1. Protein function and classification Hsin-Yu Chang www.ebi.ac.uk

2. Classifying proteins into families and identifying protein homologues can help scientists to characterise unknown proteins.

3. Greider and Blackburn discovered telomerase in 1984 and were awarded Nobel prize in 2009. Which model organism they used for this study ? 1. Tetrahymena thermophila 2. Saccharomyces cerevisiae 3. Mouse 4. Human

4. A single Tetrahymena thermophila cell has 40,000 telomeres, whereas a human cell only has 92. 1984 Discovery of telomerase Greider and Blackburn 1989 Telomere hypothesis of cell senescence Szostak 1995 Clone hTR 1995/1997 Clone hTERT 1997 Telomerase knockout mouse 1998 Ectopic expression of telomerase in normal human epithelial cells cause the extension of their lifespan 1999/2000… Telomerase/telomere dysfunctions and cancer Gilson and Ségal-Bendirdjian, Biochimie, 2010.

5. Can we identify human telomerase from Tetrahymea protein sequence?

6. Let’s pretend that human telomerase has not been identified and we only know the protein sequences of Tetrahymena telomerase. How can we find the human telomerase?

7. BLAST (Basic Local Alignment Tool) : compares protein sequences to sequence databases and calculates the statistical significance of matches.

8. BLAST Advantages: Relatively fast User friendly Very good at recognising similarity between closely related sequences Drawbacks: sometimes struggle with multi-domain proteins less useful for weakly- similar sequences (e.g., divergent homologues)

9. Using Tetrahymena telomerase protein sequences as a query in BLAST, you will find a few human proteins that have very low identity.

10. Tetrahymena and putative human telomerase (AAC51724.1) have poor protein sequence match.

11. Can we presume this protein is a telomerase homologue from humans? Can we find more information about it before pursuing it further?

12. Telomerase ribonucleoprotein complex - RNA binding domain Reverse transcriptase domain Search for protein signatures (such as domains) in AAC51724.1

13. Plan experiments and find out more! AAC51724.1 shares 23% identity with Tetrahymena telomerase. It also contains the same domains as telomerase.

14. But, where can we search for information about the protein domains?

15. Structural domains Functional annotation of families/domains Protein features (sites) Hidden Markov Models Finger prints Profiles Patterns Protein databases that use signature approaches HAMAP

16. Construction of protein signatures Construction of a multiple sequence alignment (MSA) from characterised protein sequences. Modelling the pattern of conserved amino acids at specific positions within a MSA. Use these models to infer relationships with the characterised sequences

17. Three different protein signature approaches Patterns Single motif methods Fingerprints Multiple motif methods Profiles & Hidden Markov Models (HMMs) Full alignment methods Sequence alignment

18. Patterns

19. Sequence alignment Motif Pattern signature [AC] – x -V- x(4) - {ED} Regular expression PS00000 Pattern sequences ALVKLISG AIVHESAT CHVRDLSC CPVESTIS Patterns are usually directed against functional sequence features such as: active sites, binding sites, etc.

20. PDOC00199 [SAG]-G-G-T-G-[SA]-G Tubulin signature A conserved motif in tubulins

21. Patterns Advantages: Strict - a pattern with very little variability and can produce highly accurate matches Drawbacks: Simple but less flexible

22. Fingerprints

23. Fingerprints: a multiple motif approach Sequence alignment Motif 2Motif 3Motif 1 Define motifs Fingerprint signature PR00000 Motif sequences xxxxxx Weight matrices

24. Telomerase signature (PR01365) Motif 1Motif 2 Motif 3 Motif 4

25. The significance of motif context order interval Identify small conserved regions in proteins Several motifs  characterise family 1 2 3

26. Good at modeling the often small differences between closely related proteins Distinguish individual subfamilies within protein families, allowing functional characterisation of sequences at a high level of specificity Fingerprints Amino acids relatively well conserved across all chloride channel protein family members Amino acids uniquely conserved in chloride channel protein 3 subfamily members.

27. Profiles & HMMs

28. Sequence alignment Entire domain Define coverage Whole protein Use entire alignment of domain or protein family xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx Build model (Profile or HMMs) Profile or HMM signature Profiles & HMMs

29. Profiles Start with a multiple sequence alignment Amino acids at each position in the alignment are scored according to the frequency with which they occur Scores are weighted according to evolutionary distance using a BLOSUM matrix Good at identifying homologues

30. HMMs Amino acid frequency at each position in the alignment and their transition probabilities are encoded Insertions and deletions are also modelled Start with a multiple sequence alignment Very good at identifying evolutionarily distant homologues Can model very divergent regions of alignment Advantages

31. Three different protein signature approaches Patterns Single motif methods Fingerprints Multiple motif methods Profiles & HMMs hidden Markov models Full alignment methods

32. www.ebi.ac.uk/interpro Fingerprints Patterns Profiles & HMMs hidden Markov models

33. Structural domains Functional annotation of families/domains Protein features (sites) Hidden Markov Models Finger prints Profiles Patterns HAMAP

34. The aim of InterPro Family entry: description, proteins matched and more information. Domain entry: description, proteins matched and more information. Site entry: description, proteins matched and more information. Protein sequences

35. What is InterPro? InterPro is an integrated sequence analysis resource It combines predictive models (known as signatures) from different databases It provides functional analysis of protein sequences by classifying them into families and predicting domains and important sites

