The Open Pharmacological Concepts Triple Store

The Innovative Medicines Initiative –EC funded public-private partnership for pharmaceutical research –Focus on key problems Efficacy Safety Education & Training Knowledge Management

Public Domain is engaging in Drug Discovery (DD) Public Domain Chemistry Resources are improving –NIH Roadmap Initiative Molecular Library Screening Center Network (MLSCN) PubChem (structure, bioassay and bioactivity data). –DrugBank, ChEBI, ChemBank and Chembl. Databases supporting biology-based DD are less apparent –Rich public domain resources for biology are not DD-centric Pharma Companies spend over $50 billion p.a. on R&D How much of this knowledge/information is in the public domain? How much knowledge is tacit? e.g. druggability? How much is truly competitive? Sorel Muresan, Peter Varkonyi, Chris Southan

Open PHACTS Project aims to Develop a set of robust standards… Implement the standards in a semantic integration hub (“Open Pharmacological Space”)… Deliver services to support on-going drug discovery programs in pharma and public domain… Guiding principle is open access, open usage, open source - Key to standards adoption - Guiding principle is open access, open usage, open source - Key to standards adoption -

OPS Services should allow to integrate data on target expression, biological pathways and pharmacology to identify the most productive points for therapeutic intervention investigate the in vitro pharmacology and mode-of-action of novel targets to help develop screening assays for drug discovery programmes compare molecular interaction profiles to assess potential off- target effects and safety pharmacology analyse chemical motifs against biological effects to deconvolute high content biology assays

Major Work Streams: “Build”: OPS service layer and resource integration “Drive”: Development of exemplar work packages & Applications ”Sustain”: Community engagement and long-term sustainability

Open PHACTS follows a use case driven approach Main architecture, technical implementation and primary capabilities are driven by a set of prioritised research questions Based on the main research questions, prioritised data sources are defined Three Exemplars will be developed to demonstrate the capabilites of the OPS System and to define interfaces and input/output standards Three Use cases have been defined to benchmark the OPS system towards current standard workflows in data retrieval and mining Milestone 1 (month 1)

Research questions –Give all compounds with IC 50 < xxx for target Y in species W and Z plus assay data –What substructures are associated with readout X (target, pathway, disease, …) –Give all experimental and clinical data for compound X –Give all targets for compound X or a compound with a similarity > y% Exemplar Services –Chem-Bio Navigator: querying and visualization of sets of pharmacologically annotated small molecules, on basis of chemical substructures, pharmacophores, biological activities –Target Dossier: in silico dossiers about targets, incorporating related information on sequences, structures, pathways, diseases and small molecules –Polypharmacology Browser: map coverage of the chemo-biological space, to facilitate the polypharmacological profiling of small molecules Drug Discovery Pilots/Case Studies –Fusion/aggregation of data from different domains to improve predictions of drug-transporter interactions –Combine physicochemical data and data from transporter interaction for prediction of blood- brain barrier permeation and tissue distribution –Target validation work-bench: in silico target validation studies

Prioritised Research Questions NumbersumNr of 1Question All oxido,reductase inhibitors active <100nM in both human and mouse Given compound X, what is its predicted secondary pharmacology? What are the on and off,target safety concerns for a compound? What is the evidence and how reliable is that evidence (journal impact factor, KOL) for findings associated with a compound? Given a target find me all actives against that target. Find/predict polypharmacology of actives. Determine ADMET profile of actives For a given interaction profile, give me compounds similar to it The current Factor Xa lead series is characterised by substructure X. Retrieve all bioactivity data in serine protease assays for molecules that contain substructure X Retrieve all experimental and clinical data for a given list of compounds defined by their chemical structure (with options to match stereochemistry or not) A project is considering Protein Kinase C Alpha (PRKCA) as a target. What are all the compounds known to modulate the target directly? What are the compounds that may modulate the target directly? i.e. return all cmpds active in assays where the resolution is at least at the level of the target family (i.e. PKC) both from structured assay databases and the literature Give me all active compounds on a given target with the relevant assay data Give me the compound(s) which hit most specifically the multiple targets in a given pathway (disease) Identify all known protein-protein interaction inhibitors

Prioritised Research Questions Prevalent Concepts –Compound –Bioassay –Target –Pathway –Disease Prevalent data relationships –Compound – target –Compound – bioassay –Bioassay – target –Compound – target – mode of action –Target – target classification –Target – pathway –Target – disease –Pathway - disease Required cheminformatics functionality –Chemical substructure searching –Chemical similarity searching Required bioinformatics functionality Sequence and similarity searching Bioprofile similarity searching

