Novel developments with the PRINTS protein fingerprint database.

The PRINTS database of protein family 'fingerprints' is a diagnostic resource that complements the PROSITE dictionary of sites and patterns. Unlike regular expressions, fingerprints exploit groups of conserved motifs within sequence alignments to build characteristic signatures of family membership. Thus fingerprints inherently offer improved diagnostic reliability by virtue of the mutual context provided by motif neighbours. To date, 600 fingerprints have been constructed and stored in PRINTS, representing a 50% increase in the size of the database in the last year. The current version, 13.0, encodes approximately 3000 motifs, covering a range of globular and membrane proteins, modular polypeptides, and so on. The database is accessible via UCL's Bioinformatics World Wide Web (WWW) server at http://www.biochem.ucl.ac.uk/bsm/dbbrowser / . We describe here progress with the database, its Web interface, and a recent exciting development: the integration of a novel colour alignment editor (http://www.biochem.ucl.ac.uk/bsm/dbbrowser++ +/CINEMA ), which allows visualisation and interactive manipulation of PRINTS alignments over the Internet.     

The PRINTS protein fingerprint database in its fifth year.

PRINTS is a database of protein family 'fingerprints' offering a diagnostic resource for newly-determined sequences. By contrast with PROSITE, which uses single consensus expressions to characterise particular families, PRINTS exploits groups of motifs to build characteristic signatures. These signatures offer improved diagnostic reliability by virtue of the mutual context provided by motif neighbours. To date, 800 fingerprints have been constructed and stored in PRINTS. The current version, 17.0, encodes approximately 4500 motifs, covering a range of globular and membrane proteins, modular polypeptides, and so on. The database is accessible via the UCL Bioinformatics World Wide Web (WWW) Server at http://www. biochem.ucl.ac.uk/bsm/dbbrowser/ . We have recently enhanced the usefulness of PRINTS by making available new, intuitive search software. This allows both individual query sequence and bulk data submission, permitting easy analysis of single sequences or complete genomes. Preliminary results indicate that use of the PRINTS system is able to assign additional functions not found by other methods, and hence offers a useful adjunct to current genome analysis protocols.     

The PRINTS database: a resource for identification of protein families

The PRINTS database houses a collection of protein fingerprints, which may be used to assign family and functional attributes to uncharacterised sequences, such as those currently emanating from the various genome-sequencing projects. The April 2002 release includes 1,700 family fingerprints, encoding approximately 10,500 motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. Fingerprints are groups of conserved motifs that, taken together, provide diagnostic protein family signatures. They derive much of their potency from the biological context afforded by matching motif neighbours; this makes them at once more flexible and powerful than single-motif approaches. The technique further departs from other pattern-matching methods by readily allowing the creation of fingerprints at superfamily-, family- and subfamily-specific levels, thereby allowing more fine-grained diagnoses. Here, we provide an overview of the method of protein fingerprinting and how the results of fingerprint analyses are used to build PRINTS and its relational cousin, PRINTS-S.     

PRINTS-S: the database formerly known as PRINTS

The PRINTS database houses a collection of protein family fingerprints. These are groups of motifs that together are diagnostically more potent than single motifs by virtue of the biological context afforded by matching motif neighbours. Around 1200 fingerprints have now been created and stored in the database. The September 1999 release (version 24.0) encodes approximately 7200 motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. In addition to its continued steady growth, we report here several major changes to the resource, including the design of an automated strategy for database maintenance, and implementation of an object-relational schema for more efficient data management. The database is accessible for BLAST, fingerprint and text searches at http://www.bioinf.man.ac. uk/dbbrowser/PRINTS/     

FingerPRINTScan: intelligent searching of the PRINTS motif database

MOTIVATION: By identifying an unknown gene or protein as a member of a known family, we can infer a wealth of previously compiled information pertinent to that family and its members. RESULTS: This paper introduces a method that classifies sequences using familial definitions from the PRINTS database, allowing progress to be made with the identification of distant evolutionary relationships. The approach makes use of the contextual information inherent in a multiple-motif method, and has the power to identify hitherto unidentified relationships in mass genome data. We exemplify our method by a comparison of database searches with uncharacterized sequences from the Caenorhabditis elegans and Saccharomyces cerevisiae genome projects. This analysis tool combines a simple, user-friendly interface with the capacity to provide an 'intelligent', biologically relevant result.     

