Ad hoc - canSAR

Integrated Cancer Drug Discovery Resource
http://cansar.icr.ac.uk
Bissan Al-Lazikani
Mark Halling-Brown
Cancer
Therapeutics
Unit
Data Growth to
Aid Translational Research
Source: http://www.ddbj.nig.ac.jp/
Source canSAR
Lukk et al. Nat. Biotech. (2010) 28:322-324
Translating data  drugs
needs effective integration
Need
•  Resource to effectively integrate large diverse
data
•  See wide context around target/compound/ of interest
•  Get quick idea about state of public knowledge
•  Aid decision making
•  Target prioritization
•  Driving hypotheses
•  Next experiment?
•  Live, frequently updated
http://cansar.icr.ac.uk
canSAR:
Extensible modular content
Public Data in canSAR
•  Molecular Targets
• 
•  Human proteome
•  Model organisms
•  Functional annotation
(GO, Pathway Commons ..)
•  3D structure (PDB)
•  Mutations and
variants (COSMIC, CGP)
•  Protein interaction
networks (ROCK, STRING)
• 
Compounds and chemical• 
screening
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Gene Expression
–  Array Express
chEMBL-DB
–  Cell line
Binding-DB
–  Tissue
Genomics of Drug Sensitivity –  NCI-60
NCI-60
FDA approved drugs
Clinical Candidates (ongoing)
Cell lines
–  chEMBL
–  NCI-60
–  GDS
• 
Clinical associations
–  DrugStore
–  Ad hoc
Using
http://cansar.icr.ac.uk
Instant look-see!
•  Target or Compound synopsis , summarising
current data
Chemical Annotation
of Protein Interaction Networks
•  Identify network context
for target(s)
•  View chemical and
structural annotation on
network
•  Identify potential
druggable targets within
interaction network
Bioactivity Profiles and
Polypharmacology Maps
Identify cross-reactivity for a chemical hit series or within target set
Off target effect within single family or across all protein families
Chemogenomic Annotation
of Large Gene Sets
Batch-summarizing and chemical/structural/functional
annotation of large data sets (e.g. siRNA hit lists)
Aid triaging and prioritizing targets
Identify patterns in data
canSAR Plans
•  By Sept 2010
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Extend functionality and documentation
Add siRNA data
Extend 3D data
Network annotator
•  Over next year
•  Expand data sources (metabolomics, ChiP seq, shRNA,
CGH, ….)
•  Clinical outcome data
•  Improve chemical annotation
•  “Expert” tools
•  Clinical candidate
Acknowledgements
•  CBC team
–  Krishna Bulusu
–  Mish Patel
–  Joe Tym
•  Marketa Zvelibil
•  Costas Mitsopoulos
•  Paul Workman, Paul Clarke
•  chEMBL
& Co.
•  Mike Gilson + Binding DB
•  Julian Blagg and team
•  Genomics of Drug
•  Janet Shipley and team
Sensitivity/ Sanger
•  Array Express
•  Rob Van Montfort and
•  PDBe
Swen Hoelder
http://cansar.icr.ac.uk
[email protected]