Selection of prioritised data sources Chemistry –Chembl (top) –DrugBank –Chebi –Wombat (commercial) –Pubchem –Chemspider –Human Metabolome DB Ontologies –AmiGo –KEGG –OBI –Bioassay –EFO Biology –EntrezGene –HGNC –Uniprot –Interpro –SCOP –Wikipathway –OMIM –IUPHAR

Nanopublications – Capturing scientific information in the Triple Store

Characteristics: Produce a working system (not a mockup) Constrained to use technologies present now in the consortium and a few data sources Focused on two prioritized research questions (Q15 and Q30) Q 15: All oxidoreductase inhibitors active <100nM in both human and mouse Q 30: For a given compound [clozapine], give me the interaction profile with [human or mouse] targets Minimum requirements: two data sources (one targets, one compounds) and able to produce answers in “manual time” Second milestone: Deliver a working prototype of “Open Pharmacological Space” in 6 months using established technology

Build the prototype: Expected outcomes of this exercise: Team building Performance / scalability analysis Does it provide an adequate answer to the research questions 15 and 30? Demo for users (drive group) to recalibrate build tasks in order to better respond to user requirements

Developers (Builders) End users (Drivers) The three Exemplars: Target dossier Chem/bio space navigator Polypharmacology browser The Apps must provide answers to relevant research questions Interrogation model GUI/interactivity Presentation of results Use the prototype: Connection with user needs - Exemplars

GUI - User suggestions for workflow Select question (“template” from category) Fill in template variables Via “relation browser” and add filters (IC50 value, dates etc) View results, filter and export dataset Select relevant data sources Execute search Modify query (change concepts and attributes)

Chem-Bio-Navigator (BioSolveIT / UHH) Compound centric view: Overall aim: Mixing Cheminformatics with RDF data access M. Rarey / C. Lemmen Data objects Use cases System architecture User interface design Research Questions Intuitive Browsing single molecules molecular sets Graphical annotation 2D / 3D? Powerful data selection

Benchmarking approach for the Target Dossier Target dossier (CNIO)

Polypharmacology browser (PSMAR)

Quick Summary of the Open PHACTS project Develop a set of robust standards to enable: –Solid integration between data sources via semantic technologies –Development of high quality assertions –Workflows and analysis pipelines across resources Implement the standards in a semantic integration hub (“Open Pharmacological Space”) –The core of the OPS call is to develop an open, public domain infrastructure for drug discovery data integration –Development of open web-services* for drug discovery –Development of a secure access model to enable queries with proprietary data (pharma, SME, NGO and PPP) Deliver services to support on-going drug discovery programs in pharma and public domain –Align development of standards, vocabs and data integration to selected drug discovery issues –Ensure focus and aligned priorities within Open PHACTS project Guiding principle is open access, open usage, open source - Key to standards adoption - Guiding principle is open access, open usage, open source - Key to standards adoption -

Open PHACTS Governance

Success Factors The ability of the platform to provide answers to drug discovery related questions and to be an integrated part of the drug-discovery workflow. Measurable use of the system beyond the original OPS partners, not only for direct knowledge discovery but also as a framework to build and deliver a wide range of services. OPS should grow to acceptable levels of quality, performance, usability and completeness and should be easily accessible and extendable within the scope of the project as a reliable enterprise system. Early community adoption through the engagement of 'associated partners' within and outside the European Union, among which are major data and infrastructure providers and networked initiatives Commercial information supply chain companies deliver data through and build services on top of OPS platform.

Open PHACTS Project Partners Pfizer Limited – Coordinator Universität Wien – Managing entity Technical University of Denmark University of Hamburg, Center for Bioinformatics BioSolveIT GmBH Consorci Mar Parc de Salut de Barcelona Leiden University Medical Centre Royal Society of Chemistry Vrije Universiteit Amsterdam Spanish National Cancer Research Centre University of Manchester Maastricht University Aqnowledge University of Santiago de Compostela Rheinische Friedrich-Wilhelms-Universität Bonn AstraZeneca GlaxoSmithKline Esteve Novartis Merck Serono H. Lundbeck A/S Eli Lilly Netherlands Bioinformatics Centre Swiss Institute of Bioinformatics ConnectedDiscovery EMBL-European Bioinformatics Institute Janssen Pharmaceutica OpenLink The Open PHACTS Foundation