PRINTS and PRINTS-S shed light on protein ancestry

The PRINTS database houses a collection of protein fingerprints. These may be used to make family and tentative functional assignments for uncharacterised sequences. The September 2001 release (version 32.0) includes 1600 fingerprints, encoding ~10 000 motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. In addition to its continued steady growth, we report here its use as a source of annotation in the InterPro resource, and the use of its relational cousin, PRINTS-S, to model relationships between families, including those beyond the reach of conventional sequence analysis approaches. The database is accessible for BLAST, fingerprint and text searches at http://www.bioinf.man.ac.uk/dbbrowser/PRINTS/.     

PRINTS prepares for the new millennium.

PRINTS is a diagnostic collection of protein fingerprints. Fingerprints exploit groups of motifs to build characteristic family signatures, offering improved diagnostic reliability over single-motif approaches by virtue of the mutual context provided by motif neighbours. Around 1000 fingerprints have now been created and stored in PRINTS. The September 1998 release (version 20.0), encodes approximately 5700 motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. The database is accessible via the DbBrowser Web Server at http://www.biochem.ucl.ac.uk/bsm/dbbrowser /. In addition to supporting its continued growth, recent enhancements to the resource include a BLAST server, and more efficient fingerprint search software, with improved statistics for estimating the reliability of retrieved matches. Current efforts are focused on the design of more automated methods for database maintenance; implementation of an object-relational schema for efficient data management; and integration with PROSITE, profiles, Pfam and ProDom, as part of the international InterPro project, which aims to unify protein pattern databases and offer improved tools for genome analysis.     

Topology fingerprint approach to the inverse protein folding problem.

We describe the most general solution to date of the problem of matching globular protein sequences to the appropriate three-dimensional structures. The screening template, against which sequences are tested, is provided by a protein "structural fingerprint" library based on the contact map and the buried/exposed pattern of residues. Then, a lattice Monte Carlo algorithm validates or dismisses the stability of the proposed fold. Examples of known structural similarities between proteins having weakly or unrelated sequences such as the globins and phycocyanins, the eight-member alpha/beta fold of triose phosphate isomerase and even a close structural equivalence between azurin and immunoglobulins are found.     

Associative database of protein sequences.

MOTIVATION: We present a new concept that combines data storage and data analysis in genome research, based on an associative network memory. As an illustration, 115 000 conserved regions from over 73 000 published sequences (i.e. from the entire annotated part of the SWISSPROT sequence database) were identified and clustered by a self-organizing network. Similarity and kinship, as well as degree of distance between the conserved protein segments, are visualized as neighborhood relationship on a two-dimensional topographical map. RESULTS: Such a display overcomes the restrictions of linear list processing and allows local and global sequence relationships to be studied visually. Families are memorized as prototype vectors of conserved regions. On a massive parallel machine, clustering and updating of the database take only a few seconds; a rapid analysis of incoming data such as protein sequences or ESTs is carried out on present-day workstations. AVAILABILITY: Access to the database is available at http://www.bioinf.mdc-berlin.de/unter2.html++ + CONTACT: (hanke,lehmann,reich)@mdc-berlin.de; bork@embl-heidelberg.de     

Extracting protein alignment models from the sequence database.

Biologists often gain structural and functional insights into a protein sequence by constructing a multiple alignment model of the family. Here a program called Probe fully automates this process of model construction starting from a single sequence. Central to this program is a powerful new method to locate and align only those, often subtly, conserved patterns essential to the family as a whole. When applied to randomly chosen proteins, Probe found on average about four times as many relationships as a pairwise search and yielded many new discoveries. These include: an obscure subfamily of globins in the roundworm Caenorhabditis elegans ; two new superfamilies of metallohydrolases; a lipoyl/biotin swinging arm domain in bacterial membrane fusion proteins; and a DH domain in the yeast Bud3 and Fus2 proteins. By identifying distant relationships and merging families into superfamilies in this way, this analysis further confirms the notion that proteins evolved from relatively few ancient sequences. Moreover, this method automatically generates models of these ancient conserved regions for rapid and sensitive screening of sequences.     

