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InterPro is an integrated resource for protein families, domains and functional sites, which integrates the following protein signature databases: PROSITE, PRINTS, ProDom, Pfam, SMART, TIGRFAMs, PIRSF, SUPERFAMILY, Gene3D and PANTHER. The latter two new member databases have been integrated since the last publication in this journal. There have been several new developments in InterPro, including an additional reading field, new database links, extensions to the web interface and additional match XML files. InterPro has always provided matches to UniProtKB proteins on the website and in the match XML file on the FTP site. Additional matches to proteins in UniParc (UniProt archive) are now available for download in the new match XML files only. The latest InterPro release (13.0) contains more than 13 000 entries, covering over 78% of all proteins in UniProtKB. The database is available for text- and sequence-based searches via a webserver (http://www.ebi.ac.uk/interpro), and for download by anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro). The InterProScan search tool is now also available via a web service at http://www.ebi.ac.uk/Tools/webservices/WSInterProScan.html.

InterPro, an integrated documentation resource for protein families, protein domains, and functional sites, was developed to amalgamate the individual efforts of the PROSITE, PRINTS, Pfam, and ProDom databases. InterPro can be used for the computational functional classification of newly determined amino acid sequences that lack biochemical characterization and for comparative genome analysis. InterPro contains over 3500 entries for more than 1 000 000 hits in SWISS-PROT and TrEMBL. The database is accessible for text-and sequence-based searches at http://www.ebi.ac.uk/interpro/. InterPro was used for the complete analysis of the proteome of the pathogenic microorganism Mycobacterium tuberculosis and the comparison with the predicted protein-coding sequences of the complete genomes of Bacillus subtilis and Escherichia coli. It was found that 64.8% of proteins in the proteome of M. tuberculosis matched InterPro entries and can be classified by their functions. The comparison with B. subtilis and E. coli provided information on the most common protein families and domains and on the most highly represented protein families in each organism. Thus, InterPro is a useful tool for general comparison of complete proteomes and their compositions.

InterPro, an integrated documentation resource of protein families, domains and functional sites, was created in 1999 as a means of amalgamating the major protein signature databases into one comprehensive resource. PROSITE, Pfam, PRINTS, ProDom, SMART and TIGRFAMs have been manually integrated and curated and are available in InterPro for text- and sequence-based searching. The results are provided in a single format that rationalises the results that would be obtained by searching the member databases individually. The latest release of InterPro contains 5629 entries describing 4280 families, 1239 domains, 95 repeats and 15 post-translational modifications. Currently, the combined signatures in InterPro cover more than 74% of all proteins in SWISS-PROT and TrEMBL, an increase of nearly 15% since the inception of InterPro. New features of the database include improved searching capabilities and enhanced graphical user interfaces for visualisation of the data. The database is available via a webserver (http://www.ebi.ac.uk/interpro) and anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro).

We have undertaken the first comparative pilot gene discovery analysis of approximately 25,000 random genomic and expressed sequence tags (ESTs) from three species of Plasmodium, the infectious agent that causes malaria. A total of 5482 genome survey sequences (GSSs) and 5582 ESTs were generated from mung bean nuclease (MBN) and cDNA libraries, respectively, of the ANKA line of the rodent malaria parasite Plasmodium berghei, and 10,874 GSSs generated from MBN libraries of the Salvador I and Belem lines of Plasmodium vivax, the most geographically wide-spread human malaria pathogen. These tags, together with 2438 Plasmodium falciparum sequences present in GenBank, were used to perform first-pass assembly and transcript reconstruction, and non-redundant consensus sequence datasets created. The datasets were compared against public protein databases and more than 1000 putative new Plasmodium proteins identified based on sequence similarity. Homologs of previously characterized Plasmodium genes were also identified, increasing the number of P. vivax and P. berghei sequences in public databases at least 10-fold. Comparative studies with other species of Apicomplexa identified interesting homologs of possible therapeutic or diagnostic value. A gene prediction program, Phat, was used to predict probable open reading frames for proteins in all three datasets. Predicted and non-redundant BLAST-matched proteins were submitted to InterPro, an integrated database of protein domains, signatures and families, for functional classification. Thus a partial predicted proteome was created for each species. This first comparative analysis of Plasmodium protein coding sequences represents a valuable resource for further studies on the biology of this important pathogen.

