UniProt

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UniProt
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Content
DescriptionUniProt is the Universal Protein resource, a central repository of protein data created by combining the Swiss-Prot, TrEMBL and PIR-PSD databases.
Data types
captured		Protein annotation
Organisms All
Contact
Research center EMBL-EBI, UK; SIB, Switzerland; PIR, US.
Primary citationUniProt Consortium [1]
Access
Data format Custom flat file, FASTA, GFF, RDF, XML.
Website www.uniprot.org
www.uniprot.org/news/
Download URL www.uniprot.org/downloads & for downloading complete data sets ftp.uniprot.org
Web service URLYes – JAVA API see info here & REST see info here
Tools
Web Advanced search, BLAST, ClustalO, bulk retrieval/download, ID mapping
Miscellaneous
License Creative Commons Attribution-NoDerivs
Versioning Yes
Data release
frequency		8 weeks
Curation policyYes – manual and automatic. Rules for automatic annotation generated by database curators and computational algorithms.
Bookmarkable
entities		Yes – both individual protein entries and searches

UniProt is a freely accessible database of protein sequence and functional information, many entries being derived from genome sequencing projects. It contains a large amount of information about the biological function of proteins derived from the research literature. It is maintained by the UniProt consortium, which consists of several European bioinformatics organisations and a foundation from Washington, DC, USA.

Contents

The UniProt consortium

The UniProt consortium comprises the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB), and the Protein Information Resource (PIR). EBI, located at the Wellcome Trust Genome Campus in Hinxton, UK, hosts a large resource of bioinformatics databases and services. SIB, located in Geneva, Switzerland, maintains the ExPASy (Expert Protein Analysis System) servers that are a central resource for proteomics tools and databases. PIR, hosted by the National Biomedical Research Foundation (NBRF) at the Georgetown University Medical Center in Washington, DC, US, is heir to the oldest protein sequence database, Margaret Dayhoff's Atlas of Protein Sequence and Structure, first published in 1965. [2] In 2002, EBI, SIB, and PIR joined forces as the UniProt consortium. [3]

The roots of the UniProt databases

Each consortium member is heavily involved in protein database maintenance and annotation. Until recently, EBI and SIB together produced the Swiss-Prot and TrEMBL databases, while PIR produced the Protein Sequence Database (PIR-PSD). [4] [5] [6] These databases coexisted with differing protein sequence coverage and annotation priorities.

Swiss-Prot was created in 1986 by Amos Bairoch during his PhD and developed by the Swiss Institute of Bioinformatics and subsequently developed by Rolf Apweiler at the European Bioinformatics Institute. [7] [8] [9] Swiss-Prot aimed to provide reliable protein sequences associated with a high level of annotation (such as the description of the function of a protein, its domain structure, post-translational modifications, variants, etc.), a minimal level of redundancy and high level of integration with other databases. Recognizing that sequence data were being generated at a pace exceeding Swiss-Prot's ability to keep up, TrEMBL (Translated EMBL Nucleotide Sequence Data Library) was created to provide automated annotations for those proteins not in Swiss-Prot. Meanwhile, PIR maintained the PIR-PSD and related databases, including iProClass, a database of protein sequences and curated families.

The consortium members pooled their overlapping resources and expertise, and launched UniProt in December 2003. [10]

Organization of the UniProt databases

UniProt provides four core databases: UniProtKB (with sub-parts Swiss-Prot and TrEMBL), UniParc, UniRef and Proteome.

