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A novel interactive tool for multidimensional biological data analysis. Zhaowen Luo, Xuliang Jiang Serono Research Institute, Inc. Outline. Introduction Methods Applications and Examples H2L decision making Multiple kinases inhibitors analysis. 1. Introduction.

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a novel interactive tool for multidimensional biological data analysis

A novel interactive tool for multidimensional biological data analysis

Zhaowen Luo, Xuliang Jiang

Serono Research Institute, Inc.

outline
Outline
  • Introduction
  • Methods
  • Applications and Examples
    • H2L decision making
    • Multiple kinases inhibitors analysis
data representation in drug discover
Data representation in drug discover
  • Two dimensional view: Chemistry vs. Biology
    • Chemistry – different compound structures
    • Biology - different assay data (potency, selectivity profiles, ADEM/PK and toxicity).
  • A heat map is a graphical representation of data where the values taken by a variable in a two-dimensional map are represented as colors. (WikiPedia).

Heat map meets the need of data representation in drug discovery and could be a good decision support tool.

my first heat map
My first heat map

A 200 X 200 Map

Nice picture

Some interesting patterns

But what is that???

heat map is not enough
Heat map is not enough
  • Lack of interactivity:
    • Difficult to retrieve information
    • Unable to display related information, such as structure
  • Static
    • Unable to manipulate data
    • Unable to do real-time analysis

Solution: Fully interactive heat map application – only application can satisfy all need for decision support.

features
Features

Point to any point in heat map, a tooltip box will show structure as well as assay result.

Double click on any points will bring user to the source of original data

Draw a box in heat map will create a focus heat map for the area of interesting.

More details about the point shows here

example of focus map
Example of focus map

Assay Name

Compound ID

more operations
More operations
  • Color spectrum can be changed.
  • Map Orientation can be changed.
  • Data analysis tools
    • Data points can be re-arranged based on analysis results.
    • Analysis results can be exported.
normalize biological endpoints
Normalize biological endpoints
  • Problem: Compare Orange with Apple
  • Solution: Use relative scale: MIN-MAX method
    • Define good and bad end for each endpoint.
    • Normalize result based both ends
  • For different kinds of assays, we define deferent methods to normalize result.
  • User can customize their own normalization methods.
normalization examples
Normalization examples
  • Potency – Enzyme Assay - logIC50
    • Good: -8
    • Bad: -5
  • Potency – Cell Based Assay – logIC50
    • Good: -7
    • Bad: -4.5
  • Cytochrom C P450 Inhibition – logIC50
    • Good: -4.5
    • Bad: -7
  • Rat T1/2
    • Good: > 2 hours
    • Bad: < 0.25 hour

Bad

Good

normalized results
Normalized results

Raw Data (different units)

Normalized data (No unit)

Assays as descriptors

Compounds as descriptors

Distance Matrix

For Compounds

Distance Matrix

For Assays

data analysis
Data analysis

Distance Matrix

Sorting

Clustering

Similarity analysis

  • Analysis can be done for compounds and assays
  • Based on biological assays results
  • Results can exported to Excel file for further analysis
structural analysis
Structural analysis
  • Clustering and sorting compounds by their structural similarity.
    • Using fingerprint to calculate the similarity between compounds.
  • Provides structural-activity representation and analysis.
business consideration
Business consideration
  • Hide information
    • Use generic name for compounds and assays
      • For example, compounds use prefix and sequence number.
    • Use generic structure, such as Benzene, to hide real structure.
    • Look-up table for symbol replacement
  • Offline (offsite) capability
    • Export and import heat map to binary file
    • Re-import map offline without connecting to corporate database.
application development
Application development
  • JAVA™ JDK 1.5 (from Sun Microsystems)
  • ChimePro™ for JAVA from MDL
  • CDK
  • JDBC 1.4 from Oracle

Features:

  • Direct extract structural and assays information from Accord Enterprise database, MDL ISIS/Host database.
  • Web deployed (Java Web Start)
h2l project data analysis and decision making
H2L Project data analysis and decision making

Heat map details:

  • 214 compounds from a list of Accord Enterprise
  • 18 assays in four assays group
    • Potency
    • CYP450 inhibition
    • In vitro ADME
    • In vivo PK
focus on most active area top area
Focus on most active area (top area)

All top compounds are in clinical

or lead candidates

summary for h2l data analysis
Summary for H2L data analysis
  • Bring together structural, as well as many biological assays for a discovery project.
  • Multiple dimensional data analysis
    • Most activity compounds is not the top compounds in overall profile score.
    • Heat map can pick up the drug candidates

Problems:

  • Missing data point: lots of compounds do not have in vivo data.
  • Clustering analysis is not accurate in this case.
kinase activity and selective analysis
Kinase activity and selective analysis

Heat map details:

  • 105 positives in multiple kinases screen
  • 12 Kinase assays
    • 4 Kinase family
      • AGC
      • OTHER
      • STE
      • TK
sorted by active profile
Sorted by Active Profile

Multiple-kinase inhibitors are ranked in top.

cluster by structural similarity
Cluster by structural similarity
  • Compounds are colored by clusters
  • Cluster 1: AGC-2, Other_3, and TK_10 inhibitors
  • Cluster 2: Other_3 inhibitors
  • Pan-inhibitors
  • Structural similar compounds (in same structural cluster) have similar kinase inhibitory behaviors.
cluster by overall kinase inhibitory profile
Cluster by overall kinase inhibitory profile

Multiple inhibitor cluster

Three singlet exhibit different inhibitory pattern

AGC_1 inhibitor cluster

AGC_1,AGC_2 and TK_10 inhibitors

cluster assays based on overall compounds profile
Cluster assays based on overall compounds profile
  • The clusters of assays based on compounds profile is not same as phylogeny tree.
  • Identify kinases with possible cross-interaction.
summary of kinase inhibitors heat map
Summary of kinase inhibitors heat map
  • Identify pan-inhibitors.
  • Graphics structural-activity relationship
  • Identify kinase inhibitors activity patter for selectivity analysis.
  • Clustering kinase based on compounds profile and identify possible cross-interaction group.
conclusion
Conclusion
  • Provide a interactive graphics tool for decision making in drug discovery process.
    • Direct get data from corporate database
    • Interactive
    • Information-rich: structural and biological assay in one place
    • One-stop shop for information analysis of drug discovery
  • Statistic analysis based on result code provides powerful tool in decision making
    • Based on overall biological profile
    • Can pick winner in H2L process
    • Provide useful SAR analysis for compounds
    • Provide selectivity profiles for biological targets.
acknowledge
Acknowledge

Ben Askew

Steve Arkinstall

Brian Healey