36. First release in 1999 11 partner databases Add annotation to UniProtKB/TrEMBL Provides matches to over 80% of UniProtKB Source of >85 million Gene Ontology (GO) mappings to >24 million distinct UniProtKB sequences 50,000 unique visitors to the web site per month> 2 million sequences searched online per month. Plus offline searches with downloadable version of software Facts about InterPro

37. Signatures are provided by member databases They are scanned against the UniProt database to see which sequences they match Curators manually inspect the matches before integrating the signatures into InterPro InterPro signature integration process InterPro curators

38. InterPro signature integration process Signatures representing the same entity are integrated together Relationships between entries are traced, where possible Curators add literature referenced abstracts, cross-refs to other databases, and GO terms

39. http://www.ebi.ac.uk/interpro/

40. Search using protein sequences

41. Family

42. Type

43. InterPro entry types Proteins share a common evolutionary origin, as reflected in their related functions, sequences or structure. Ex. Telomerase family. Family Distinct functional, structural or sequence units that may exist in a variety of biological contexts. Ex. DNA binding domain. Domain Short sequences typically repeated within a protein. Ex. Tubulin binding repeats in microtubule associated protein Tau. Repeats PTM Active Site Binding Site Conserved Site Sites Ex. Phosphorylation sites, ion binding sites, tubulin conserved site.

44. Type Name Identifier Contributing signatures Description GO terms References

49. Type Name Identifier Contributing signatures Description References Relationships

50. InterPro family and domain relationships

51. Family relationships in InterPro: Interleukin-15/Interleukin-21 family (IPR003443) Interleukin-15 (IPR020439) Interleukin-15 Avian (IPR020451) Interleukin-15 Fish (IPR020410) Interleukin-15 Mammal (IPR020466) Interleukin-21 (IPR028151)

52. Relationships

53. InterPro relationships: domains Protein kinase-like domain Protein kinase domain Serine/threonine kinase catalytic domain Tyrosine kinase catalytic domain

55. Gene Ontology Allow cross-species and/or cross-database comparisons Unify the representation of gene and gene product attributes across species

56. The Concepts in GO 1. Molecular Function 2. Biological Process 3. Cellular Component protein kinase activity insulin receptor activity Cell cycle Microtubule cytoskeleton organisation

57. GO:0003677 DNA binding GO:0003721 telomeric template RNA reverse transcriptase activity GO:0005634 Nucleus

58. Search using keywords

61. Summary Protein classification could help scientists to gain information about protein functions. Blast is fast and easy to use but has its drawbacks. Alternative approach: protein signature databases build models (protein signatures) by using different methods (patterns, fingerprints, profile and HMMs). InterPro integrates these signatures from 11 member databases. It serves as a sequence analysis resource that classifies sequences into protein families and predicts important domains and sites.

63. Why use InterPro? Large amounts of manually curated data 35,634 signatures integrated into 25,214 entries Cites 38,877 PubMed publications Large coverage of protein sequence space Regularly updated ~ 8 week release schedule New signatures added Scanned against latest version of UniProtKB

64. Caution We need your feedback! missing/additional references reporting problems requests InterPro is a predictive protein signature database - results are predictions, and should be treated as such InterPro entries are based on signatures supplied to us by our member databases....this means no signature, no entry! EBI support pageEBI support page. And one more thing…..

65. The InterPro Team: Amaia Sangrador Craig McAnulla Matthew Fraser Maxim Scheremetjew Siew-Yit Yong Alex Mitchell Sebastien Pesseat Sarah Hunter Gift Nuka Hsin-Yu Chang www.ebi.ac.uk/interpro Twitter: @InterProDB

66. DatabaseBasisInstitution Built from FocusURL PfamHMMSanger Institute Sequence alignment Family & Domain based on conserved sequence http://pfam.sanger.ac.uk/ Gene3DHMMUCL Structure alignment Structural Domain http://gene3d.biochem.ucl.a c.uk/Gene3D/ SuperfamilyHMMUni. of Bristol Structure alignment Evolutionary domain relationships http://supfam.cs.bris.ac.uk/ SUPERFAMILY/ SMARTHMMEMBL Heidelberg Sequence alignment Functional domain annotation http://smart.embl- heidelberg.de/ TIGRFAMHMMJ. Craig Venter Inst. Sequence alignment Microbial Functional Family Classification http://www.jcvi.org/cms/rese arch/projects/tigrfams/overv iew/ PantherHMMUni. S. California Sequence alignment Family functional classification http://www.pantherdb.org/ PIRSFHMM PIR, Georgetown, Washington D.C. Sequence alignment Functional classification http://pir.georgetown.edu/pir www/dbinfo/pirsf.shtml PRINTS Fingerprints Uni. of Manchester Sequence alignment Family functional classification http://www.bioinf.mancheste r.ac.uk/dbbrowser/PRINTS/i ndex.php PROSITE Patterns & Profiles SIB Sequence alignment Functional annotation http://expasy.org/prosite/ HAMAPProfilesSIB Sequence alignment Microbial protein family classification http://expasy.org/sprot/ham ap/ ProDom Sequence clustering PRABI : Rhône-Alpes Bioinformatics Center Sequence alignment Conserved domain prediction http://prodom.prabi.fr/prodo m/current/html/home.php

67. Thank you! www.ebi.ac.uk Twitter: @emblebi Facebook: EMBLEBI YouTube: EMBLMedia

68. The BLOSUM (BLOcks SUbstitution Matrix) matrix is a substitution matrix used for sequence alignment of proteins. BLOSUM matrices are used to score alignments between evolutionarily divergent protein sequences.