Elisabeth Gasteiger

Protein identification and analysis tools in the ExPASy server.

Protein identification and analysis software performs a central role in the investigation of proteins from two-dimensional (2-D) gels and mass spectrometry. For protein identification, the user matches certain empirically acquired information against a protein database to define a protein as already known or as novel. For protein analysis, information in protein databases can be used to predict certain properties about a protein, which can be useful for its empirical investigation. The two processes are thus complementary. Although there are numerous programs available for those applications, we have developed a set of original tools with a few main goals in mind. Specifically, these are: 1. To utilize the extensive annotation available in the Swiss-Prot database wherever possible, in particular the position-specific annotation in the Swiss-Prot feature tables to take into account posttranslational modifications and protein processing. 2. To develop tools specifically, but not exclusively, applicable to proteins prepared by two dimensional gel electrophoresis and peptide mass fingerprinting experiments. 3. To make all tools available on the World-Wide Web (WWW), and freely usable by the scientific community. In this chapter we give details about protein identification and analysis software that is available through the ExPASy World Wide Web server.

The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003

The SWISS-PROT protein knowledgebase (http://www.expasy.org/sprot/ and http://www.ebi.ac.uk/swissprot/) connects amino acid sequences with the current knowledge in the Life Sciences. Each protein entry provides an interdisciplinary overview of relevant information by bringing together experimental results, computed features and sometimes even contradictory conclusions. Detailed expertise that goes beyond the scope of SWISS-PROT is made available via direct links to specialised databases. SWISS-PROT provides annotated entries for all species, but concentrates on the annotation of entries from human (the HPI project) and other model organisms to ensure the presence of high quality annotation for representative members of all protein families. Part of the annotation can be transferred to other family members, as is already done for microbes by the High-quality Automated and Manual Annotation of microbial Proteomes (HAMAP) project. Protein families and groups of proteins are regularly reviewed to keep up with current scientific findings. Complementarily, TrEMBL strives to comprise all protein sequences that are not yet represented in SWISS-PROT, by incorporating a perpetually increasing level of mostly automated annotation. Researchers are welcome to contribute their knowledge to the scientific community by submitting relevant findings to SWISS-PROT at swiss-prot@expasy.org.

ExPASy: the proteomics server for in-depth protein knowledge and analysis

The ExPASy (the Expert Protein Analysis System) World Wide Web server (http://www.expasy.org), is provided as a service to the life science community by a multidisciplinary team at the Swiss Institute of Bioinformatics (SIB). It provides access to a variety of databases and analytical tools dedicated to proteins and proteomics. ExPASy databases include SWISS-PROT and TrEMBL, SWISS-2DPAGE, PROSITE, ENZYME and the SWISS-MODEL repository. Analysis tools are available for specific tasks relevant to proteomics, similarity searches, pattern and profile searches, post-translational modification prediction, topology prediction, primary, secondary and tertiary structure analysis and sequence alignment. These databases and tools are tightly interlinked: a special emphasis is placed on integration of database entries with related resources developed at the SIB and elsewhere, and the proteomics tools have been designed to read the annotations in SWISS-PROT in order to enhance their predictions. ExPASy started to operate in 1993, as the first WWW server in the field of life sciences. In addition to the main site in Switzerland, seven mirror sites in different continents currently serve the user community.

UniProt: the Universal Protein knowledgebase

To provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information, the Swiss-Prot, TrEMBL and PIR protein database activities have united to form the Universal Protein Knowledgebase (UniProt) consortium. Our mission is to provide a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and query interfaces. The central database will have two sections, corresponding to the familiar Swiss-Prot (fully manually curated entries) and TrEMBL (enriched with automated classification, annotation and extensive cross-references). For convenient sequence searches, UniProt also provides several non-redundant sequence databases. The UniProt NREF (UniRef) databases provide representative subsets of the knowledgebase suitable for efficient searching. The comprehensive UniProt Archive (UniParc) is updated daily from many public source databases. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). The scientific community is encouraged to submit data for inclusion in UniProt.

The Universal Protein Resource (UniProt): an expanding universe of protein information

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at or downloaded at .

ScanProsite: detection of PROSITE signature matches and ProRule-associated functional and structural residues in proteins

ScanProsite——is a new and improved version of the web-based tool for detecting PROSITE signature matches in protein sequences. For a number of PROSITE profiles, the tool now makes use of ProRules—context-dependent annotation templates—to detect functional and structural intra-domain residues. The detection of those features enhances the power of function prediction based on profiles. Both user-defined sequences and sequences from the UniProt Knowledgebase can be matched against custom patterns, or against PROSITE signatures. To improve response times, matches of sequences from UniProtKB against PROSITE signatures are now retrieved from a pre-computed match database. Several output modes are available including simple text views and a rich mode providing an interactive match and feature viewer with a graphical representation of results.

