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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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    Presentation Transcript
    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