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

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Presentation on theme: "Protein function and classification www.ebi.ac.uk/interpro Hsin-Yu Chang www.ebi.ac.uk."— Presentation transcript:

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

2 Protein classification could help scientists to gain information about protein functions.

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 2. Saccharomyces cerevisiae 3. Mouse 4. Human

4 A single Tetrahymena 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 Therefore, classify proteins into families and identify protein homologues can help scientists to gather more information about their favourite proteins.

6 However, in the lab, what do we usually do to analyse protein sequences and find out their functions?

7 >ProteinA MNRGVPFRHLLLVLQLALLPAATQGKKVVLGKKGDTVEL TCTASQKKSIQFHWKNSNQIKILGNQGSFLTKGPSKLND RADSRRSLWDQGNFPLIIKNLKIEDSDTYICEVEDQKEEV QLLVFGLTANSDTHLLQGQSLTLTLESPPGSSPSVQCRS PRGKNIQGGKTLSVSQLELQDSGTWTCTVLQNQKKVEF KIDIVVLAFQKASSIVYKKEGEQVEFSFPLAFTVEKLTGS GELWWQAERASSSKSWITFDLKNKEVSVKRVTQDPKLQ MGKKLPLHLTLPQALPQYAGSGNLTLALEAKTGKLHQEV NLVVMRATQLQKNLTCEVWGPTSPKLMLSLKLENKEAK VSKREKAVWVLNPEAGMWQCLLSDSGQVLLESNIKVLP TWSTPVQPMALIVLGGVAGLLLFIGLGIFFCVRCRHRRR QAERMSQIKRLLSEKKTCQCPHRFQKTCSPI How can we annotate ProteinA ?

8 Protein BLAST Publications - text books or papers UniProt PDB Specialized protein databases such as SGD, the human protein atlas, etc. What I used to do:

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

10 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)

11 Using BLAST to find clues of protein functions -when it goes well

12 Pairwise alignment of two proteins: CD4 from two closely-related species

13 Using BLAST to find clues of protein functions -when it does not give you much information

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15 Because BLAST performs local pairwise alignment, it: Cannot encode the information found in a multiple sequence alignment that show you conserved sites.

16 60S acidic ribosomal protein P0: multiple sequence alignment Using pairwise alignment could miss out on conserved residues

17 An alternative approach: protein signature search

18 An alternative approach: protein signature search 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 This is the approach taken by protein signature databases

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

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

21 Patterns

22 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.

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

24 Fingerprints

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

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

27 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

28 Profiles & HMMs

29 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

30 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

31 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

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

33 www.ebi.ac.uk/interpro

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

35 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

36 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

37 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

38 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

39 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

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

41 >ProteinA MNRGVPFRHLLLVLQLALLPAATQGKKVVLGKKGDTVEL TCTASQKKSIQFHWKNSNQIKILGNQGSFLTKGPSKLND RADSRRSLWDQGNFPLIIKNLKIEDSDTYICEVEDQKEEV QLLVFGLTANSDTHLLQGQSLTLTLESPPGSSPSVQCRS PRGKNIQGGKTLSVSQLELQDSGTWTCTVLQNQKKVEF KIDIVVLAFQKASSIVYKKEGEQVEFSFPLAFTVEKLTGS GELWWQAERASSSKSWITFDLKNKEVSVKRVTQDPKLQ MGKKLPLHLTLPQALPQYAGSGNLTLALEAKTGKLHQEV NLVVMRATQLQKNLTCEVWGPTSPKLMLSLKLENKEAK VSKREKAVWVLNPEAGMWQCLLSDSGQVLLESNIKVLP TWSTPVQPMALIVLGGVAGLLLFIGLGIFFCVRCRHRRR QAERMSQIKRLLSEKKTCQCPHRFQKTCSPI How can we annotate ProteinA by using InterPro?

42 Search using protein sequences

43 Family

44 Type

45 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.

46 Type Name Identifier Contributing signatures Description GO terms References

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51 Type Name Identifier Contributing signatures Description References Relationships

52 InterPro family and domain relationships

53 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)

54 Relationships

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

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57 A brief diversion into the Gene Ontology...

58 English is not a very precise language Same name for different concepts Different names for the same concept ? An example … Tactition Tactile sense Taction Sensory perception of touch ; GO:0050975 Inconsistency in naming of biological concepts

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

60 A way to capture biological knowledge in a written and computable form The Gene Ontology A set of concepts and their relationships to each other arranged as a hierarchy www.ebi.ac.uk/QuickGO Less specific concepts More specific concepts

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

62 GO:0006955 Immune response GO:0016020 membrane

63 Search using keywords

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66 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.

67 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

68 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…..

69 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 Louise Daugherty

70 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

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

72 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.


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