ACS National Meeting San Diego 2016

Applications of drug-target data in translating genomic variation into drug discovery opportunities

Anna Gaulton European Molecular Biology Laboratory – European Bioinformatics Institute

4. Insight, tools and resources for translational drug discovery 1. Scientific facts

Bioactivity data

Compound

Ass

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>Thrombin MAHVRGLQLPGCLALAALCSLVHSQHVFLAPQQARSLLQRVRRANTFLEEVRKGNLERECVEETCSYEEAFEALESSTATDVFWAKYTACETARTPRDKLAACLEGNCAEGLGTNYRGHVNITRSGIECQLWRSRYPHKPEINSTTHPGADLQENFCRNPDSSTTGPWCYTTDPTVRRQECSIPVCGQDQVTVAMTPRSEGSSVNLSPPLEQCVPDRGQQYQGRLAVTTHGLPCLAWASAQAKALSKHQDFNSAVQLVENFCRNPDGDEEGVWCYVAGKPGDFGYCDLNYCEEAVEEETGDGLDEDSDRAIEGRTATSEYQTFFNPRTFGSGEADCGLRPLFEKKSLEDKTERELLESYIDGRIVEGSDAEIGMSPWQVMLFRKSPQELLCGASLISDRWVLTAAHCLLYPPWDKNFTENDLLVRIGKHSRTRYERNIEKISMLEKIYIHPRYNWRENLDRDIALMKLKKPVAFSDYIHPVCLPDRETAASLLQAGYKGRVTGWGNLKETWTANVGKGQPSVLQVVNLPIVERPVCKDSTRIRITDNMFCAGYKPDEGKRGDACEGDSGGPFVMKSPFNNRWYQMGIVSWGEGCDRDGKYGFYTHVFRLKKWIQKVIDQFGE

2. Organization, integration, curation and standardization of pharmacology data

Ki = 4.5nM

APTT = 11 min.

ChEMBL

3. Drug annotation

ChEMBL •  Manually curate efficacy targets for FDA approved drugs (and more

recently, clinical candidates)

•  Targets with which drug interacts directly

•  Targets responsible for efficacy in approved indication

•  Protein and non-protein targets included

•  Human and pathogen targets included

•  References provided (e.g., publications, prescribing information)

•  NOT targets responsible for adverse-effects or non-approved indications

•  NOT targets assigned purely on basis of pharmacology data

•  Deal with non-specific drugs and targets that are protein complexes

•  Annotate drug type (small molecule, antibody etc), action type (e.g., agonist, antagonist), and binding site/subunit information where available

Bento et al (2013) DOI: 10.1093/nar/gkt1031

ChEMBL target types

DNA  HEK293  cells   Nervous  

GABA-­‐A  receptors   Muscarinic  receptors  

Mitochondria  

Protein Nucleic-Acid Complex Small Molecule

                     Ribosome          Methotrexate  

Molecular

Nucleic acid Protein

Single Protein Protein Complex Protein Complex Group Protein Family Protein-Protein Interaction

Integrin  alpha-­‐4/beta-­‐7  PDE5   p53-­‐MDM2  

ChEMBL target data model

Natalizumab CHEMBL1201607 Integrin α4/β7

CHEMBL2095184

Integrin β7 P26010

Integrin α4 P13612

Drug Mechanism Target Target components (mAb) (target/action type) (protein complex) (proteins)

Integrin α4/β7 inhibitor

Binding site

References

ChEMBL efficacy targets

ChEMBL bioactivity data

Applications

Target identification Target prioritization Target validation

Open PHACTS Illuminating the Centre for Therapeutic Platform Druggable Genome Target Validation

De-convoluting phenotypic screens Identifying understudied targets Identifying target-disease evidence

https://www.openphacts.org https://pharos.nih.gov/idg/index https://www.targetvalidation.org

Mendelian Randomization Natural genetic variation can be considered analogous to a randomized controlled trial

Coronary heart disease risk

Randomized Controlled Trial

Intervention: statin at start of treatment Target: HMGCR enzyme

Drug perturbation of ‘disease’ gene function

HOO

O

OHO

Placebo

Mendelian Randomization Genetic perturbation of ‘disease’ gene function Intervention: genetic variation in HMGCR gene at birth

Target: HMGCR gene

aa allele ab allele bb allele

Cholesterol Treatment Trialists’ Collaborators (2012) DOI:10.1016/S0140-6736(12)60367-5; Ference, BA et al (2012) DOI:10.1016/j.jacc.2012.09.017

Genome-wide association studies •  Genotyping studies of large numbers of patients can identify associations

between genetic variants (SNPs) and diseases/traits

•  101 RA risk loci (42 novel) from 100,000 subjects -> 98 candidate genes.

