1 / 38

Signals in Sequences

Signals in Sequences. The number of sequences available for analysis rapidly approaches infinite. We need new ways to look at all this information. Rule 1. First rule of sequence analysis: If a residue is conserved, it is important. Rule 2. Second rule of sequence analysis:

weaverj
Download Presentation

Signals in Sequences

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. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Signals in Sequences The number of sequences available for analysis rapidly approaches infinite. We need new ways to look at all this information.

  2. Rule 1 First rule of sequence analysis: If a residue is conserved, it is important.

  3. Rule 2 Second rule of sequence analysis: If a residue is very conserved, it is very important.

  4. GPCR Project GPCR is THE drug target. Lots of data available. You have ~630 GPCRs. Little structure data. 2000 sequences known. ‘Easy’ to align.

  5. The GPCR (rhodopsin)

  6. 1 conserved aa / helix!

  7. Laerte about modelling: “Use the sequence, Luke”

  8. Conserved, CMA, variable QWERTYASDFGRGH QWERTYASDTHRPM QWERTNMKDFGRKC QWERTNMKDTHRVW Black = conserved White = variable Green = correlated mutations(CMA)

  9. CMA and tree 1 ASASDFDFGHKM 2 ASASDFDFRRRL 3 ASLPDFLPGHSI 4 ASLPDFLPRRRV

  10. CMA versus tree 1 ASASDFDFGHKMGHS 2 ASASDFDFRRRLRHS 3 ASLPDFLPGHSIGHS 4 ASLPDFLPRRRVRIT 5 ASASDFDFRRRLRIT 6 ASLPDFLPGHSIGIT Red : 1,2,5 vs 3,4,6 Black : 1,3,6 vs 2,4,5 Yellow: 1,2,3 vs 4,5,6

  11. CMA on GPCR

  12. CMA on GPCR

  13. Florence Horn

  14. Class B Ligands

  15. Class B – ligand docking

  16. G protein-coupling?

  17. Sequence Signals • Three classes of residues • Conserved • CMA • Variable

  18. Conservation Artefacts Conservation can result from Not enough sequences Too conserved sequences Over-alignment

  19. Variability Artefacts Variability can result from Wrong sequence choice Variable loops Alignment errors

  20. CMA Artefacts CMA can result from Wrong sequence choice Poor sequence homogeneity Over-fitting

  21. Recalcitrant residues

  22. Sequence Entropy 20 Ei = S pi ln(pi) i=1

  23. Sequence Variability Sequence variability is the number of residues that is present in more than 0.5% of all sequences.

  24. Entropy - Variability Entropy = Information Variability = Chaos

  25. Entropy - Variability Variability is result of evolution. Entropy is the protein’s break on evolutionary speed.

  26. GPCR Entropy - Variability 11 Red 12 Orange 22 Yellow 23 Green 33 Blue

  27. GPCR Location 11 Red 12 Orange 22 Yellow 23 Green 33 Blue

  28. Ras Entropy - Variability

  29. Ras Location 11 Red 12 Orange 22 Yellow 23 Green 33 Blue

  30. Protease Entropy - Variability

  31. Protease Location 11 Red 12 Orange 22 Yellow 23 Green 33 Blue

  32. Globin Entropy - Variability GPCR

  33. Globin Location 11 Red 12 Orange 22 Yellow 23 Green 33 Blue

  34. GPCR Again….

  35. GPCR Location (Again) 11 Red 12 Orange 22 Yellow 23 Green 33 Blue

  36. GPCR signaling 11 Purple 12 Red 22 ‘Yellow’ 23 Green 33 Blue

  37. Summary Given infinitely many sequences: Every residues role known. Signaling paths detectable. So, sequences contain many signals

  38. Thanks to: Laerte Oliveira Sao Paulo Wilma Kuipers Weesp Florence Horn San Francisco Bob Bywater Copenhagen Nora vd Wenden The Hague Mike Singer New Haven Ad IJzerman Leiden Margot Beukers Leiden Amos Bairoch Geneva Fabien Campagne New York

More Related