieve binding selectivity. Moreover, some domains exhibit binding specificities that are distinct from the two canonical classes. We integrated peptide-SH3 domain binding data from three complementary screening techniques using a Bayesian statistical model to generate a protein–protein interaction network for the budding yeast SH3 domain family. This network was highly enriched in endocytosis proteins and their interactions. By examining these interactions in detail, we show that our SH3 domain network can be used to predict the temporal localization of several previously uncharacterized proteins to dynamic complexes that orchestrate the process of endocytosis.

VirusMINT: a viral protein interaction database

Understanding the consequences on host physiology induced by viral infection requires complete understanding of the perturbations caused by virus proteins on the cellular protein interaction network. The VirusMINT database (http://mint.bio.uniroma2.it/virusmint/) aims at collecting all protein interactions between viral and human proteins reported in the literature. VirusMINT currently stores over 5000 interactions involving more than 490 unique viral proteins from more than 110 different viral strains. The whole data set can be easily queried through the search pages and the results can be displayed with a graphical viewer. The curation effort has focused on manuscripts reporting interactions between human proteins and proteins encoded by some of the most medically relevant viruses: papilloma viruses, human immunodeficiency virus 1, Epstein–Barr virus, hepatitis B virus, hepatitis C virus, herpes viruses and Simian virus 40.

Binding to DPF-motif by the POB1 EH domain is responsible for POB1-Eps15 interaction

Background

Eps15 homology (EH) domains are protein interaction modules binding to peptides containing Asn-Pro-Phe (NPF) motifs and mediating critical events during endocytosis and signal transduction. The EH domain of POB1 associates with Eps15, a protein characterized by a striking string of DPF triplets, 15 in human and 13 in mouse Eps15, at the C-terminus and lacking the typical EH-binding NPF motif.

Results

By screening a multivalent nonapeptide phage display library we have demonstrated that the EH domain of POB1 has a different recognition specificity since it binds to both NPF and DPF motifs. The region of mouse Eps15 responsible for the interaction with the EH domain of POB1 maps within a 18 amino acid peptide (residues 623–640) that includes three DPF repeats. Finally, mutational analysis in the EH domain of POB1, revealed that several solvent exposed residues, while distal to the binding pocket, mediate specific recognition of binding partners through both hydrophobic and electrostatic contacts.

Conclusion

In the present study we have analysed the binding specificity of the POB1 EH domain. We show that it differs from other EH domains since it interacts with both NPF- and DPF-containing sequences. These unusual binding properties could be attributed to a different conformation of the binding pocket that allows to accommodate negative charges; moreover, we identified a cluster of solvent exposed Lys residues, which are only found in the EH domain of POB1, and influence binding to both NPF and DPF motifs. The characterization of structures of the DPF ligands described in this study and the POB1 EH domain will clearly determine the involvement of the positive patch and the rationalization of our findings.

Selectivity and promiscuity in the interaction network mediated by protein recognition modules

A substantial fraction of protein interactions in the cell is mediated by families of protein modules binding to relatively short linear peptides. Many of these interactions have a high dissociation constant and are therefore suitable for supporting the formation of dynamic complexes that are assembled and disassembled during signal transduction. Extensive work in the past decade has shown that, although member domains within a family have some degree of intrinsic peptide recognition specificity, the derived interaction networks display substantial promiscuity. We review here recent advances in the methods for deriving the portion of the protein network mediated by these domain families and discuss how specific biological outputs could emerge in vivo despite the observed promiscuity in peptide recognition in vitro.

Protein interaction networks by proteome peptide scanning

A substantial proportion of protein interactions relies on small domains binding to short peptides in the partner proteins. Many of these interactions are relatively low affinity and transient, and they impact on signal transduction. However, neither the number of potential interactions mediated by each domain nor the degree of promiscuity at a whole proteome level has been investigated. We have used a combination of phage display and SPOT synthesis to discover all the peptides in the yeast proteome that have the potential to bind to eight SH3 domains. We first identified the peptides that match a relaxed consensus, as deduced from peptides selected by phage display experiments. Next, we synthesized all the matching peptides at high density on a cellulose membrane, and we probed them directly with the SH3 domains. The domains that we have studied were grouped by this approach into five classes with partially overlapping specificity. Within the classes, however, the domains display a high promiscuity and bind to a large number of common targets with comparable affinity. We estimate that the yeast proteome contains as few as six peptides that bind to the Abp1 SH3 domain with a dissociation constant lower than 100 μM, while it contains as many as 50–80 peptides with corresponding affinity for the SH3 domain of Yfr024c. All the targets of the Abp1 SH3 domain, identified by this approach, bind to the native protein in vivo, as shown by coimmunoprecipitation experiments. Finally, we demonstrate that this strategy can be extended to the analysis of the entire human proteome. We have developed an approach, named WISE (whole interactome scanning experiment), that permits rapid and reliable identification of the partners of any peptide recognition module by peptide scanning of a proteome. Since the SPOT synthesis approach is semiquantitative and provides an approximation of the dissociation constants of the several thousands of interactions that are simultaneously analyzed in an array format, the likelihood of each interaction occurring in any given physiological settings can be evaluated. WISE can be easily extended to a variety of protein interaction domains, including those binding to modified peptides, thereby offering a powerful proteomic tool to help completing a full description of the cell interactome.

