Compound Set Enrichment

A novel approach to analysis of primary HTS data

Compound Set Enrichment

Thibault Varin Ansgar Schuffenhauer

Gubler, H., Parker, C., Zhang, JH., Raman, P., Ertl, P.

INTRODUCTION

| Compound Set Enrichment | Thibault Varin | 10/07/142


Introduction

Active series identification: Can relevant SAR be extracted from primary HTS data?

Are activity data binary or continuous?


IntroductionActive series identification


Hypothesis 1:Within primary HTS screening data, structure activity relationships (SAR) are apparent and can be used to help selecting active compound classes.

IntroductionAre the activity data binary or continuous?


Scaffold 1 Scaffold 2

Activity

Binary activity:-1 active / 5 inactives-Scaffold 1 = Scaffold 2

Continuous activity:Scaffold 1 > Scaffold 2

Active compound (binary)Inactive compound (binary)

N

N

NN

O

O

Introduction Are the activity data binary or continuous?


Threshold 1Activity

Threshold 2Activity

Binary scaffold activity is different according to the threshold

Active compound (binary)Inactive compound (binary)

Hypothesis 2:

Methods based on an activity cut-off distort the activity information leading to the incorrect assignment of active series of compounds.

N

N

N

METHODS



The Scaffold Tree – Visualization of the Scaffold Universe by Hierarchical Scaffold Classification A. Schuffenhauer, P. Ertl et al. J. Chem. Inf. Model., 47, 47, 2007

MethodsThe Scaffold Tree classification


MethodsDatasets


PubChem Annotationfrom CRC

Simulation of the primary screening data

Hypothesis 1

Methods Single hypothesis test: summary procedure

1. State the null and the alternative hypotheses

- H0: „the scaffold is inactive“

- H1: „the scaffold is active“

2. Specify a significance level: α=0.01

3. Compute the statistics and the p-value )→p-value=probability that the scaffold is inactive (H0)

4. Decision step:

- p-value> α: H0 is accepted

- p-value< α: H0 is rejected and then H1 is accepted„The scaffold is active“


Methods The KS and the Binomial hypothesis tests


Continuous dataKS test

Binary dataBinomial test

Actives Inactives

BioassayScaffold

H0: there is no difference in the activity distribution defined by compounds having the scaffold S3-2 and the background distribution

H0: there is no difference in the proportion of active compounds for compounds having the scaffold S3-2 and the proportion of active compounds for the full dataset.

Methods Multiple hypothesis tests: Bonferroni correction

Problem of false positives• α =probability to identify as active an inactive scaffold (for each test done...)

• 100 inactive scaffolds: probability to identify an „active“ by chance is equal 63% (1-0.99100))

Suggests to test each scaffold at a critical significance level equal to α = 0.01 / Nbr of scaffolds

Makes the assumption that the individual tests are independent

Each level in the Scaffold Tree have been done separately


MethodsDetermining the activity of classes


Hypo1

Hypo2

Scaffold activity evaluation

Comparison of results

Multiple hypothesis test correction (Bonferroni)

RESULTS



ResultsComparison of KSP and BTP predictions


BioassayTotal BPCA significantly

activesBPCA non significantly

actives

KSP BTP Δ BPCA KSP BTP Δ KSP BTP Δ

Hydroxysteroid dehydrogenase 330 231 +99 199 183 168 +15 147 63 +84

Caspase-1 331 114 +217 5 2 2 0 329 112 +217

PK 12 4 +8 12 3 3 0 9 1 +8

Luciferase 67 12 +55 15 13 11 +2 54 1 +53

Luciferase 178 48 +130 41 32 35 -3 146 13 +133

CYP450 2C9 58 33 +25 34 34 31 +3 24 2 +22

CYP450 3A4 121 64 +57 60 60 53 +7 61 11 +50With:-KSP: KS Prediction-BTP: Binomial Threshold Prediction-Δ: KSP-BTP-BPCA: Binomial PubChem Annotation

Both KSP and BTP retrieve BPCA significantly active classesNumber of active classes: KSP > BTPMost of new KSP active classes are not BPCA significantly actives

ResultsKSP significantly active scaffolds that are in Pubchem inactives


S

NH

S

O

O

NH

NH

O

NH

S O

O

O

N

N

Inconclusives?Inconclusive?

Inconclusives?

Compound activity (PubChem Annotation)

Active InconclusiveInactiveWA

WAWA

WA

ResultsPrioritize nodes instead of individual scaffolds


Scaffold activity (KS Prediction / Bonferroni)

Non significantly activeSignificantly active

ResultsVisualization tool (Peter Ertl)


CONCLUSION



ConclusionCompound Set Enrichment


Validation of initial hypotheses

A method to mine HTS data and identify active series of compounds• Chemical classification: Scaffold Tree

• Statistical analysis: Kolmogorov-Smirnov hypothesis test

• Multiple hypothesis test correction: Bonferroni correction

Use all primary data

No activity cut-off

Identification of new active scaffolds not necessarily represented by very active compounds (latent hits) during the primary screen

With many thanks to


Acknowledgments

Primary mentor: - Ansgar Schuffenhauer

Scientific advisers:-Christian Parker-Hanspeter Gubler-Ji-Hu Zhang-Peter Ertl-Edgar Jacoby

Help: MLI group

Fellowship: Education office

Discussions:-Martin Beibel-Sebastian Bergling-Meir Glick-Alain Dietrich-Marie-Cecile Didiot

Questions?


Documents

Compound Set Enrichment