Sequence homology treat or trick
This presentation is the property of its rightful owner.
Sponsored Links
1 / 28

Sequence Homology Treat or Trick? PowerPoint PPT Presentation


  • 96 Views
  • Uploaded on
  • Presentation posted in: General

Sequence Homology Treat or Trick?. Fine Grain Structural Classification using the T-RMSD method Cedric Notredame Luis Serrano Cedrik Magis François Stricher Almer van der Slot. Same sequence Same structure. Same Sequence. Same Origin. Same Function. Same 3D fold.

Download Presentation

Sequence Homology Treat or Trick?

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Sequence homology treat or trick

Sequence Homology Treat or Trick?

Fine Grain Structural Classification using the T-RMSD method

Cedric Notredame

Luis Serrano

Cedrik Magis

François Stricher

Almer van der Slot


Same sequence same structure

Same sequence Same structure

Same

Sequence

Same

Origin

Same

Function

Same

3D fold


Same sequence same structure1

Same sequence Same structure ???

Prion protein

PrP-c

(normal)

Prion protein

PrP-sc

(pathology)

100% Identical

Sequence

>P04156|23-230 / PRIO_HUMAN

KKRPKPGGWNTGGSRYPGQGSPGGNRYPPQGGGGWGQPHGGGWGQPHGGGWGQPHGGGWGQPHGGGWGQGGGTHSQWNKPSKPKTNMKHMAGAAAAGAVVGGLGGYMLGSAMSRPIIHFGSDYEDRYYRENMHRYPNQVYYRPMDEYSNQNNFVHDCVNITIKQHTVTTTTKGENFTETDVKMMERVVEQMCITQYERESQAYYQRGS

100% Identical

Sequence


Tnf receptors tnfrs

TNF Receptors (TNFRs)

Receptor

Ligand

Intra

Extra

Aggarwal, BB. Nat RevImmunol. 2003 Sep;3(9):745-56.


Tnfrs the cystein rich domains crds

TNFRs: The Cystein Rich Domains (CRDs)

Turn

1

Loop

1

Loop

2

Turn

2


Tnfr and crd collections

TNFR and CRD Collections

Domain Databases

UNIPROT

17

4

2

34

10

0

1

25 annotated

notidentified

6 putativesnotidentified


This suggests the crds are homogenous

This suggests the CRDs are homogenous


Is it supported by 3d superposition

Is it supported by 3D Superposition ?


Classifications

Classifications

  • If they are so different and diverse

    • Can we classify them?

    • Can this classification bring functional information?


Structurally

Structurally?

Not really…


Phylogeny

Phylogeny?

Not quite there…


Add hoc

Add-hoc?

Maybe…


Add hoc1

Add-hoc?

Maybe…

Bodmer, JL., Schneider, P., Tschopp, J. Trends Biochem. Sci. 2002 Jan;27(1):19-26.


Add hoc2

Add-hoc?

  • Half Domains

  • Complex

  • Explains Little

Maybe…


A new classification

A new Classification ?

  • Is it possible to design a new classification

    • Structure based

    • Functionally informative

    • Predictive for TNFRs without a known structure

  • Yes if we can compare structures in a more informative way


The standard way rmsd root mean square deviation

The Standard Way: RMSD(Root Mean Square Deviation)

  • RMSD

    • Superpose the Structures

    • Measure The deviation

D1

D2

Z

X

D3

Y

W


A simpler alternative the irmsd

A Simpler Alternative: the iRMSD

D2

D1

D1

D2


T rmsd trees based on irmsd

UPGMA

C

A

B

D

T-RMSD: Trees based on iRMSD

Dd2

Dd1

A

B

C

D

P1

Distance

Matrix

P1

B


T rmsd trees based on irmsd1

C

A

B

D

T-RMSD: Trees based on iRMSD

Dd1

Dd2

A

B

C

D

P1

A

A

C

C

C

A

B

B

B

D

D

D

Consensus Tree


T rmsd vs clustering

T-RMSD Vs Clustering


T rmsd vs clustering1

T-RMSD Vs Clustering


Does the clustering make sense

Does The Clustering Make Sense ?


Well conserved inserts

Well Conserved Inserts ?


What does the new classification predict

What Does the New Classification Predict ?

Type I

Type II

Type III

Outliers


What does the new classification predict1

What Does the New Classification Predict ?

Type I

Type II

Type III

Outliers

Nter CRDs (Pre Ligand Assembly

Domains, PLAD) are involved in the

complex formation


Sequence homology treat or trick

Next ???

  • New Classes ?

  • New Functions ?

  • New Structures

???


Sequence homology treat or trick

Next ???

  • Which Ligand

  • How To Align These things

    • MSA problem

???


Summary

Summary

  • T-RMSD

    • Fine Grain Structural Classification

  • TNFRs/CRD

    • New typology

    • Structurally meaningful

    • Functionally informative

    • Predictive

  • T-RMSD is available for download and part of the T-Coffee package (www.tcoffee.org)

  • Collaborators

    • Cedrik Magis

    • François Stricher

    • Almer van der Slot

    • Luis Serrano

    • Cedric Notredame


  • Login