ExPASy: SIB bioinformatics resource portal

ExPASy (http://www.expasy.org) has worldwide reputation as one of the main bioinformatics resources for proteomics. It has now evolved, becoming an extensible and integrative portal accessing many scientific resources, databases and software tools in different areas of life sciences. Scientists can henceforth access seamlessly a wide range of resources in many different domains, such as proteomics, genomics, phylogeny/evolution, systems biology, population genetics, transcriptomics, etc. The individual resources (databases, web-based and downloadable software tools) are hosted in a ‘decentralized’ way by different groups of the SIB Swiss Institute of Bioinformatics and partner institutions. Specifically, a single web portal provides a common entry point to a wide range of resources developed and operated by different SIB groups and external institutions. The portal features a search function across ‘selected’ resources. Additionally, the availability and usage of resources are monitored. The portal is aimed for both expert users and people who are not familiar with a specific domain in life sciences. The new web interface provides, in particular, visual guidance for newcomers to ExPASy.

GlycoMod - A software tool for determining glycosylation compositions from mass spectrometric data

GlycoMod (http://www.expasy.ch/tools/glycomod/) is a software tool designed to find all possible compositions of a glycan structure from its experimentally determined mass. The program can be used to predict the composition of any glycoprotein‐derived oligosaccharide comprised of either underivatised, methylated or acetylated monosaccharides, or with a derivatised reducing terminus. The composition of a glycan attached to a peptide can be computed if the sequence or mass of the peptide is known. In addition, if the protein is known and is contained in the SWISS‐PROT or TrEMBL databases, the program will match the experimentally determined masses against all the predicted protease‐produced peptides (including any post‐translational modifications annotated in these databases) which have the potential to be glycosylated with either N‐ or O‐linked oligosaccharides. Since many possible glycan compositions can be generated from the same mass, the program can apply compositional constraints to the output if the user supplies either known or suspected monosaccharide constituents. Furthermore, known oligosaccharide structural constraints on monosaccharide composition are also incorporated into the program to limit the output.

The Sulfinator: predicting tyrosine sulfation sites in protein sequences.

UNLABELLED Protein tyrosine sulfation is an important post-translational modification of proteins that go through the secretory pathway. No clear-cut acceptor motif can be defined that allows the prediction of tyrosine sulfation sites in polypeptide chains. The Sulfinator is a software tool that can be used to predict tyrosine sulfation sites in protein sequences with an overall accuracy of 98%. Four different Hidden Markov Models were constructed, each of them specialized to recognize sulfated tyrosine residues depending on their location within the sequence: near the N-terminus, near the C-terminus, in the center of a window with a size of at least 25 amino acids, as well as in windows containing several tyrosine residues. AVAILABILITY The Sulfinator is accessible at (http://www.expasy.org/tools/sulfinator/). SUPPLEMENTARY INFORMATION Sulfinator documentation is accessible at (http://www.expasy.org/tools/sulfinator/sulfinator-doc.html).

Improving protein identification from peptide mass fingerprinting through a parameterized multi-level scoring algorithm and an optimized peak detection.

We have developed a new algorithm to identify proteins by means of peptide mass fingerprinting. Starting from the matrix‐assisted laser desorption/ionization‐time‐of‐flight (MALDI‐TOF) spectra and environmental data such as species, isoelectric point and molecular weight, as well as chemical modifications or number of missed cleavages of a protein, the program performs a fully automated identification of the protein. The first step is a peak detection algorithm, which allows precise and fast determination of peptide masses, even if the peaks are of low intensity or they overlap. In the second step the masses and environmental data are used by the identification algorithm to search in protein sequence databases (SWISS‐PROT and/or TrEMBL) for protein entries that match the input data. Consequently, a list of candidate proteins is selected from the database, and a score calculation provides a ranking according to the quality of the match. To define the most discriminating scoring calculation we analyzed the respective role of each parameter in two directions. The first one is based on filtering and exploratory effects, while the second direction focuses on the levels where the parameters intervene in the identification process. Thus, according to our analysis, all input parameters contribute to the score, however with different weights. Since it is difficult to estimate the weights in advance, they have been computed with a generic algorithm, using a training set of 91 protein spectra with their environmental data. We tested the resulting scoring calculation on a test set of ten proteins and compared the identification results with those of other peptide mass fingerprinting programs.