UniProtKB

UniProt Knowledgebase (UniProtKB) is a protein database partially curated by experts, consisting of two sections: UniProtKB/Swiss-Prot (containing reviewed, manually annotated entries) and UniProtKB/TrEMBL (containing unreviewed, automatically annotated entries). [11] As of 22 February 2023, release "2023_01" of UniProtKB/Swiss-Prot contains 569,213 sequence entries (comprising 205,728,242 amino acids abstracted from 291,046 references) and release "2023_01" of UniProtKB/TrEMBL contains 245,871,724 sequence entries (comprising 85,739,380,194 amino acids). [12]

UniProtKB/Swiss-Prot

UniProtKB/Swiss-Prot is a manually annotated, non-redundant protein sequence database. It combines information extracted from scientific literature and biocurator-evaluated computational analysis. The aim of UniProtKB/Swiss-Prot is to provide all known relevant information about a particular protein. Annotation is regularly reviewed to keep up with current scientific findings. The manual annotation of an entry involves detailed analysis of the protein sequence and of the scientific literature. [13]

Sequences from the same gene and the same species are merged into the same database entry. Differences between sequences are identified, and their cause documented (for example alternative splicing, natural variation, incorrect initiation sites, incorrect exon boundaries, frameshifts, unidentified conflicts). A range of sequence analysis tools is used in the annotation of UniProtKB/Swiss-Prot entries. Computer-predictions are manually evaluated, and relevant results selected for inclusion in the entry. These predictions include post-translational modifications, transmembrane domains and topology, signal peptides, domain identification, and protein family classification. [13] [14]

Relevant publications are identified by searching databases such as PubMed. The full text of each paper is read, and information is extracted and added to the entry. Annotation arising from the scientific literature includes, but is not limited to: [10] [13] [14]

Annotated entries undergo quality assurance before inclusion into UniProtKB/Swiss-Prot. When new data becomes available, entries are updated.

UniProtKB/TrEMBL

UniProtKB/TrEMBL contains high-quality computationally analyzed records, which are enriched with automatic annotation. It was introduced in response to increased dataflow resulting from genome projects, as the time- and labour-consuming manual annotation process of UniProtKB/Swiss-Prot could not be broadened to include all available protein sequences. [10] The translations of annotated coding sequences in the EMBL-Bank/GenBank/DDBJ nucleotide sequence database are automatically processed and entered in UniProtKB/TrEMBL. UniProtKB/TrEMBL also contains sequences from PDB, and from gene prediction, including Ensembl, RefSeq and CCDS. [15] Since 22 July 2021 it also includes structures predicted with AlphaFold2. [16]

UniParc

UniProt Archive (UniParc) is a comprehensive and non-redundant database, which contains all the protein sequences from the main, publicly available protein sequence databases. [17] Proteins may exist in several different source databases, and in multiple copies in the same database. In order to avoid redundancy, UniParc stores each unique sequence only once. Identical sequences are merged, regardless of whether they are from the same or different species. Each sequence is given a stable and unique identifier (UPI), making it possible to identify the same protein from different source databases. UniParc contains only protein sequences, with no annotation. Database cross-references in UniParc entries allow further information about the protein to be retrieved from the source databases. When sequences in the source databases change, these changes are tracked by UniParc and history of all changes is archived.

Source databases

Currently UniParc contains protein sequences from the following publicly available databases:

UniRef

The UniProt Reference Clusters (UniRef) consist of three databases of clustered sets of protein sequences from UniProtKB and selected UniParc records. [20] The UniRef100 database combines identical sequences and sequence fragments (from any organism) into a single UniRef entry. The sequence of a representative protein, the accession numbers of all the merged entries and links to the corresponding UniProtKB and UniParc records are displayed. UniRef100 sequences are clustered using the CD-HIT algorithm to build UniRef90 and UniRef50. [20] [21] Each cluster is composed of sequences that have at least 90% or 50% sequence identity, respectively, to the longest sequence. Clustering sequences significantly reduces database size, enabling faster sequence searches.

UniRef is available from the UniProt FTP site.

Funding

UniProt is funded by grants from the National Human Genome Research Institute, the National Institutes of Health (NIH), the European Commission, the Swiss Federal Government through the Federal Office of Education and Science, NCI-caBIG, and the US Department of Defense. [11]

Related Research Articles

In the field of bioinformatics, a sequence database is a type of biological database that is composed of a large collection of computerized ("digital") nucleic acid sequences, protein sequences, or other polymer sequences stored on a computer. The UniProt database is an example of a protein sequence database. As of 2013 it contained over 40 million sequences and is growing at an exponential rate. Historically, sequences were published in paper form, but as the number of sequences grew, this storage method became unsustainable.