PRINTS--a database of protein motif fingerprints.

PRINTS is a compendium of protein motif 'fingerprints'. A fingerprint is defined as a group of motifs excised from conserved regions of a sequence alignment, whose diagnostic power or potency is refined by iterative databasescanning (in this case the OWL composite sequence database). Generally, the motifs do not overlap, but are separated along a sequence, though they may be contiguous in 3D-space. The use of groups of independent, linearly- or spatially-distinct motifs allows protein folds and functionalities to be characterised more flexibly and powerfully than conventional single-component patterns or regular expressions. The current version of the database contains 200 entries (encoding 950 motifs), covering a wide range of globular and membrane proteins, modular polypeptides, and so on. The growth of the databaseis influenced by a number of factors; e.g. the use of multiple motifs; the maximisation of sequence information through iterative database scanning; and the fact that the database searched is a large composite. The information contained within PRINTS is distinct from, but complementary to the consensus expressions stored in the widely-used PROSITE dictionary of patterns.     

OWL--a non-redundant composite protein sequence database.

A comprehensive, non-redundant composite protein sequence database is described. The database, OWL, is an amalgam of data from six publicly-available primary sources, and is generated using strict redundancy criteria. The database is updated monthly and its size has increased almost eight-fold in the last six years: the current version contains > 76,000 entries. For added flexibility, OWL is distributed with a tailor-made query language, together with a number of programs for database exploration, information retrieval and sequence analysis, which together form an integrated database and software resource for protein sequences.     

A database of protein structure families with common folding motifs.

The availability of fast and robust algorithms for protein structure comparison provides an opportunity to produce a database of three-dimensional comparisons, called families of structurally similar proteins (FSSP). The database currently contains an extended structural family for each of 154 representative (below 30% sequence identity) protein chains. Each data set contains: the search structure; all its relatives with 70-30% sequence identity, aligned structurally; and all other proteins from the representative set that contain substructures significantly similar to the search structure. Very close relatives (above 70% sequence identity) rarely have significant structural differences and are excluded. The alignments of remote relatives are the result of pairwise all-against-all structural comparisons in the set of 154 representative protein chains. The comparisons were carried out with each of three novel automatic algorithms that cover different aspects of protein structure similarity. The user of the database has the choice between strict rigid-body comparisons and comparisons that take into account interdomain motion or geometrical distortions; and, between comparisons that require strictly sequential ordering of segments and comparisons, which allow altered topology of loop connections or chain reversals. The data sets report the structurally equivalent residues in the form of a multiple alignment and as a list of matching fragments to facilitate inspection by three-dimensional graphics. If substructures are ignored, the result is a database of structure alignments of full-length proteins, including those in the twilight zone of sequence similarity.(ABSTRACT TRUNCATED AT 250 WORDS)     

Searching the protein sequence database

As the volume of protein sequence data grows, rapid methods for searching the protein sequence database become of primary importance. Rigorous comparison of sequences is obtained with the well-known dynamic programming algorithms. However, these algorithms are not rapid enough to use for routinely searching the entire database. In this paper we discuss some methods that can be used for rapid searches.     

PFDB: a generic protein family database integrating the CATH domain structure database with sequence based protein family resources

MOTIVATION: The PFDB (Protein Family Database) is a new database designed to integrate protein family-related data with relevant functional and genomic data. It currently manages biological data for three projects-the CATH protein domain database (Orengo et al., 1997; Pearl et al., 2001), the VIDA virus domains database (Albà et al., 2001) and the Gene3D database (Buchan et al., 2001). The PFDB has been designed to accommodate protein families identified by a variety of sequence based or structure based protocols and provides a generic resource for biological research by enabling mapping between different protein families and diverse biochemical and genetic data, including complete genomes. RESULTS: A characteristic feature of the PFDB is that it has a number of meta-level entities (for example aggregation, collection and inclusion) represented as base tables in the final design. The explicit representation of relationships at the meta-level has a number of advantages, including flexibility-both in terms of the range of queries that can be formulated and the ability to integrate new biological entities within the existing design. A potential drawback with this approach-poor performance caused by the number of joins across meta-level tables-is avoided by implementing the PFDB with materialized views using the mature relational database technology of Oracle 8i. The resultant database is both fast and flexible. This paper presents the principles on which the database has been designed and implemented, and describes the current status of the database and query facilities supported.     

