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/     

Progress with the PRINTS protein fingerprint database.

PRINTS is a compendium of protein motif 'fingerprints' derived from the OWL composite sequence database. Fingerprints are groups of motifs within sequence alignments whose conserved nature allows them to be used as signatures of family membership. To date, 400 fingerprints have been constructed and stored in Prints, the size of which has doubled in the last year. The current version, 9.0, encodes approximately 2000 motifs, covering a range of globular and membrane proteins, modular polypeptides, and so on. Fingerprints inherently offer improved diagnostic reliability over single motif methods by virtue of the mutual context provided by motif neighbours. PRINTS thus provides a useful adjunct to the widely used PROSITE dictionary of patterns. The database is now accessible via the Database Browser on the UCL Bioinformatics server at http://www.biochem.ucl.ac.uk/bsm/dbbrowser .     

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 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.     

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.     

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.     

DSEARCH: sensitive database searching using distributed computing

SUMMARY: We present a distributed and fully cross-platform database search program that allows the user to utilize the idle clock cycles of machines to perform large searches using the most sensitive algorithms. For those in an academic or corporate environment with hundreds of idle desktop machines, DSEARCH can deliver a 'free' database search supercomputer. AVAILABILITY: The software is publicly available under the GNU general public licence from http://www.cs.may.ie/distributed CONTACT: tom.naughton@may.ie SUPPLEMENTARY INFORMATION: Full documentation and a user manual is available from http://www.cs.may.ie/distributed.     

Defining parameters for homology-tolerant database searching.

De novo interpretation of tandem mass spectrometry (MS/MS) spectra provides sequences for searching protein databases when limited sequence information is present in the database. Our objective was to define a strategy for this type of homology-tolerant database search. Homology searches, using MS-Homology software, were conducted with 20, 10, or 5 of the most abundant peptides from 9 proteins, based either on precursor trigger intensity or on total ion current, and allowing for 50%, 30%, or 10% mismatch in the search. Protein scores were corrected by subtracting a threshold score that was calculated from random peptides. The highest (p < .01) corrected protein scores (i.e., above the threshold) were obtained by submitting 20 peptides and allowing 30% mismatch. Using these criteria, protein identification based on ion mass searching using MS/MS data (i.e., Mascot) was compared with that obtained using homology search. The highest-ranking protein was the same using Mascot, homology search using the 20 most intense peptides, or homology search using all peptides, for 63.4% of 112 spots from two-dimensional polyacrylamide gel electrophoresis gels. For these proteins, the percent coverage was greatest using Mascot compared with the use of all or just the 20 most intense peptides in a homology search (25.1%, 18.3%, and 10.6%, respectively). Finally, 35% of de novo sequences completely matched the corresponding known amino acid sequence of the matching peptide. This percentage increased when the search was limited to the 20 most intense peptides (44.0%). After identifying the protein using MS-Homology, a peptide mass search may increase the percent coverage of the protein identified.     

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.     

Understanding the improved sensitivity of spectral library searching over sequence database searching in proteomics data analysis

Spectral library searching has been recently proposed as an alternative to sequence database searching for peptide identification from MS/MS. We performed a systematic comparison between spectral library searching and sequence database searching using a wide variety of data to better demonstrate, and understand, the superior sensitivity of the former observed in preliminary studies. By decoupling the effect of search space, we demonstrated that the success of spectral library searching is primarily attributable to the use of real library spectra for matching, without which the sensitivity advantage largely disappears. We further determined the extent to which the use of real peak intensities and non-canonical fragments, both under-utilized information in sequence database searching, contributes to the sensitivity advantage. Lastly, we showed that spectral library searching is disproportionately more successful in identifying low-quality spectra, and complex spectra of higher- charged precursors, both important frontiers in peptide sequencing. Our results answered important outstanding questions about this promising yet unproven method using well-controlled computational experiments and sound statistical approaches.     

GOfetcher: a database with complex searching facility for gene ontology

MOTIVATION: An important contribution to the Gene Ontology (GO) project is to develop tools that facilitate the creation, maintenance and use of ontologies. Several tools have been created for communicating and using the GO project. However, a limitation with most of these tools is that they suffer from lack of a comprehensive search facility. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: 'Quick Search', 'Advanced Search' and 'Upload Files' for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating GO information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values and the extensible markup language (XML) format. The database is available at http://mcbc.usm.edu/gofetcher/.     

Disperse: a simple and efficient approach to parallel database searching

SUMMARY: A general system for performing multiple independent database searches in parallel is presented. Run-time addition and removal of clients, robust failure and error trapping and near 100% efficiency with very large numbers of clients are achieved by a flexible asynchronous, client-driven approach.     

Automated assembly of protein blocks for database searching.

A system is described for finding and assembling the most highly conserved regions of related proteins for database searching. First, an automated version of Smith's algorithm for finding motifs is used for sensitive detection of multiple local alignments. Next, the local alignments are converted to blocks and the best set of non-overlapping blocks is determined. When the automated system was applied successively to all 437 groups of related proteins in the PROSITE catalog, 1764 blocks resulted; these could be used for very sensitive searches of sequence databases. Each block was calibrated by searching the SWISS-PROT database to obtain a measure of the chance distribution of matches, and the calibrated blocks were concatenated into a database that could itself be searched. Examples are provided in which distant relationships are detected either using a set of blocks to search a sequence database or using sequences to search the database of blocks. The practical use of the blocks database is demonstrated by detecting previously unknown relationships between oxidoreductases and by evaluating a proposed relationship between HIV Vif protein and thiol proteases.     