<span class="mw-page-title-main">Swiss Institute of Bioinformatics</span>

The SIB Swiss Institute of Bioinformatics is an academic not-for-profit foundation which federates bioinformatics activities throughout Switzerland.

The Protein Information Resource (PIR), located at Georgetown University Medical Center, is an integrated public bioinformatics resource to support genomic and proteomic research, and scientific studies. It contains protein sequences databases

The European Bioinformatics Institute (EMBL-EBI) is an intergovernmental organization (IGO) which, as part of the European Molecular Biology Laboratory (EMBL) family, focuses on research and services in bioinformatics. It is located on the Wellcome Genome Campus in Hinxton near Cambridge, and employs over 600 full-time equivalent (FTE) staff.

<span class="mw-page-title-main">Pfam</span> Database of protein families

Pfam is a database of protein families that includes their annotations and multiple sequence alignments generated using hidden Markov models. The latest version of Pfam, 37.0, was released in June 2024 and contains 21,979 families. It is currently provided through InterPro website.

<span class="mw-page-title-main">Amos Bairoch</span> Swiss bioinformatician

Amos Bairoch is a Swiss bioinformatician and Professor of Bioinformatics at the Department of Human Protein Sciences of the University of Geneva where he leads the CALIPHO group at the Swiss Institute of Bioinformatics (SIB) combining bioinformatics, curation, and experimental efforts to functionally characterize human proteins.

InterPro is a database of protein families, protein domains and functional sites in which identifiable features found in known proteins can be applied to new protein sequences in order to functionally characterise them.

<span class="mw-page-title-main">PROSITE</span> Database of protein domains, families and functional sites

PROSITE is a protein database. It consists of entries describing the protein families, domains and functional sites as well as amino acid patterns and profiles in them. These are manually curated by a team of the Swiss Institute of Bioinformatics and tightly integrated into Swiss-Prot protein annotation. PROSITE was created in 1988 by Amos Bairoch, who directed the group for more than 20 years. Since July 2018, the director of PROSITE and Swiss-Prot is Alan Bridge.

Expasy is an online bioinformatics resource operated by the SIB Swiss Institute of Bioinformatics. It is an extensible and integrative portal which provides access to over 160 databases and software tools and supports a range of life science and clinical research areas, from genomics, proteomics and structural biology, to evolution and phylogeny, systems biology and medical chemistry. The individual resources are hosted in a decentralized way by different groups of the SIB Swiss Institute of Bioinformatics and partner institutions.

The Reference Sequence (RefSeq) database is an open access, annotated and curated collection of publicly available nucleotide sequences and their protein products. RefSeq was introduced in 2000. This database is built by National Center for Biotechnology Information (NCBI), and, unlike GenBank, provides only a single record for each natural biological molecule for major organisms ranging from viruses to bacteria to eukaryotes.

<span class="mw-page-title-main">UGENE</span> Computer software for bioinformatics

UGENE is computer software for bioinformatics. It works on personal computer operating systems such as Windows, macOS, or Linux. It is released as free and open-source software, under a GNU General Public License (GPL) version 2.

SUPERFAMILY is a database and search platform of structural and functional annotation for all proteins and genomes. It classifies amino acid sequences into known structural domains, especially into SCOP superfamilies. Domains are functional, structural, and evolutionary units that form proteins. Domains of common Ancestry are grouped into superfamilies. The domains and domain superfamilies are defined and described in SCOP. Superfamilies are groups of proteins which have structural evidence to support a common evolutionary ancestor but may not have detectable sequence homology.

neXtProt is an on-line knowledge platform on human proteins. It strives to be a comprehensive resource that provides a variety of types of information on human proteins, such as their function, subcellular location, expression, interactions and role in diseases. The major part of the information in neXtProt is obtained from the UniProt Swiss-Prot database but it is complemented by data originating from high-throughput studies with an emphasis on proteomics. neXtProt offers also an advanced search capacity based on the SPARQL technology as well as an API that allows to programmatically extract the data stored in the resource. It is developed by the CALIPHO group directed by Amos Bairoch and Lydie Lane of the Swiss Institute of Bioinformatics (SIB).

