UniProtKB

1. Sandra Orchard UniProtKB

2. 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 • Stabilityand 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

3. Summary of protein sequence databases Updated from Nesvizhskii, A. I., and Aebersold, R. (2005) Interpretation of shotgun proteomic data: the protein inference problem. Mol. Cell. Proteomics. 4,1419–1440l

4. UniProtKB • UniProt Knowledgebase: • 2 sections • UniProtKB/Swiss-Prot Non-redundant, high-quality manual annotation - reviewed • UniProtKB/TrEMBL Redundant, automatically annotated - unreviewed www.uniprot.org Master headline

5. Manual annotation of UniProtKB/Swiss-Prot Splice variants Sequence Sequence features UniProtKB Ontologies Annotations References Nomenclature

6. Sequence curation, stable identifiers, versioning and archiving • For example – erroneous gene model predictions, frameshifts • …. ..premature stop codons, read-throughs, erroneous initiator methionines….. Master headline

7. Splice variants Master headline

8. Identification of amino acid variants ..and of PTMs … and also Master headline

9. Domain annotation Binding sites Master headline

10. Protein nomenclature Master headline

11. Master headline

12. Annotation - >30 defined fields Controlled vocabularies used whenever possible… Master headline

13. ..and also imported from external resources Binary interactions taken from the IntAct database Interactors of human p53 Master headline

14. Controlled vocabulary usage increasing – for example from the Gene Ontology Annotation for human Rhodopsin Master headline

15. Evidence 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) Evidence 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. Inferred from homology The existence of a protein is likely because orthologs exist in closely related species 4 Predicted 5 Uncertain Sequence evidence Type of evidence that supports the existence of a protein

16. 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

17. Text-based searching • Logical operators ‘&’ (and), ‘|’ Searching UniProt – Simple Search Master headline

18. Searching UniProt – Advanced Search Master headline

19. Each linked to the UniProt entry Searching UniProt – Search Results Master headline

20. Searching UniProt – Search Results Master headline

21. Searching UniProt – Search Results Master headline

22. Searching UniProt – Blast Search Master headline

23. Searching UniProt – Blast Search Master headline

24. Alignment with query sequence Searching UniProt – Blast Results Master headline

25. Searching UniProt – Blast Results Master headline

26. UniProtKB/TrEMBL • Multiple entries for the same protein (redundancy) can arise in UniProtKB/TrEMBL due to: • Erroneous gene model predictions • Sequence errors (Frame shifts) • Polymorphisms • Alternative start sites • Isoforms • Apart from 100% identical sequences all merged sequences are analysed by a curator so they can be annotated accordingly.

27. Why do we need predictive annotation tools?

28. 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?

29. 2. The protein signature approach 1. Pairwise alignment approaches (e.g. BLAST) • Good at recognising similarity between closely related sequences • Perform less well at detecting divergent homologues • Alternatively, we can model the conservation of amino acids at specific positions within a multiple sequence alignment, seeking ‘patterns’ across closely related proteins • We can then use these models to infer relationshipswith previously characterised sequences • This is the approach taken by protein signature databases

30. Multiple sequence alignment What are protein signatures? Protein family/domain Build model Search UniProt Protein analysis Significant match ITWKGPVCGLDGKTYRNECALL Mature model AVPRSPVCGSDDVTYANECELK

31. Diagnostic approaches (sequence-based) Single motif methods Regex patterns (PROSITE) Full domain alignment methods Profiles (Profile Library) HMMs (Pfam) Multiple motif methods Identity matrices (PRINTS)

32. Motif Define pattern xxxxxx xxxxxx xxxxxx xxxxxx Extract pattern sequences Build regular expression C-C-{P}-x(2)-C-[STDNEKPI]-x(3)-[LIVMFS]-x(3)-C Pattern signature PS00000 Patterns Sequence alignment

33. Patterns Advantages • 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 cysteinesC-{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 Patterns are mostly directed against functional residues: active sites, PTM, disulfide bridges, binding sites

34. Motif 1 Motif 2 Motif 3 Define motifs xxxxxx xxxxxx xxxxxx xxxxxx xxxxxx xxxxxx xxxxxx xxxxxx xxxxxx xxxxxx xxxxxx xxxxxx Extract motif sequences Correct order Fingerprint signature 1 2 3 Correct spacing PR00000 Fingerprints Sequence alignment Weight matrices

35. 1 2 3 4 5 The significance of motif context • 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 order interval

36. Profiles & HMMs Whole protein Sequence alignment Entire domain Define coverage xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx Use entire alignment for domain or protein xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Models insertions and deletions Build model Profile or HMM signature

37. 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

38. 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

39. InterPro Entry Groups similar signatures together Adds extensive annotation Adds extensive annotation Links to other databases Links to other databases Structural information and viewers • Hierarchical classification

40. 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

41. Interpro hierarchies: Domains DOMAINS can have parent/child relationships with other domains

42. Domains and Families may be linked through Domain Organisation Hierarchy

43. InterPro Entry Groups similar signatures together Adds extensive annotation Adds extensive annotation Links to other databases Links to other databases Structural information and viewers

44. InterPro Entry Groups similar signatures together Adds extensive annotation Adds extensive annotation Links to other databases Links to other databases Structural information and viewers The Gene Ontology project provides a controlled vocabulary of terms for describing gene product characteristics

45. InterPro Entry Groups similar signatures together Adds extensive annotation Adds extensive annotation Links to other databases Links to other databases Structural information and viewers UniProt KEGG ... Reactome ... IntAct ... UniProt taxonomy PANDIT ... MEROPS ... Pfam clans ... Pubmed

46. InterPro Entry Groups similar signatures together Adds extensive annotation Adds extensive annotation Links to other databases Links to other databases Structural information and viewers PDB 3-D Structures SCOP Structural domains CATH Structural domain classification

47. Searching InterPro

48. Searching InterPro Protein family membership Domain organisation Domains, repeats & sites GO terms

49. Searching InterPro

50. Searching InterPro