Transcript Research questions

The Open Pharmacological
Concepts Triple Store
www.openphacts.org
The Innovative Medicines Initiative
– EC funded public-private partnership for
pharmaceutical research
– Focus on key problems
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Efficacy
Safety
Education & Training
Knowledge Management
www.openphacts.org
Public Domain is engaging in Drug
Discovery (DD)
Public Domain Chemistry Resources
are improving
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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
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2008
NIH Roadmap Initiative
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2006
Sorel Muresan, Peter Varkonyi, Chris Southan
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?
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 www.openphacts.org
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 offtarget effects and safety pharmacology
analyse chemical motifs against biological effects to deconvolute
high content biology assays
www.openphacts.org
Major Work Streams:
• “Build”: OPS service layer and resource integration
• “Drive”: Development of exemplar work packages & Applications
• ”Sustain”: Community engagement and long-term sustainability
‘Consumer’
Firewall
Target
Dossier
Pharmacological
Networks
Compound
Dossier
OPS Service Layer
Assertion & Meta Data Mgmt
Transform / Translate
Integrator
Std Public
Vocabularies
Business
Rules
Supplier
Firewall
Work Stream 2: Exemplar Drug Discovery Informatics tools
Develop exemplar services to test OPS Service Layer
Target Dossier (Data Integration)
Pharmacological Network Navigator (Data Visualisation)
Compound Dossier (Data Analysis)
Work Stream 1: Open Pharmacological
Space (OPS) Service Layer
Standardised software layer to allow public
DD resource integration
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Db 2
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Db 4
Corpus 1
Db 3
Corpus 5
Define standards and construct OPS service layer
Develop interface (API) for data access, integration
and analysis
Develop secure access models
Existing Drug Discovery (DD) Resource
Integration
Open PHACTS follows a use case driven approach
Main architecture, technical implementation and primary capabilities are driven by
a set of prioritised research questions
Milestone 1 (month 1)
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
www.openphacts.org
Research questions
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Give all compounds with IC50 < 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
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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
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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 bloodbrain barrier permeation and tissue distribution
Target validation work-bench: in silico target validation studies
www.openphacts.org
Prioritised Research Questions
Number
sum
Nr of 1
Question
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All oxido,reductase inhibitors active <100nM in both human and mouse
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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?
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Given a target find me all actives against that target. Find/predict polypharmacology of actives. Determine
ADMET profile of actives.
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For a given interaction profile, give me compounds similar to it.
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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.
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59
14
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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
www.openphacts.org
Prioritised Research Questions
Prevalent Concepts
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Compound
Bioassay
Target
Pathway
Disease
Prevalent data relationships
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Required cheminformatics functionality
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Chemical substructure searching
Chemical similarity searching
Required bioinformatics functionality
Sequence and similarity searching
Bioprofile similarity searching
Compound – target
Compound – bioassay
Bioassay – target
Compound – target – mode of action
Target – target classification
Target – pathway
Target – disease
Pathway - disease
www.openphacts.org
Selection of prioritised data sources
Chemistry
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Chembl (top)
DrugBank
Chebi
Wombat (commercial)
Pubchem
Chemspider
Human Metabolome DB
Ontologies
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Biology
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EntrezGene
HGNC
Uniprot
Interpro
SCOP
Wikipathway
OMIM
IUPHAR
AmiGo
KEGG
OBI
Bioassay
EFO
www.openphacts.org
Nanopublications – Capturing scientific information in
the Triple Store
Second milestone: Deliver a working prototype of “Open
Pharmacological Space” in 6 months using established technology
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”
www.openphacts.org
Expected outcomes of this
exercise:
Build the prototype:
Concept
WikiUI
Concept
Wiki
Identity
Resolution
Service
Utopia
Docs
Path
Physio
User
Interface
software
Term
mapping
Team building
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Performance / scalability
analysis
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Does it provide an
adequate answer to the
research questions 15 and
30?
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Demo for users (drive
group) to recalibrate build
tasks in order to better
respond to user
requirements
SPARQL
Bridge
DB
IRS to disambiguate
Other
mappings
Uri mapping
LarKC in the
core
LarKC
SPARQL or LarKC plugin
Data sources
Linked
Open
DrugData
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ChEMBL
ChemDistributed
ScaiView
system Concept
Wiki
Spider
Index
Linked
LifeData
www.openphacts.org
Wiki
Pathways
Use the prototype: Connection with user needs - Exemplars
The three Exemplars:
• Target dossier
• Chem/bio space navigator
• Polypharmacology browser
Developers
(Builders)
The Apps must provide answers to
relevant research questions
• Interrogation model
• GUI/interactivity
• Presentation of results
End users
(Drivers)
GUI - User suggestions for workflow
Select question
(“template”
from category)
Fill in template variables
Via “relation browser”
and add filters
Execute search
View results, filter and
export dataset
Select relevant
data sources
(IC50 value, dates etc)
www.openphacts.org
Modify query
(change concepts
and attributes)
Chem-Bio-Navigator (BioSolveIT / UHH)
Research
Questions
Data objects
User interface
design
Use
cases
System
architecture
• Compound centric view:
Intuitive Browsing
• single molecules
OMe
MeO
MeO
NH2
N
N
NH2
• molecular sets
Graphical annotation
• 2D / 3D?
Powerful data selection
Overall aim: Mixing Cheminformatics with RDF data access
M. Rarey / C. Lemmen
Target dossier (CNIO)
Benchmarking approach for the
Target Dossier
www.openphacts.org
Polypharmacology browser (DTU)
Chemical centric
From WP4 data stored
Annotation
Prediction
based on:
- Chemical structure similarity
- Chemical bioactivity similarity
- Proteins promiscuity
Target centric
PPI
- Disease(s) – gene(s)
- Tissue specificity
- Gene ontology, side effects
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 -
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.
www.openphacts.org
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
www.openphacts.org
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