<span class="mw-page-title-main">Rolf Apweiler</span> German bioinformatician

Rolf Apweiler is a director of European Bioinformatics Institute (EBI) part of the European Molecular Biology Laboratory (EMBL) with Ewan Birney.

Swiss-model is a structural bioinformatics web-server dedicated to homology modeling of 3D protein structures. As of 2024, homology modeling is the most accurate method to generate reliable three-dimensional protein structure models and is routinely used in many practical applications. Homology modelling methods make use of experimental protein structures (templates) to build models for evolutionary related proteins (targets).

<span class="mw-page-title-main">Terri Attwood</span> British bioinformatics researcher

Teresa K. Attwood is a professor of Bioinformatics in the Department of Computer Science and School of Biological Sciences at the University of Manchester and a visiting fellow at the European Bioinformatics Institute (EMBL-EBI). She held a Royal Society University Research Fellowship at University College London (UCL) from 1993 to 1999 and at the University of Manchester from 1999 to 2002.

In bioinformatics, the PANTHER classification system is a large curated biological database of gene/protein families and their functionally related subfamilies that can be used to classify and identify the function of gene products. PANTHER is part of the Gene Ontology Reference Genome Project designed to classify proteins and their genes for high-throughput analysis.

Cathy H. Wu is the Edward G. Jefferson Chair and professor and director of the Center for Bioinformatics & Computational Biology (CBCB) at the University of Delaware. She is also the director of the Protein Information Resource (PIR) and the North east Bioinformatics Collaborative Steering Committee, and the adjunct professor at the Georgetown University Medical Center.