By combining phage display and SPOT selection, the binding partners of any peptide recognition motif can be identified, thus facilitating the identification of all protein-protein interactions within a proteome

In vitro evolution of recognition specificity mediated by SH3 domains reveals target recognition rules

We have designed a repertoire of 10(7) different SH3 domains by grafting the residues that are represented in the binding surfaces of natural SH3 domains onto the scaffold of the human Abl-SH3 domain. This phage-displayed library was screened by affinity selection for SH3 domains that bind to the synthetic peptides, APTYPPPLPP and LSSRPLPTLPSP, which are peptide ligands for the human Abl or Src SH3 domains, respectively. By characterizing the isolates, we have observed that as few as two or three amino acid substitutions lead to dramatic changes in recognition specificity. We propose that the ability to shift recognition specificity with a small number of amino acid replacements is an important evolutionary characteristic of protein binding modules. Furthermore, we have used the information obtained by these in vitro evolution experiments to generate a scoring matrix that evaluates the probability that any SH3 domain binds to the peptide ligands for the Abl and Src SH3 domains. A table of predictions for the 28 SH3 domains of baker's yeast is presented.

Mapping the C terminal epitope of the Alzheimer's disease specific antibody MN423

The mapping of monoclonal antibody epitopes is now predominantly carried out using molecular diversity techniques, phage display in particular. However, until very recently, phage display methods have been inappropriate for the analysis of epitopes that require a free carboxy terminus. Here we describe the use of two different techniques to analyze the known C terminal epitope specificity of MN423, a monoclonal antibody specifically staining truncated tau in Alzheimer's brain. Using a lambda phage based C-terminal random peptide library, and an intracellular expression library based on truncated tau, we show that this antibody has an absolute requirement for a glycine at position -3 with respect to the C terminus. Both methods give similar results, and identify other important residues in the binding site. However, affinity analysis of synthetic peptides revealed that the affinity of the antibody for identified tripeptides was far lower than the pentapeptide sequence in the native target, and that this in turn was considerably below the affinity for the native target itself. This suggests that molecular diversity methods may define minimum, but not necessarily complete epitopes. The methods described here have a general application to the analysis of antibody epitopes suspected to be found at the C terminus.

Can we infer peptide recognition specificity mediated by SH3 domains?

Protein interaction domain families that modulate the formation of macromolecular complexes recognize specific sequence or structural motifs. For instance SH3 and WW domains bind to polyproline peptides while SH2 and FHA domains bind to peptides phosphorylated in Tyr and Thr respectively. Within each family, variations in the chemical characteristics of the domain binding pocket modulate a finer peptide recognition specificity and, as a consequence, determine the selection of functional protein partners in vivo. In the proteomic era there is the need for reliable inference methods to help restricting the sequence space of the putative targets to be confirmed experimentally by more laborious experimental approaches. Here we will review the published data about the peptide recognition specificity of the SH3 domain family and we will propose a classification of SH3 domains into eight classes. Finally, we will discuss whether the available information is sufficient to infer the recognition specificity of any uncharacterized SH3 domain.

Alternative bacteriophage display systems

Filamentous phage has been extensively used to implement various aspects of phage display technology. The success of these organisms as vectors to present foreign peptides and to link them to their coding sequences is a consequence of their structural and biological characteristics. Some of these properties, however, represent a limitation when one attempts to display proteins that cannot be efficiently exported through the bacterial membrane or do not fold properly in the periplasm. Thus, the desirability of developing alternative display systems was recognised recently and led to the development of a different class of display vectors that assemble their capsid in the cytoplasm and are released via cell lysis. This review describes and compares the properties of these alternative display systems.

Domain repertoires as a tool to derive protein recognition rules

Several approaches, some of which are described in this issue, have been proposed to assemble a complete protein interaction map. These are often based on high throughput methods that explore the ability of each gene product to bind any other element of the proteome of the organism. Here we propose that a large number of interactions can be inferred by revealing the rules underlying recognition specificity of a small number (a few hundreds) of families of protein recognition modules. This can be achieved through the construction and characterization of domain repertoires. A domain repertoire is assembled in a combinatorial fashion by allowing each amino acid position in the binding site of a given protein recognition domain to vary to include all the residues allowed at that position in the domain family. The repertoire is then searched by phage display techniques with any target of interest and from the primary structure of the binding site of the selected domains one derives rules that are used to infer the formation of complexes between natural proteins in the cell.

A novel peptide-SH3 interaction

SH3 domains constitute a family of protein-protein interaction modules that bind to peptides displaying an X-proline-X-X-proline (XPXXP) consensus. We report that the SH3 domain of Eps8, a substrate of receptor and non-receptor tyrosine kinases, displays a novel and unique binding preference. By a combination of approaches including (i) screening of phage-displayed random peptide libraries, (ii) mapping of the binding regions on three physiological interactors of Eps8, (iii) alanine scanning of binding peptides and (iv) in vitro cross-linking, we demonstrate that a proline-X-X-aspartate-tyrosine (PXXDY) consensus is indispensable for binding to the SH3 domain of Eps8. Screening of the Expressed Sequence Tags database allowed the identification of three Eps8-related genes, whose SH3s also display unusual binding preferences and constitute a phylogenetically distinct subfamily within the SH3 family. Thus, Eps8 identifies a novel family of SH3-containing proteins that do not bind to canonical XPXXP-containing peptides, and that establish distinct interactions in the signaling network.