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Protein function and classification . www.ebi.ac.uk/interpro. Hsin -Yu Chang www.ebi.ac.uk. Greider and Balckburn discovered telomerase in 1984 and were awarded Nobel prize in 2009. Which model organism they used for this study ? . 3. Mouse. 2. S accharomyces cerevisiae.

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protein function and classification

Protein function and classification

www.ebi.ac.uk/interpro

Hsin-Yu Chang

www.ebi.ac.uk

slide2

Greider and Balckburn discovered telomerase in 1984 and were awarded Nobel prize in 2009. Which model organism they used for this study ?

3. Mouse

2. Saccharomyces cerevisiae

1. Tetrahymena

4. Human

slide3

1995 Clone hTR

1995/1997 Clone hTERT

1997 Telomerase knockout mouse

1989

Telomere hypothesis of cell senescence

Szostak

1999/2000…

Telomerase/telomere dysfunctions and cancer

1985

Discovery of telomerase

Greider and Blackburn

1998 Ectopic expression of telomerase in normal fibroblasts and epithelial cells bypasses the Hayflick’s limit

A single Tetrahymena cell has 40,000 telomeres, whereas a human cell only has 92.

Gilson and Ségal-Bendirdjian, Biochimie, 2010.

therefore protein classification could help scientists to gain information about protein functions
Therefore, protein classification could help scientists to gain information about protein functions.
i n the lab what do we usually do to analyse protein sequences and find out their functions
In the lab, what do we usually do to analyse protein sequences and find out their functions?
slide6

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:

blast it
BLAST it?
  • Drawbacks:
    • sometimes struggle with multi-domain proteins
    • less useful for weakly-similar sequences (e.g., divergent homologues)
  • Advantages:
  • Relatively fast
  • User friendly
  • Very good at recognising similarity between closely related sequences
slide12

Because BLAST performs localpairwise alignment, it:

  • Cannot encode the information found in an multiple sequence alignment that show you conserved sites.
60s acidic ribosomal protein p0 m ultiple sequence alignment
60S acidic ribosomal protein P0: multiple sequence alignment

Using pairwise alignment could miss out on conserved residues

an alternative approach protein signature search
An alternative approach: protein signature search
  • Model the pattern of conserved amino acids at specific positions within a multiple sequence alignment
  • Use these models to infer relationships with the characterised sequences (from which the alignment was constructed)
  • This is the approach taken by protein signature databases
three different protein signature approaches
Three different protein signature approaches

Patterns

Single motif methods

Profiles & HMMs

hidden Markov models

Full alignment methods

Fingerprints

Multiple motif methods

slide16

PS00000

Patterns

Patterns are usually directed against functional sequence features such as: active sites, binding sites, etc.

Sequence alignment

Motif

ALVKLISG

AIVHESAT

CHVRDLSC

CPVESTIS

Pattern sequences

[AC] – x -V- x(4) - {ED}

Regular expression

Pattern signature

slide17

Patterns

  • Advantages:
      • Cananchor the match to the extremity of a sequence
      • <M-R-[DE]-x(2,4)-[ALT]-{AM}
      • Strict - a pattern with very little variability and forbidden residues can produce highly accurate matches
  • Drawbacks:
    • Simple but less flexible
slide18

Motif 1

Motif 2

Motif 3

xxxxxx

xxxxxx

xxxxxx

xxxxxx

xxxxxx

xxxxxx

xxxxxx

xxxxxx

xxxxxx

xxxxxx

xxxxxx

xxxxxx

Motif sequences

Fingerprint signature

PR00000

Fingerprints:

a multiple motif approach

Sequence alignment

Define motifs

Weight matrices

the significance of motif context
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

1

2

3

interval

slide20

Fingerprints

  • 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
slide21

Profiles & HMMs

Whole protein

Sequence alignment

Entire domain

Define coverage

xxxxxxxxxxxxxxxxxxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxx

Use entire alignment of domain or protein family

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Build model

Profile or HMM signature

slide22

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
slide23

HMMs

Start with a multiple sequence alignment

Amino acid frequency at each position in the alignment and their transition probabilities are encoded