We consider the problem of biological complexity via a projection of protein-coding genes of complex organisms onto the functional space of the proteome. The latter can be defined as a set of all functions committed by proteins of an organism. Alternative splicing (AS) allows an organism to generate diverse mature RNA transcripts from a single mRNA strand and thus it could be one of the key mechanisms of increasing of functional complexity of the organism's proteome and a driving force of biological evolution. Thus, the projection of transcription units (TU) and alternative splice-variant (SV) forms onto proteome functional space could generate new types of relational networks (e.g. SV-protein function networks, SFN) and lead to discoveries of novel evolutionarily conservative functional modules. Such types of networks might provide new reliable characteristics of organism complexity and a better understanding of the evolutionary integration and plasticity of interconnection of genome-transcriptome-proteome functions. Results We use the InterPro and UniProt databases to attribute descriptive features (keywords) to protein sequences. UniProt database includes a controlled and curated vocabulary of specific descriptors or keywords. The keywords have been assigned to a protein sequence via conserved domains or via similarity with annotated sequences. Then we consider the unique combinations of keywords as the protein functional labels (FL), which characterize the biological functions of the given protein and construct the contingency tables and graphs providing the projections of transcription units (TU) and alternative splice-variants (SV) onto all FL of the proteome of a given organism. We constructed SFNs for organisms with different evolutionary history and levels of complexity, and performed detailed statistical parameterization of the networks. Conclusions The application of the algorithm to organisms with different evolutionary history and level of biological complexity (nematode, fruit fly, vertebrata) reveals that the parameters describing SFN correlate with the complexity of a given organism. Using statistical analysis of the links of the functional networks, we propose new features of evolution of protein function acquisition. We reveal a group of genes and corresponding functions, which could be attributed to an early conservative part of the cellular machinery essential for cell viability and survival. We identify and provide characteristics of functional switches in the polyform group of TUs in different organisms. Based on comparison of mouse and human SFNs, a role of alternative splicing as a necessary source of evolution towards more complex organisms is demonstrated. The entire set of FL across many organisms could be used as a draft of the catalogue of the functional space of the proteome world.

The entire protein domain set of the proteome of an organism we call the domainome. We define the list of domains in domainome, together with the numbers of their occurrences (links to proteins) found in the proteome to be the domain-to-protein linkage profile (DPLP). We estimated the DPLP of the proteomes of the 156 complete genomes represented in the InterPro database. This work presents several quantitative measures of the complexity of a proteome based on the DPLP. For each of the 156 studied genomes, we found two large sets of domains: D1, the domains that are not replicated within any protein of the proteome and D2, the domains that occur two or more times in at least one protein of the proteome. Statistics of the observed domain-to-protein links (DPLs) for set D1 and set D2 do not exhibit simple ‘scale-free network’ properties: for D1, the distribution of DPLs in proteome follows the Generalized Discrete Pareto function and for D2, the distribution of DPLs in proteome follows the inversed gamma probability function. Dynamical range of DPLs for D1 domains is larger than for D2 domains, and this range correlates with biological complexity of organism. D1 and D2 sets exhibit significant differences of molecular functions of the corresponding proteins, biological processes, and cellular components. The statistical distributions of the number of DPLs in the proteome and the estimates of the differences between the DPLPs for pairs of organisms are used as measures of relative biological complexity of the organisms. In particular, we show quantitatively the greater domain composition complexity of the human proteins relative to that of a mouse or a rat.

Integr8 is a new web portal for exploring the biology of organisms with completely deciphered genomes. For over 190 species, Integr8 provides access to general information, recent publications, and a detailed statistical overview of the genome and proteome of the organism. The preparation of this analysis is supported through Genome Reviews, a new database of bacterial and archaeal DNA sequences in which annotation has been upgraded (compared to the original submission) through the integration of data from many sources, including the EMBL Nucleotide Sequence Database, the UniProt Knowledgebase, InterPro, CluSTr, GOA and HOGENOM. Integr8 also allows the users to customize their own interactive analysis, and to download both customized and prepared datasets for their own use. Integr8 is available at http://www.ebi.ac.uk/integr8.

International audience; InterPro, an integrated documentation resource of protein families, domains and functional sites, was created to integrate the major protein signature databases. Currently, it includes PROSITE, Pfam, PRINTS, ProDom, SMART, TIGRFAMs, PIRSF and SUPERFAMILY. Signatures are manually integrated into InterPro entries that are curated to provide biological and functional information. Annotation is provided in an abstract, Gene Ontology mapping and links to specialized databases. New features of InterPro include extended protein match views, taxonomic range information and protein 3D structure data. One of the new match views is the InterPro Domain Architecture view, which shows the domain composition of protein matches. Two new entry types were introduced to better describe InterPro entries: these are active site and binding site. PIRSF and the structure-based SUPERFAMILY are the latest member databases to join InterPro, and CATH and PANTHER are soon to be integrated. InterPro release 8.0 contains 11 007 entries, representing 2573 domains, 8166 families, 201 repeats, 26 active sites, 21 binding sites and 20 post-translational modification sites. InterPro covers over 78% of all proteins in the Swiss-Prot and TrEMBL components of UniProt. The database is available for text- and sequence-based searches via a webserver (http://www.ebi.ac.uk/interpro), and for download by anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro).

The aim of this work is to use a supervised learning approach to identify sets of motif-based sequence characteristics, combinations of which can give the most accurate annotation of new proteins. We assess several of InterPro Consortium member databases for their informativeness for the annotation of full-length protein sequences. Thus, our study addresses the problem of integrating biological information from various resources. Decision-rule algorithms are used to cross-map different biological classification systems in order to optimise the process of functional annotation of protein sequences. Various features (e.g., keywords, GO terms, structural complex names) may be assigned to a sequence via its characteristics (e.g., motifs built by various protein sequence analysis methods) with the developed approach. We chose SwissProt keywords as the set of features on which to perform our analysis. From the presented results one can quickly obtain the best combinations of methods appropriate for the description of a given class of proteins.

