EBI is an Outstation of the European Molecular Biology Laboratory. UniProtKB Sandra Orchard
Importance of reference protein sequence databases Completeness and minimal redundancy A non redundant protein sequence database, with maximal coverage including splice isoforms, disease variant and PTMs. Low degree of redundancy for facilitating peptide assignments Stability and consistency Stable identifiers and consistent nomenclature Databases are in constant change due to a substantial amount of work to improve their completeness and the quality of sequence annotation High quality protein annotation Detailed information on protein function, biological processes, molecular interactions and pathways cross-referenced to external source
Summary of protein sequence databases DatabaseDescriptionSpecies UniProtKBExpertly curated section (UniProtKB/Swiss-Prot) and computer- annotated section (UniProtKB/TrEMBL); minimum level of redundancy; high level of integration with other databases; stable identifiers; diversity of sources including large scale genomics, small scale cloning and sequencing, protein sequencing, PDB, predicted sequences from Ensembl and RefSeq Many UniRef100Assembled from UniProtKB, Ensembl and RefSeq; merges 100% identical sequences; stable identifiers Many EnsemblPredictions using automated genome annotation pipeline; explicitly linked to nucleotide and protein sequences; stable reference; merge their annotations with Vega annotations at transcript level; extensive quality checks to remove erroneous gene models ; high level of integration with other databases Over 50 Eukaryotic genomes Ensembl Genomes: Metazoa, Plants and Fungi, Protists, Bacteria and Archaea RefSeqNCBI creates from existing data; ongoing curation; non-redundant; explicitly linked nucleotide and protein sequences; stable reference; high level of integration with other databases Limited to fully sequenced organisms Entrez protein (NCBInr)Assembled from GenBank and RefSeq coding sequence translations and UniProt KB ; annotations extracted from source curated databases; high degree of sequence redundancy Many Updated from Nesvizhskii, A. I., and Aebersold, R. (2005) Interpretation of shotgun proteomic data: the protein inference problem. Mol. Cell. Proteomics. 4,1419–1440l
UniProtKB Master headline UniProt Knowledgebase: 2 sections 1. UniProtKB/Swiss-Prot Non-redundant, high- quality manual annotation - reviewed 2. UniProtKB/TrEMBL Redundant, automatically annotated - unreviewed
SequenceSequence features Ontologies References Nomenclature Splice variants Annotations UniProtKB Manual annotation of UniProtKB/Swiss-Prot
Master headline Sequence curation, stable identifiers, versioning and archiving For example – erroneous gene model predictions, frameshifts …...premature stop codons, read-throughs, erroneous initiator methionines…..
Master headline Splice variants
Master headline Identification of amino acid variants..and of PTMs … and also
Master headline Domain annotation Binding sites
Master headline Protein nomenclature
Master headline
Controlled vocabularies used whenever possible… Annotation - >30 defined fields
Master headline..and also imported from external resources Binary interactions taken from the IntAct database Interactors of human p53
Master headline Controlled vocabulary usage increasing – for example from the Gene Ontology Annotation for human Rhodopsin
1Evidence at protein level There is experimental evidence of the existence of a protein (e.g. Edman sequencing, MS, X-ray/NMR structure, good quality protein-protein interaction, detection by antibodies) 2Evidence at transcript level The existence of a protein has not been proven but there is expression data (e.g. existence of cDNAs, RT-PCR or Northern blots) that indicates the existence of a transcript. 3Inferred from homology The existence of a protein is likely because orthologs exist in closely related species 4 Predicted 5Uncertain Sequence evidence Type of evidence that supports the existence of a protein
Manual annotation of the human proteome (UniProtKB/Swiss-Prot) A draft of the complete human proteome has been available in UniProtKB/Swiss-Prot since 2008 Manually annotated representation of 20,242 protein coding genes with ~ 36,000 protein sequences - an additional 38,484 UniProtKB/TrEMBL form the complete proteome set Approximately 63,000 single amino acid polymorphisms (SAPs), mostly disease-linked 80,000 post-translational modifications (PTMs) Close collaboration with NCBI, Ensembl, Sanger Institute and UCSC to provide the authoritative set to the user community
Master headline Searching UniProt – Simple Search Text-based searching Logical operators ‘&’ (and), ‘|’
Master headline Searching UniProt – Advanced Search
Master headline Searching UniProt – Search Results Each linked to the UniProt entry
Master headline Searching UniProt – Search Results
Master headline Searching UniProt – Search Results
Master headline Searching UniProt – Blast Search
Master headline Searching UniProt – Blast Search
Master headline Searching UniProt – Blast Results Alignment with query sequence
Master headline Searching UniProt – Blast Results
UniProtKB/TrEMBL Multiple entries for the same protein (redundancy) can arise in UniProtKB/TrEMBL due to: o Erroneous gene model predictions o Sequence errors (Frame shifts) o Polymorphisms o Alternative start sites o Isoforms Apart from 100% identical sequences all merged sequences are analysed by a curator so they can be annotated accordingly.
Why do we need predictive annotation tools?
Given a set of uncharacterised sequences, we usually want to know: –what are these proteins; to what family do they belong? –what is their function; how can we explain this in structural terms?
