Aligning Kinases

Applying MSA Analysis to the CDK family

Building A Multiple Sequence Alignment

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chite AATAKQNYIRALQEYERNGG-wheat ANKLKGEYNKAIAAYNKGESAtrybr AEKDKERYKREM---------mouse AKDDRIRYDNEMKSWEEQMAE * : .* . :

Extrapolation

Motifs/Patterns

Phylogeny

Profiles

Struc. PredictionMultiple Alignments Are CENTRAL to MOST Bioinformatics Techniques.

Potential Uses of A Multiple Sequence Alignment?

1

Organizing a Family Gathering

The CDK example

Choosing the Right Sequences

SwisProt Litterature Other Databases

Organizing the Data

SRS

PublicData

IGSData

Aventis

CDKGenecard

Manual

Automatic

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

Our CDK Data

CDKs and CDK-like– Protein Information

Functional Features Structural Information

– Genomic Information Genes Variant SNPs

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

2

Aligning The Sequences

Building A Multiple Sequence Alignment

ClustalW T-Coffee Muscle Hand Editing

Combination Comparison

Using Structural Information3D-Coffee

Struct Vs StructSeq Vs Struct

ThreadSuperpose

Seq Vs SeqLocalGlobal

Method

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

3

Dressing Up a

Multiple Sequence Alignment

Feature Dressing

-25 Binding site-20 Phospho-40 nsSNP-50 Splice Site…………

Escript

Feature Dressing

4

How Good Is The Alignment

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T-Coffee CORE Evaluation

T-Coffee CORE Evaluation

CORE index

Specificity () and Sensitivity ()

Feature Based Evaluation

Features mapping on multiple alignment

T-coffee

ATP binding site

Glycine loop

ATP binding siteATP binding site

Glycine loop

Non-synonymous SNP

ClustalW

Structure Based EvaluationAPDB

Structure Based EvaluationAPDB

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

Evaluating a Multiple Sequence Alignment

T-Coffee CORE index Feature Based Library APDB

Maninupulating and Comparing Alignments

Reformating/Processing– seq_reformat– extract_from_pdb

Coloring– seq_reformat– ESCript

Comparing– aln_compare

5

Thinking Large

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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

Using A Multiple Sequence Alignment

1

Exploring The Alignment

Exploring The Alignment

Cdk's signatureCdk's T-loop (orange) and aurora's Activating loop

Substrat recognition motif

2

Using The Alignment

Does my Sequence Make Sense

Identifying Abnormalities within an MSA

Insertion within the NucBinding Site…

Identifying Abnormalities within an MSA

Identifying Abnormalities within an MSA

Identifying Abnormalities within an MSA

Activation loop (orange)

Identifying Abnormalities within an MSA

Retinoblastoma

2

Using The Alignment

Analysing the Structure withThe Alignment

The Evoltionnary Trace

3

Using The Alignment

Spotting differences

What makes a CDK not and AurorA

4

Clustering and Correlating

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