Insertions and deletions are also modelled

  • Can model very divergent regions of alignment
  • Very good at identifying evolutionarily distant homologues
three different protein signature approaches1
Three different protein signature approaches

Patterns

Single motif methods

Profiles & HMMs

hidden Markov models

Full alignment methods

Fingerprints

Multiple motif methods

what is interpro
What is InterPro?
  • InterProis an integrated sequence analysis resource
  • It combines predictive models (known as signatures) from different databases to provide functional analysis of protein sequences by classifying them into families and predicting domains and important sites
slide28

Facts about InterPro

  • First release in 1999
  • 11 partner databases
  • Forms part of the automated system that adds annotation to UniProtKB/TrEMBL
  • Provides matches to over 80% of UniProtKB
  • Source of >60 million Gene Ontology (GO) mappings to >17 million distinct UniProtKBsequences
  • 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
slide29

HAMAP

Profiles

Protein features 

(sites)

Functional annotation of families/domains

Structural

domains

Patterns

Finger prints

Hidden Markov Models

interpro signature integration process
InterPro signature integration process
  • 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
  • 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
interpro entry types
InterPro entry types

Proteins share a common evolutionary origin, as reflected in their related functions, sequences or structure

Family

Domain

Distinct functional, structural or sequence units that may exist in a variety of biological contexts

Repeats

Short sequences typically repeated within a protein

Active

Site

Binding

Site

Conserved

Site

PTM

Sites

slide36

Type

Name

Identifier

Contributing signatures

Description

References

GO terms

slide41

Type

Name

Identifier

Contributing signatures

Relationships

Description

References

family relationships in interpro
Family relationships in InterPro:

Interleukin-15/Interleukin-21 family

Interleukin-15

Interleukin-15

mammal

Interleukin-15

fish

Interleukin-15

avian

interpro relationships domains
InterPro relationships: domains

Protein kinase-like

domain

Protein kinase

catalytic domain

Tyrosine

kinase catalytic

domain

Serine/threonine

kinase catalytic

domain

gene ontology
Gene Ontology
  • Unify the representation of gene and gene product attributes across species
  • Allow cross-species and/or cross-database comparisons
slide49

The Gene Ontology

Less specific concepts

  • A way to capture

biological knowledge

in a written and

computable form

  • A set of concepts
  • and their relationships
  • to each other arranged
  • as a hierarchy

More specific concepts

www.ebi.ac.uk/QuickGO

the concepts in go
The Concepts in GO

1. Molecular Function

  • protein kinase activity
  • insulin receptor activity

2. Biological Process

  • Cell cycle
  • Microtubule cytoskeleton organisation

3. Cellular Component

slide51

GO:0006955 Immune response

GO:0016020 membrane

summary
Summary

InterPro is a sequence analysis resource that classifies sequences into protein families and predicts important domains and sites

It uses protein signatures based on different methodologies from different member databases

Its member databases all have their particular niche or focus...

...but InterPro offers a combination of all their areas of expertise!

why use interpro
Why use InterPro?
  • Large amounts of manually curated data
    • 35,634signatures integrated into 25,214entries
    • Cites 38,877PubMed publications
  • Large coverage of protein sequence space
  • Regularly updated
    • ~ 8 week release schedule
    • New signatures added
    • Scanned against latest version of UniProtKB
caution
CautionAnd one more thing…..
  • 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!

We need your feedback!

missing/additional references

reporting problems

requests

EBI support page.

slide55

The InterPro Team:

Hsin-Yu

Chang

Alex Mitchell

Craig McAnulla

Siew-Yit Yong

Amaia Sangrador

Sarah

Hunter

Gift

Nuka

Sebastien Pesseat

Matthew

Fraser

Maxim Scheremetjew

Louise

Daugherty

thank you

Thank you!

www.ebi.ac.uk

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