1. EBI is an Outstation of the European Molecular Biology Laboratory. Alex Mitchell InterPro team mitchell@ebi.ac.uk Using InterPro for functional analysis of protein sequences

2. Why do we need predictive annotation tools?

3. 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?

4. Pairwise alignment approaches (e.g., BLAST)

6. Good at recognising similarity between closely related sequences Perform less well at detecting divergent homologues Pairwise alignment approaches (e.g., BLAST)

7. 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 They go about this in 3 different ways... Alternatively, we can model the conservation of amino acids at specific positions within a multiple sequence alignment, seeking ‘patterns’ across closely related proteins

8. Protein signature methods (patterns) (fingerprints) (profiles & HMMs)

9. Sequence features Domains Families

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

11. 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)

12. 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

13. Patterns Patterns are mostly directed against functional residues: active sites, PTM, disulfide bridges, binding sites Anchoring the match to the extremity of a sequence <M-R-[DE]-x(2,4)-[ALT]-{AM} 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 Simple but less powerful Advantages

14. Fingerprints Sequence alignment Correct order Correct spacing Motif 2Motif 3Motif 1 Define motifs Fingerprint signature 123 PR 00000 Extract motif sequences xxxxxx Weight matrices

15. 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

16. 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

17. PROSITE domains: high quality manually curated seeds (using biologically characterized UniProtKB/Swiss-Prot entries), documentation and annotation rules. Oriented toward functional domain discrimination. HAMAP families: manually curated bacterial, archaeal and plastid protein families (represented by profiles and associated rules), covering some highly conserved proteins and functions. PROSITE and HAMAP profiles: a functional annotation perspective

18. 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

19. 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

20. InterPro Structural domains Hidden Markov Models Finger- Prints ProfilesPatterns Functional annotation of families/domains Protein features (sites)

21. InterPro integration process Member databases + annotation Protein signatures InterPro

22. 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

23. 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

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

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

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

27. 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

28. 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

29. 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

30. Searching InterPro

31. Protein family membership Domain organisation Domains, repeats & sites GO terms

32. Searching InterPro

34. Interactive: http://www.ebi.ac.uk/Tools/pfa/iprscan/ Webservice (SOAP and REST): http://www.ebi.ac.uk/Tools/webservices/services/pfa/iprscan_rest http://www.ebi.ac.uk/Tools/webservices/services/pfa/iprscan_soap Downloadable: ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan/ InterProScan access

35. Searching InterPro

36. Searching InterPro: BioMart

37. Large volumes of data can be queried efficiently The interface is shared with many other bioinformatics resources It allows federation with other databases:  PRIDE (mass spectrometry-derived proteins and peptides  REACTOME (biological pathways) BioMart Search BioMart allows more powerful and flexible queries

38. BioMart Search 1)Choose Dataset a. Choose InterPro BioMart

39. BioMart Search 1)Choose Dataset a. Choose InterPro BioMart b. Choose InterPro entries or protein matches

40. BioMart Search 2)Choose Filters  Search specific entries, signatures or proteins

41. BioMart Search 2)Choose Filters  e.g. Filter by specific proteins

42. BioMart Search 3)Choose Attributes  What results you want

43. BioMart Search 4)Choose additional Dataset (optional)  This is where you link results to Pride and Reactome

44. BioMart Search Results User manual HTML = web-formatted table CSV = comma-separated values TSV = tab-separated values XLS = excel spreadsheet Click to view results