2. The protein signature approach We can then use these models to infer relationships with previously characterised sequences This is the approach taken by protein signature databases Alternatively, we can model the conservation of amino acids at specific positions within a multiple sequence alignment, seeking ‘patterns’ across closely related proteins 1. Pairwise alignment approaches (e.g. BLAST) Good at recognising similarity between closely related sequences Perform less well at detecting divergent homologues
What are protein signatures? Multiple sequence alignment Protein family/domain Build model Search Mature model ITWKGPVCGLDGKTYRNECALL AVPRSPVCGSDDVTYANECELK UniProt Significant match Protein analysis
Full domain alignment methods Single motif methods Multiple motif methods Regex patterns (PROSITE) Profiles (Profile Library) HMMs (Pfam) Identity matrices (PRINTS) Diagnostic approaches (sequence-based)
Patterns Extract pattern sequences xxxxxx Sequence alignment Motif Define pattern Pattern signature C-C-{P}-x(2)-C-[STDNEKPI]-x(3)-[LIVMFS]-x(3)-C Build regular expression PS 00000
Patterns Patterns are mostly directed against functional residues: active sites, PTM, disulfide bridges, binding sites Some aa can be forbidden at some specific positions which can help to distinguish closely related subfamilies Short motifs handling - a pattern with very few variability and forbidden positions, can produce significant matches e.g. conotoxins: very short toxins with few conserved cysteines C-{C}(6)-C-{C}(5)-C-C-x(1,3)-C-C-x(2,4)-C-x(3,10)- C Drawbacks High False Positive/False Negative rate Advantages
Fingerprints Sequence alignment Correct order Correct spacing Motif 2Motif 3Motif 1 Define motifs Fingerprint signature 123 PR Extract motif sequences xxxxxx Weight matrices
The significance of motif context order interval Identify small conserved regions in proteins Several motifs characterise family Offer improved diagnostic reliability over single motifs by virtue of the biological context provided by motif neighbours
Profiles & HMMs Sequence alignment Entire domain Define coverage Whole protein Use entire alignment for domain or protein xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx Build model Models insertions and deletions Profile or HMM signature
HMM databases Sequence-based PIR SUPERFAMILY: families/subfamilies reflect the evolutionary relationship PANTHER : families/subfamilies model the divergence of specific functions TIGRFAM: microbial functional family classification PFAM : families & domains based on conserved sequence SMART: functional domain annotation Structure-based SUPERFAMILY : models correspond to SCOP domains GENE3D : models correspond to CATH domains
Why we created InterPro By uniting the member databases, InterPro capitalises on their individual strengths, producing a powerful diagnostic tool & integrated database –to simplify & rationalise protein analysis –to facilitate automatic functional annotation of uncharacterised proteins –to provide concise information about the signatures and the proteins they match, including consistent names, abstracts (with links to original publications), GO terms and cross- references to other databases
InterPro Entry Adds extensive annotation Links to other databases Structural information and viewers Groups similar signatures together Adds extensive annotation Links to other databases Hierarchical classification
Interpro hierarchies: Families FAMILIES can have parent/child relationships with other Families Parent/Child relationships are based on: Comparison of protein hits child should be a subset of parent siblings should not have matches in common Existing hierarchies in member databases Biological knowledge of curators
Interpro hierarchies: Domains DOMAINS can have parent/child relationships with other domains
Domains and Families may be linked through Domain Organisation Hierarc hy
InterPro Entry Adds extensive annotation Links to other databases Structural information and viewers Groups similar signatures together Adds extensive annotation Links to other databases
InterPro Entry Adds extensive annotation Links to other databases Structural information and viewers Groups similar signatures together Adds extensive annotation Links to other databases The Gene Ontology project provides a controlled vocabulary of terms for describing gene product characteristics
InterPro Entry Adds extensive annotation Links to other databases Structural information and viewers Groups similar signatures together Adds extensive annotation Links to other databases UniProt KEGG... Reactome... IntAct... UniProt taxonomy PANDIT... MEROPS... Pfam clans... Pubmed
InterPro Entry Adds extensive annotation Links to other databases Structural information and viewers Groups similar signatures together Adds extensive annotation Links to other databases PDB 3-D Structures SCOP Structural domains CATH Structural domain classification
Searching InterPro
Protein family membership Domain organisation Domains, repeats & sites GO terms
Searching InterPro
Interactive: Webservice (SOAP and REST): Downloadable: ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan/ InterProScan access
Searching InterPro
Master headline Automated clean-up of annotation from original nucleotide sequence entry Additional value added by using automatic annotation Recognises common annotation belonging to a closely related family within UniProtKB/Swiss-Prot Identifies all members of this family using pattern/motif/HMMs in InterPro Transfers common annotation to related family members in TrEMBL Automatic Annotation
← Name (non-standard) ← Taxonomy ← Publication ← Sequence
Master headline InterPro
Master headline
Finding a complete proteome in UniProtKB
Complete Proteomes
MS Proteomics Require each sequence (inc isoforms) to be present in the dataset as an separate entity for search engines to access For higher organisms, with isoforms, expanded set made available on ftp site Fasta files by FTP One file per species containing canonical + isoform sequences
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