Okada et al (2014) DOI:10.1038/nature12873

Use of drug target information

•  Authors looked at whether any of candidate proteins were targets for existing drugs (approved and experimental)

•  27 proteins were targets of approved drugs for RA (confirmed associations)

•  Additional targets identified that had drugs for other indications - potential drug repurposing opportunities: •  E.g., CDK4 and CDK6 identified as candidate genes

Palbociclib is an approved CDK4/6 inhibitor for breast cancer

•  Understanding of mechanism of action and targets of existing drugs is therefore crucial in exploiting genetic association data

•  Even if approved drugs/clinical candidates not already available for a target, knowledge of druggability (likelihood target can be modulated by a drug-like small molecule or biotherapeutic) important in prioritizing proteins for follow-up studies, identifying tool compounds etc

Use of drug target information

•  Furthermore, knowledge of drug target information can impact the design of genetic association studies

•  In order to identify novel druggable targets linked to a disease, important to sample variation within these genes

•  Various types of genotyping array used for genetic association studies

•  Genome wide association studies – arrays with broad coverage across genome (e.g., Illumina HumanCore, Exome, Affymetrix UK Biobank Array)

•  Gene-centric arrays – arrays with dense coverage of genes relevant to a particular therapeutic area (e.g., Cardiochip, Metabochip)

•  Opportunity for an array providing dense coverage across the whole druggable genome

http://www.illumina.com/techniques/microarrays/human-genotyping/human-genotyping-arrays.html; http://www.affymetrix.com/estore/catalog/prod730013/AFFY/Axiom%26%23174%3B+Biobank+Genotyping+Arrays#1_1; Barrans et al (2001) DOI:10.1006/bbrc.2000.4137; Voight et al (2012) DOI:10.1371/journal.pgen.1002793

Design of a new genotyping array •  We compiled an updated view of the druggable genome (including targets for

protein therapeutics), based on data in ChEMBL, UniProt, GO and Ensembl

•  Genes were divided into three tiers based on confidence in druggability

•  Tier 1 – clinical precendence (1427 genes): •  Targets of drugs (ChEMBL efficacy targets),

•  Targets of clinical candidates (Pharma pipelines, Clinical trials, USANs)

•  Proteins involved in ADME (PharmaADME.org)

•  Tier 2 – druggable proteins (682 genes): •  Targets with potent, drug-like small molecules (ChEMBL bioactivity data)

•  Close homologues of drug targets (>50% identity to ChEMBL efficacy targets)

•  Tier 3 – likely druggable proteins (2370 genes): •  Extracellular proteins (UniProt and GO annotation)

•  Members of druggable gene families (>25% identity to ChEMBL efficacy targets, kinases, GPCRs, NHRs, Ion channels, phosphodiesterases)

•  Total 4479 genes (high-confidence, precedence-based druggable genome)

Selection of content

•  Array based on existing Illumina HumanCore BeadChip*

•  180,000 additional SNPs added

•  Additional content selected from 1000 genomes European populations

•  SNPs considered within +/-2.5kb of each druggable gene

•  Prioritized Tag SNPs (those associated with others at r2>0.8)

•  Excluded very rare SNPs (MAF threshold >= 0.015)

•  HumanExome content and 6400 SNPs from GWAS studies also included

•  Infinium® DrugDev Consortium Array*: •  485,000 SNPs total

•  Average 50 SNPs per druggable gene (80 Tier 1 -> 25 Tier 3)

•  ~87% coverage (MAF >= 0.05) and ~68% coverage (MAF >= 0.005) of 1000 genomes variants within druggable genes (r2>= 0.8, European populations)

http://www.illumina.com/science/consortia.html *For Research Use Only. Not for use in diagnostic procedures.

Applications of DrugDev array

Targets of FDA approved drugs Drug repurposing opportunities

Targets of clinical candidates Target validation, drug trial support and stratification

ADME targets Pharmacogenomics, safety and differential response

Targets binding small molecules Prioritization/initiation/de-risking discovery programs

Extracellular proteins Address important future role of mAbs

Members of druggable families Identification of novel tractable targets

The research leading to these results has received support from: Strategic Awards from the Wellcome Trust [WT086151/Z/08/Z and WT104104/Z/14/Z]; Member States of the European Molecular Biology Laboratory (EMBL); University College London Hospitals National Institute of Health Research Biomedical Research Centre; the British Heart Foundation [BHF Project Grant PG12/71/29684], the Innovative Medicines Initiative Joint Undertaking under grant agreement no. [115191]; the National Institutes of Health under award number [U54CA189205]; the Centre for Therapeutic Target Validation and Pfizer.

Acknowledgements

EMBL-EBI ChEMBL team1

Aroon Hingorani2

Chris Finan2

Felix Kruger2,6

Tina Shah2

Jorgen Engmann2 Juan-Pablo Casas2,3 John Overington1,6 Anneli Karlsson1,6 Rita Santos1,7 Luana Galver McAuliffe4 Ryan Kelley4 Cora Vacher5

Ian Dunham8

1.  European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK

2.  Institute of Cardiovascular Science, University College London, UK

3.  Farr Institute in London, University College London, UK 4.  Illumina Inc, San Diego, USA 5.  Illumina UK Ltd, Little Chesterford, UK 6.  Stratified Medical, London, UK (current) 7.  GlaxoSmithKline, Stevenage, UK (current) 8.  Centre for Therapeutic Target Validation, Cambridge, UK