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Aligning Kinases

Aligning Kinases. Applying MSA Analysis to the CDK family. Building A Multiple Sequence Alignment. Potential Uses of A Multiple Sequence Alignment ?. chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE

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Aligning Kinases

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  1. Aligning Kinases Applying MSA Analysis to the CDK family

  2. Building A Multiple Sequence Alignment

  3. Potential Uses of A Multiple Sequence Alignment? chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. ::: .: .. . : . . * . *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM--------- mouse AKDDRIRYDNEMKSWEEQMAE * : .* . : Extrapolation Phylogeny Multiple Alignments Are CENTRAL to MOST Bioinformatics Techniques. Motifs/Patterns Struc. Prediction Profiles

  4. 1 Organizing a Family Gathering The CDK example

  5. Choosing the Right Sequences • SwisProt • Litterature • Other Databases

  6. Organizing the Data PublicData Automatic SRS IGSData CDK Genecard Manual Aventis

  7. Accessing the Data: The Fischer Server • Fischer will Contain • A collection of Flat files • A secure SRS server • File Formats • The server is a Technology Pipeline • Can be adapted in real time • Can be Transfered

  8. Our CDK Data • CDKs and CDK-like • Protein Information • Functional Features • Structural Information • Genomic Information • Genes • Variant • SNPs

  9. Our MSA dataset • 29 amino acid sequences (CDKS and Aurora families, stemming from primary transcripts) • 2 isoforms of a cdk member • 4 PDB structures : • 1MUO (AUR A) • 1BLX (CDK 6 ) • 1b38 (CDK 2) • 1H4L (CDK 5) • Use of T-coffee release 1.78 with integration of the structure informations contained in pdb files

  10. 2 Aligning The Sequences

  11. Building A Multiple Sequence Alignment • ClustalW • T-Coffee • Muscle • Hand Editing • Combination • Comparison

  12. Using Structural Information3D-Coffee Seq Vs Seq LocalGlobal Seq Vs Struct Struct Vs Struct Thread Superpose

  13. Method

  14. Accessing the Methods:Fischer • Public 3D-Coffee server • igs-server.cnrs-mrs.fr/TCoffee/ • Fischer • Latest version of T-Coffee • Customised parameters • Coktails of MSA methods

  15. 3Dressing Up aMultiple Sequence Alignment

  16. Feature Dressing -25 Binding site -20 Phospho -40 nsSNP -50 Splice Site … … … … Escript

  17. Feature Dressing

  18. 4How Good Is The Alignment????

  19. T-Coffee CORE Evaluation

  20. T-Coffee CORE Evaluation Specificity () and Sensitivity () CORE index

  21. Feature Based Evaluation

  22. ATP binding site ATP binding site ATP binding site Glycine loop Glycine loop Non-synonymous SNP Features mapping on multiple alignment T-coffee ClustalW

  23. Structure Based EvaluationAPDB

  24. Structure Based EvaluationAPDB

  25. Structure Based EvaluationAPDB • Include Sequences with Known Structures • Do Not use Structural Information Score 1 • Use Structural Information: Score 2 • If Score1 ~ Score 2 • Structural Information does not help much • The alignment is of reasonnable quality

  26. Evaluating a Multiple Sequence Alignment • T-Coffee CORE index • Feature Based Library • APDB

  27. Maninupulating and Comparing Alignments • Reformating/Processing • seq_reformat • extract_from_pdb • Coloring • seq_reformat • ESCript • Comparing • aln_compare

  28. 5 Thinking Large ????

  29. T-Coffee_dpa • T-Coffee is limited to a small number of sequences • T-coffee_dpa: Double Progressive Algo • Able to handle large datasets • 1000 sequences and more • Able to use structural information

  30. Using A Multiple Sequence Alignment

  31. 1 Exploring The Alignment

  32. Cdk's T-loop (orange) and aurora's Activating loop Cdk's signature Substrat recognition motif Exploring The Alignment

  33. 2 Using The Alignment Does my Sequence Make Sense

  34. Insertion within the NucBinding Site… Identifying Abnormalities within an MSA

  35. Identifying Abnormalities within an MSA

  36. Identifying Abnormalities within an MSA

  37. Identifying Abnormalities within an MSA Activation loop (orange)

  38. Identifying Abnormalities within an MSA Retinoblastoma

  39. 2Using The AlignmentAnalysing the Structure withThe Alignment

  40. The Evoltionnary Trace

  41. 3 Using The Alignment Spotting differences

  42. What makes a CDK not and AurorA

  43. 4 Clustering and Correlating

  44. Function Trees Vs Lead Trees • 1-Select Functionnaly Important Positions • 2-Make a tree based on these positions • 3-Compare the tree with the lead tree • PROBLEMS: • Choose on the right positions • Describe the Leads with the right determinants

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