References

  1. ↑ UniProt, Consortium. (January 2015). "UniProt: a hub for protein information". Nucleic Acids Research. 43 (Database issue): D204–12. doi:10.1093/nar/gku989. PMC   4384041 . PMID   25348405.
  2. ↑ Dayhoff, Margaret O. (1965). Atlas of protein sequence and structure. Silver Spring, Md: National Biomedical Research Foundation.
  3. ↑ "2002 Release: NHGRI Funds Global Protein Database". National Human Genome Research Institute (NHGRI). Archived from the original on 24 September 2015. Retrieved 14 April 2018.
  4. ↑ O'Donovan, C.; Martin, M. J.; Gattiker, A.; Gasteiger, E.; Bairoch, A.; Apweiler, R. (2002). "High-quality protein knowledge resource: SWISS-PROT and TrEMBL". Briefings in Bioinformatics. 3 (3): 275–284. doi: 10.1093/bib/3.3.275 . PMID   12230036. Archived from the original on 2024-01-24. Retrieved 2024-01-24.
  5. ↑ Wu, C. H.; Yeh, L. S.; Huang, H.; Arminski, L.; Castro-Alvear, J.; Chen, Y.; Hu, Z.; Kourtesis, P.; Ledley, R. S.; Suzek, B. E.; Vinayaka, C. R.; Zhang, J.; Barker, W. C. (2003). "The Protein Information Resource". Nucleic Acids Research. 31 (1): 345–347. doi:10.1093/nar/gkg040. PMC   165487 . PMID   12520019.
  6. ↑ Boeckmann, B.; Bairoch, A.; Apweiler, R.; Blatter, M. C.; Estreicher, A.; Gasteiger, E.; Martin, M. J.; Michoud, K.; O'Donovan, C.; Phan, I.; Pilbout, S.; Schneider, M. (2003). "The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003". Nucleic Acids Research. 31 (1): 365–370. doi:10.1093/nar/gkg095. PMC   165542 . PMID   12520024.
  7. ↑ Bairoch, A.; Apweiler, R. (1996). "The SWISS-PROT protein sequence data bank and its new supplement TREMBL". Nucleic Acids Research. 24 (1): 21–25. doi:10.1093/nar/24.1.21. PMC   145613 . PMID   8594581.
  8. ↑ Bairoch, A. (2000). "Serendipity in bioinformatics, the tribulations of a Swiss bioinformatician through exciting times!". Bioinformatics. 16 (1): 48–64. doi: 10.1093/bioinformatics/16.1.48 . PMID   10812477. Archived from the original on 2024-02-05. Retrieved 2024-02-05.
  9. ↑ Séverine Altairac, "Naissance d’une banque de données: Interview du prof. Amos Bairoch Archived 2010-07-12 at the Wayback Machine ". Protéines à la Une Archived 2011-06-21 at the Wayback Machine , August 2006. ISSN   1660-9824.
  10. 1 2 3 Apweiler, R.; Bairoch, A.; Wu, C. H. (2004). "Protein sequence databases". Current Opinion in Chemical Biology. 8 (1): 76–80. doi:10.1016/j.cbpa.2003.12.004. PMID   15036160.
  11. 1 2 Uniprot, C. (2009). "The Universal Protein Resource (UniProt) in 2010". Nucleic Acids Research. 38 (Database issue): D142–D148. doi:10.1093/nar/gkp846. PMC   2808944 . PMID   19843607.
  12. ↑ "UniProtKB/Swiss-Prot Release 2023_01 statistics". web.expasy.org. Archived from the original on 4 April 2023. Retrieved 31 March 2023.
  13. 1 2 3 "How do we manually annotate a UniProtKB entry?". UniProt. September 21, 2011. Archived from the original on Dec 13, 2013. Retrieved 14 April 2018.
  14. 1 2 Apweiler, R.; Bairoch, A.; Wu, C. H.; Barker, W. C.; Boeckmann, B.; Ferro, S.; Gasteiger, E.; Huang, H.; Lopez, R.; Magrane, M.; Martin, M. J.; Natale, D. A.; o’Donovan, C.; Redaschi, N.; Yeh, L. S. (2004). "UniProt: The Universal Protein knowledgebase". Nucleic Acids Research. 32 (90001): 115D–1119. doi: 10.1093/nar/gkh131 . PMC   308865 . PMID   14681372.
  15. ↑ "Where do the UniProtKB protein sequences come from?". UniProt. September 21, 2011. Archived from the original on Dec 15, 2013. Retrieved 14 April 2018.
  16. ↑ Hassabis, Demis (22 July 2022). "Putting the power of AlphaFold into the world's hands". Deepmind. Archived from the original on 24 July 2021. Retrieved 24 July 2021.
  17. ↑ Leinonen, R.; Diez, F. G.; Binns, D.; Fleischmann, W.; Lopez, R.; Apweiler, R. (2004). "UniProt archive". Bioinformatics. 20 (17): 3236–3237. doi: 10.1093/bioinformatics/bth191 . PMID   15044231. Archived (PDF) from the original on Mar 30, 2024.
  18. ↑ "Protein Research Foundation". Archived from the original on 2010-08-30. Retrieved 2010-08-25.
  19. ↑ ftp://ftp.isrec.isb-sib.ch/pub/databases/trome%5B‍%5D
  20. 1 2 Suzek, B. E.; Huang, H.; McGarvey, P.; Mazumder, R.; Wu, C. H. (2007). "UniRef: Comprehensive and non-redundant UniProt reference clusters". Bioinformatics. 23 (10): 1282–1288. doi:10.1093/bioinformatics/btm098. PMID   17379688.
  21. ↑ Li, W.; Jaroszewski, L.; Godzik, A. (2001). "Clustering of highly homologous sequences to reduce the size of large protein databases". Bioinformatics. 17 (3): 282–283. doi:10.1093/bioinformatics/17.3.282. PMID   11294794.
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