A general overview of the protein sequence set for the mouse transcriptome produced during the FANTOM2 sequencing project is presented here. We applied different algorithms to characterize protein sequences derived from a nonredundant representative protein set (RPS) and a variant protein set (VPS) of the mouse transcriptome. The functional characterization and assignment of Gene Ontology terms was done by analysis of the proteome using InterPro. The Superfamily database analyses gave a detailed structural classification according to SCOP and provide additional evidence for the functional characterization of the proteome data. The MDS database analysis revealed new domains which are not presented in existing protein domain databases. Thus the transcriptome gives us a unique source of data for the detection of new functional groups. The data obtained for the RPS and VPS sets facilitated the comparison of different patterns of protein expression. A comparison of other existing mouse and human protein sequence sets (e.g., the International Protein Index) demonstrates the common patterns in mammalian proteomes. The analysis of the membrane organization within the transcriptome of multiple eukaryotes provides valuable statistics about the distribution of secretory and transmembrane proteins

The Proteome Analysis database (http://www.ebi.ac.uk/proteome/) has been developed by the Sequence Database Group at EBI utilizing existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archeae and eukaryotes. Three main projects are used, InterPro, CluSTr and GO Slim, to give an overview on families, domains, sites, and functions of the proteins from each of the complete genomes. Complete proteome analysis is available for a total of 89 proteome sets. A specifically designed application enables InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

The applications of InterPro span a range of biologically important areas that includes automatic annotation of protein sequences and genome analysis. In automatic annotation of protein sequences InterPro has been utilised to provide reliable characterisation of sequences, identifying them as candidates for functional annotation. Rules based on the InterPro characterisation are stored and operated through a database called RuleBase. RuleBase is used as the main tool in the sequence database group at the EBI to apply automatic annotation to unknown sequences. The annotated sequences are stored and distributed in the TrEMBL protein sequence database. InterPro also provides a means to carry out statistical and comparative analyses of whole genomes. In the Proteome Analysis Database, InterPro analyses have been combined with other analyses based on CluSTr, the Gene Ontology (GO) and structural information on the proteins.

InterPro (http://www.ebi.ac.uk/interpro/) is an integrated documentation resource for protein families, domains and sites, developed initially as a means of rationalizing the complementary efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. It is a useful resource that aids the functional classification of proteins. Almost 90% of the actinopterygii protein sequences from SWISS-PROT and TrEMBL can be classified using InterPro. Over 30% of the actinopterygii protein sequences currently in SWISS-PROT and TrEMBL are of mitochondrial origin, the majority of which belong to the cytochrome b/b6 family. InterPro also gives insights into the domain composition of the classified proteins and has applications in the functional classification of newly determined sequences lacking biochemical characterization, and in comparative genome analysis. A comparison of the actinopterygii protein sequences against the sequences of other eukaryotes confirms the high representation of eukaryotic protein kinase in the organisms studied. The comparisons also show that, based on InterPro families, the trans-species evolution of MHC class I and II molecules in mammals and teleost fish can be recognized.

Signature databases are vital tools for identifying distant relationships in novel sequences and hence for inferring protein function. InterPro is an integrated documentation resource for protein families, domains and functional sites, which amalgamates the efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. Each InterPro entry includes a functional description, annotation, literature references and links back to the relevant member database(s). Release 2.0 of InterPro (October 2000) contains over 3000 entries, representing families, domains, repeats and sites of post-translational modification encoded by a total of 6804 different regular expressions, profiles, fingerprints and Hidden Markov Models. Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1 000 000 hits from 462 500 proteins in SWISS-PROT and TrEMBL). The database is accessible for text- and sequence-based searches at http://www.ebi.ac.uk/interpro/. Questions can be emailed to interhelp@ebi.ac.uk.

The SWISS-PROT group at EBI has developed the Proteome Analysis Database utilising existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archaea and eukaryotes (http://www.ebi.ac.uk/proteome/). The two main projects used, InterPro and CluSTr, give a new perspective on families, domains and sites and cover 31–67% (InterPro statistics) of the proteins from each of the complete genomes. CluSTr covers the three complete eukaryotic genomes and the incomplete human genome data. The Proteome Analysis Database is accompanied by a program that has been designed to carry out InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

Motivation: The SWISS-PROT group at the EBI has developed the Proteome Analysis Database utilizing existing resources and providing comprehensive and integrated comparative analysis of the predicted protein coding sequencesof the complete genomes of bacteria, archaea and eukaryotes. The Proteome Analysis Database is accompanied by a program that has been designed to carry out interactive InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database. Availability: http://www.ebi.ac.uk/proteome/comparisons.html Contact: alex@ebi.ac.uk; proteome@ebi.ac.uk * To whom all correspondence should be addressed.