SLAS2016: Why have one model when you could have thousands?

Why have one modelwhen you could have thousands?

Alex M. Clark, Ph.D.

January 2016

© 2016 Molecular Materials Informatics, Inc. http://molmatinf.com

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Cheminformatics• Generally 2D structures with activities:

• Look for trends: structure-activity relationships

• Leverages quantity rather than detail... but quality is also supremely important

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Structure-Activity Models

• Bayesian models very effective

• Tabulate structure fingerprints for actives vs. inactives

• Prediction: ordering, probability

• Low maintenance

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10001001000001101001011101110111

• ECFP6 fingerprints

0.8343ROC integral

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The Data Problem• > 10 years ago: quantity the biggest issue

- open structure-activity data rare and small - paid collections, big pharma registration

• ~5 years ago: quality the biggest issue

- huge databases, e.g. PubChem, ChemSpider, ZINC, vendors, etc.

- generally no provenance: anything goes

• Cheminformatics seemed to be stagnant...

- new methods, same mediocre performance

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The Data Solution• Recently: some excellent developments

- Open Melting Points: models actually work - PubChem: direct submission by scientists - CDD: store and share with same platform - ChEMBL: large, open, high quality, broad

• Can now have quantity and quality, without fees or restrictions

• Evidence suggests that the data was holding us back, not the methods

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ChEMBL• Hierarchy looks like this:

• What we need it to be:

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target assay activity molecule

dataset assayactivitymolecule

target

mergedactivity

materialsfor model

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Slicing & Dicing

• Divide by target, species and type of assay (protein binding, whole cell, ADMET, etc.)

• Measurements: [Ki, Kd] or [IC50, EC50, AC50, GI50]

• Units: [M, mM, μM, nM]

• Relations [=, <, >, ≤, ≥]

• Total of 8646 groups of structure-activity

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Consolidation• Strip salts / adducts

• Common organic elements only:

- [H, C, N, O, P, S, F, Cl, Br, I, B, Si, Se, As, Sb, Te]

• Duplicate molecules: merge activities, e.g.

- [1.2, 1.8] ➡ 1.5 ± 0.3 - [> 5, 5.5] ➡ > 5 - [< 1, 3.5] ➡ invalid

• Keep groups with at least 100 molecules remaining

• Now down to 1839 datasets

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Model Building• Bayesian models need a threshold...

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pIC50 9 157 3

inactive active

• Suitable values often known; large scale automation: must estimate

• Score: population, balance, trial Bayesian

• See J. Chem. Inf. Model. 55, 1246-1260 (2015)

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Model Results

• Metrics generally good for Bayesian models using ECFP6 fingerprints

• Note that not all datasets have any SAR

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AU

C (

easy

)

AU

C (

hard

)

population population

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Deliverable• Datasets with acceptable models: 1826

- list of unique molecules - activity (standard molar units) - threshold (active/inactive) - target & assay provenance - Bayesian model (ECFP6)

• Targets are diverse, data is high quality: thanks to the ChEMBL project

• Can apply all models to any molecule...

• Start with a set of discontinued drugs...

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Discontinued Drugs12

• ~50 drugs that passed most tests, but never made it to market

• Maybe they cure something else?

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Detail & Visualisation13

Atom-centric Bayesian

Honeycomb clustering

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PolyPharma app

• Proof of concept tools being explored for several drug discovery collaborations

• Interactive functionality demonstrated as a mobile app for iPhone & iPad

• Free to use

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http://itunes.apple.com/app/polypharma/id1025327772

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Acknowledgments

http://molmatinf.com http://molsync.com http://cheminf20.org

@aclarkxyz

• Collaborative Drug Discovery

• Sean Ekins

• Society for Laboratory Automation & Screening

• Inquiries to info@molmatinf.com