The ProDom database of protein domain families.

The ProDom database contains protein domain families generated from the SWISS-PROT database by automated sequence comparisons. It can be searched on the World Wide Web (http://protein.toulouse.inra. fr/prodom.html ) or by E-mail (prodom@toulouse.inra.fr) to study domain arrangements within known families or new proteins. Strong emphasis has been put on the graphical user interface which allows for interactive analysis of protein homology relationships. Recent improvements to the server include: ProDom search by keyword; links to PROSITE and PDB entries; more sensitive ProDom similarity search with BLAST or WU-BLAST; alignments of query sequences with homologous ProDom domain families; and links to the SWISS-MODEL server (http: //www.expasy.ch/swissmod/SWISS-MODEL.html ) for homology based 3-D domain modelling where possible.     

The HSSP database of protein structure-sequence alignments.

HSSP (homology-derived structures of proteins) is a derived database merging structural (2-D and 3-D) and sequence information (1-D). For each protein of known 3D structure from the Protein Data Bank, the database has a file with all sequence homologues, properly aligned to the PDB protein. Homologues are very likely to have the same 3D structure as the PDB protein to which they have been aligned. As a result, the database is not only a database of sequence aligned sequence families, but it is also a database of implied secondary and tertiary structures.     

The HSSP database of protein structure-sequence alignments.

HSSP is a derived database merging structural three dimensional (3-D) and sequence one dimensional(1-D) information. For each protein of known 3-D structure from the Protein Data Bank (PDB), the database has a multiple sequence alignment of all available homologues and a sequence profile characteristic of the family. The list of homologues is the result of a database search in Swissprot using a position-weighted dynamic programming method for sequence profile alignment (MaxHom). The database is updated frequently. The listed homologues are very likely to have the same 3-D structure as the PDB protein to which they have been aligned. As a result, the database is not only a database of aligned sequence families, but also a database of implied secondary and tertiary structures covering 27% of all Swissprot-stored sequences.     

SPiD: a subtilis protein interaction database.

MOTIVATION: Protein-protein interactions are a potential source of valuable clues in determining the functional role of as yet uncharacterized gene products in metabolic pathways. Graph-like structures emerging from the accumulation of interaction data make it difficult to maintain a consistent and global overview by hand. Bioinformatics tools are needed to perform this graph visualization while maintaining a link to the experimental data. RESULTS: "SPiD" is an online database for exploring networks of interacting proteins in Bacillus subtilis characterized by the two-hybrid system. Graphical displays of interaction networks are created dynamically as users interactively navigate through these networks. Third party applications can interface the database through a Common Object Request Broker Architecture (CORBA) tier. AVAILABILITY: SPiD is available through its web site at http://www-mig.versailles.inra.fr/bdsi/SPiD, and through an Interoperable Object Reference (IOR) and its associated Interface Definition Language (IDL). CONTACT: hoebeke@versailles.inra.fr     

The HSSP database of protein structure-sequence alignments.

HSSP is a derived database merging structural (3-D) and sequence (1-D) information. For each protein of known 3-D structure from the Protein Data Bank (PDB), the database has a multiple sequence alignment of all available homologues and a sequence profile characteristic of the family. The list of homologues is the result of a database search in SwissProt using a position-weighted dynamic programming method for sequence profile alignment (MaxHom). The database is updated frequently. The listed homologues are very likely to have the same 3-D structure as the PDB protein to which they have been aligned. As a result, the database is not only a database of aligned sequence families, but also a database of implied secondary and tertiary structures covering 29% of all SwissProt-stored sequences.