Real-time structural motif searching in proteins using an inverted index strategy

Biochemical and biological functions of proteins are the product of both the overall fold of the polypeptide chain, and, typically, structural motifs made up of smaller numbers of amino acids constituting a catalytic center or a binding site that may be remote from one another in amino acid sequence. Detection of such structural motifs can provide valuable insights into the function(s) of previously uncharacterized proteins. Technically, this remains an extremely challenging problem because of the size of the Protein Data Bank (PDB) archive. Existing methods depend on a clustering by sequence similarity and can be computationally slow. We have developed a new approach that uses an inverted index strategy capable of analyzing >170,000 PDB structures with unmatched speed. The efficiency of the inverted index method depends critically on identifying the small number of structures containing the query motif and ignoring most of the structures that are irrelevant. Our approach (implemented at motif.rcsb.org) enables real-time retrieval and superposition of structural motifs, either extracted from a reference structure or uploaded by the user. Herein, we describe the method and present five case studies that exemplify its efficacy and speed for analyzing 3D structures of both proteins and nucleic acids.     

Design of novel nicotinic ligands through 3D database searching

A series of quinoline derivatives have been designed on the basis of results from a 3D search of the Cambridge Structural Database using the nicotinic pharmacophore as a query and further modified using molecular modeling. Some of the synthesized compounds show nanomolar affinity for the central nicotinic receptor on rat cerebral cortex.     

PROSITE: a documented database using patterns and profiles as motif descriptors

Among the various databases dedicated to the identification of protein families and domains, PROSITE is the first one created and has continuously evolved since. PROSITE currently consists of a large collection of biologically meaningful motifs that are described as patterns or profiles, and linked to documentation briefly describing the protein family or domain they are designed to detect. The close relationship of PROSITE with the SWISS-PROT protein database allows the evaluation of the sensitivity and specificity of the PROSITE motifs and their periodic reviewing. In return, PROSITE is used to help annotate SWISS-PROT entries. The main characteristics and the techniques of family and domain identification used by PROSITE are reviewed in this paper.     

ANDY: a general, fault-tolerant tool for database searching on computer clusters

SUMMARY: ANDY (seArch coordination aND analYsis) is a set of Perl programs and modules for distributing large biological database searches, and in general any sequence of commands, across the nodes of a Linux computer cluster. ANDY is compatible with several commonly used distributed resource management (DRM) systems, and it can be easily extended to new DRMs. A distinctive feature of ANDY is the choice of either dedicated or fair-use operation: ANDY is almost as efficient as single-purpose tools that require a dedicated cluster, but it runs on a general-purpose cluster along with any other jobs scheduled by a DRM. Other features include communication through named pipes for performance, flexible customizable routines for error-checking and summarizing results, and multiple fault-tolerance mechanisms. Availability: ANDY is freely available and can be obtained from http://compbio.berkeley.edu/proj/andy. SUPPLEMENTARY INFORMATION: Supplemental data, figures, and a more detailed overview of the software are found at http://compbio.berkeley.edu/proj/andy.     

Membrane protein identification: N-terminal labeling of nontryptic membrane protein peptides facilitates database searching

Membrane proteins are fairly refractory to digestion especially by trypsin, and less specific proteases, such as elastase and pepsin, are much more effective. However, database searching using nontryptic peptides is much less effective because of the lack of charge localization at the N and C termini and the absence of sequence specificity. We describe a method for N-terminal-specific labeling of peptides from nontryptic digestions of membrane proteins, which facilitates Mascot database searching and can be used for relative quantitation. The conditions for digestion have been optimized to obtain peptides of a suitable length for mass spectrometry (MS) fragmentation. We show the effectiveness of the method using a plasma membrane preparation from a leukemia cell line and demonstrate a large increase in the number of membrane proteins, with small extra-membranar domains being identified in comparison to previous published methods.     

Mass accuracy and sequence requirements for protein database searching.

To elucidate the role of high mass accuracy in mass spectrometric peptide mapping and database searching, selected proteins were subjected to tryptic digestion and the resulting mixtures were analyzed by electrospray ionization on a 7 Tesla Fourier transform mass spectrometer with a mass accuracy of 1 ppm. Two extreme cases were examined in detail: equine apomyoglobin, which digested easily and gave very few spurious masses, and bovine alpha-lactalbumin, which under the conditions used, gave many spurious masses. The effectiveness of accurate mass measurements in minimizing false protein matches was examined by varying the mass error allowed in the search over a wide range (2-500 ppm). For the "clean" data obtained from apomyoglobin, very few masses were needed to return valid protein matches, and the mass error allowed in the search had little effect up to 500 ppm. However, in the case of alpha-lactalbumin more mass values were needed, and low mass errors increased the search specificity. Mass errors below 30 ppm were particularly useful in eliminating false protein matches when few mass values were used in the search. Collision-induced dissociation of an unassigned peak in the alpha-lactalbumin digest provided sufficient data to unambiguously identify the peak as a fragment from alpha-lactalbumin and eliminate a large number of spurious proteins found in the peptide mass search. The results show that even with a relatively high mass error (0.8 Da for mass differences between singly charged product ions), collision-induced dissociation can help identify proteins in cases where unfavorable digest conditions or modifications render digest peaks unidentifiable by a simple mass mapping search.