Work Package 6.1 ‘Pharmainformatics’

1. Work Package 6.1‘Pharmainformatics’

2. WP 6.1: Participants (thusfar) Johan van der Lei Marc Weeber Anke GJ De Bruijn Jordi Mestres Montserrat Cases Scott Boyer Kristina Hettne

3. WP 6.1 Pharmainformatics Information Continuum Pathology Pathway Target Ligand Ontologies Evolution

4. WP6.1 Coordination Meeting - 1 • June 3-4 Barcelona • IMIM, AZ, Erasmus, ISCIII • Three example disease areas • Interferon pathways in inflammation • Nuclear Hormone Receptors • Complex Regional Pain Syndrome

5. WP6.1 Coordination Meeting - 1 • June 3-4 Barcelona • IMIM, AZ, Erasmus, ISCIII • Three example disease areas • Interferon pathways in inflammation • Nuclear Hormone Receptors • Complex Regional Pain Syndrome

6. WP6.1 Working Meeting - 1 • August 23-27, Mölndal • IMIM, AZ, Erasmus • Focussed on CRPS Pathway documentation • What are the known Pathways • Complete picture of all theories • Are there any commonalities?

7. WP6.1 Working Meeting - 2 • September 27-30, Rotterdam • IMIM, AZ, Erasmus • Progress on CRPS • Firming up Pathways and important targets • Agreeing ‘Virtual Screening’ strategy • Review of IPCI Database

8. WP6.1 Working Meeting - 2 • September 27-30, Rotterdam • IMIM, AZ, Erasmus • Progress on NHR’s • Full listing of NHR’s and agreement on ontologies • Review of Growing Ligand Database • Planning of text mining of adverse events associated with PPAR agonists

9. WP6.1 Working Meeting - 2 • September 27-30, Rotterdam • IMIM, AZ, Erasmus • Clarification of exact work plans and activities

10. Complex Regional Pain Syndrome(CRPS) • Significant patient population • Several potential biochemical/physiological lesions • Several drug classes tried in the clinic • Large patient datasets (Trend Project & IPCI Database)

11. Complex Regional Pain Syndrome Pathology Pathway Target Ligand • Pathology to Pathway: Erasmus identifies all known pathways related to CRPS through literature mining, and share the information with AZ. • Pathway to Target: The known pathways are associated or expanded by Erasmus and AZ. Both obvious and non-obvious interactions will be investigated. Erasmus will use the knowledge retrieval tool Collexis and AZ the pathway analysis tool PathwayAssist for this purpose. • Target to Ligands/Approved Drugs:AZ and IMIM identify approved drugs or ligands that are active against members of the associated or expanded pathways,with the help of compound/ligand databases. • Target/Pathway to new Target/Pathway: Erasmus verifies in original population database if the found approved drugs are being used, what their indications are, whether it is possible to use them in CRPS or whether patients on these drugs have an altered incidence of CRPS.

12. Complex Regional Pain Syndrome(CRPS) Primary Question: Can we clarify possible pathological biochemical pathways and their constituent members against which we can then identify ligands that could be useful in understanding/treating CRPS?

13. WP 6.1 - CRPS Information Continuum Pathology Pathway Target Ligand Evolution

14. CRPS Pathways Neurogenic inflammation Sympathetically-maintained pain

15. Complex Regional Pain Syndrome(CRPS) Anke GJ De Bruijn

16. Complex Regional Pain Syndrome(CRPS) Anke GJ De Bruijn

17. Complex Regional Pain Syndrome(CRPS) Anke GJ De Bruijn

18. Approach: Brute Force Lock Anke, Marc & Kristina in a room for a week Feed them regularly Open literature & PathwayAssist

19. PathwayAssist • Interaction visualisation tool • Interaction extraction tool: Medline -> NLP -> ResNet • 4.6M sentences extracted from Medline (full text) • Recall low (21%) • Precision high (>90%) • Low recall? Term word recognition & lexicon errors • Large room for improvement • Not Open Source, Not FreeWare, but CheapWare

22. Simplified Picture of Possible CRPS Pathophysiology

23. Linear Model of Drug Discovery Target Identification Concept Testing Lead Optimisation Development for launch Target Validation Lead Identification Candidate Drug (CD) Target Compound Product

24. WP 6.1 - CRPS ’Target Identification’ Pathology Pathway Target Ligand Evolution Target Validation - Using BMI

25. Cluster analysis of all compounds in list (IMIM & AZ) Clustered NFkB List Run ’Known drug’ list against the clusters (IMIM & AZ) ’Unassociated’ Candidates Potency ranking By virtual screening ? (IMIM & AZ) Molecule List - NFkB Erasmus & AZ Filter by Drug list (Erasmus) Lower number of ’Drug-Like’ compounds Rank List by: Distances in ACS (Erasmus) Relationships in PA (AZ) Interaction Type & Number (All) Ranked List of Drugs Rank by potency against pathway (All) Final List of Drugs Deliverable Relative Risk Assessment in IPCI (Erasmus) Activity New Treatment Options For CRPS

26. Complex Regional Pain Syndrome Pathology Pathway Target Ligand • Pathology to Pathway: Erasmus identifies all known pathways related to CRPS through literature mining, and share the information with AZ. • Pathway to Target: The known pathways are associated or expanded by Erasmus and AZ. Both obvious and non-obvious interactions will be investigated. Erasmus will use the knowledge retrieval tool Collexis and AZ the pathway analysis tool PathwayAssist for this purpose. • Target to Ligands/Approved Drugs:AZ and IMIM identify approved drugs or ligands that are active against members of the associated or expanded pathways,with the help of compound/ligand databases. • Target/Pathway to new Target/Pathway: Erasmus verifies in original population database if the found approved drugs are being used, what their indications are, whether it is possible to use them in CRPS or whether patients on these drugs have an altered incidence of CRPS.

27. Nuclear Hormone Receptors & Clinical Adverse Events

28. Why NHRs? • One of the largest groups of transcription factors • 49 known • They regulate a broad spectrum of processes, including reproduction, development and general metabolism • Tissue distribution of co-factors varies and different ligands induce NHR binding with different co-factors = tissue-specific therapeutics • Receptor cross-talk & Structural similarity • Need for pathway mapping and annotation tools

29. Nuclear Hormone Receptors Primary Question: Can we associate preclincal & clinical adverse events from PPARg agonists to activities on any of the other nuclear hormone receptors?

30. Specific Activities: NHRs Pathology Pathway Target Ligand • Ligand to Target: IMIM and AZ identify relevant ligands and privileged structures. AZ to identify current PPARg agonists and communicate this list to Erasmus. • Target to Pathway: AZ, using the tool PathwayAssist and the target information from the previous step, identifies all pathways related to the targets. Erasmus use Collexis to differentiate or expand the pathways. • Pathway/Target to Genetic Variation and Clinical Adverse Events: Erasmus and AZ link individual members of the identified pathway to specific phenotypic information, i.e., phenotypes of genetic variants and deficiencies etc. Erasmus and AZ investigate whether any of the phenotypes identified from genetic variability are similar to the adverse effect patterns observed in PPARg agonist patients.

31. WP 6.1 - CRPS Information Continuum Pathology Pathway Target Ligand Evolution

32. Step I - Assemble Ligand Database AZ -> IMIM: Existing, literature-based NHR ligand database IMIM: Expand and systematically associate ligands to proteins

33. Step I - Assemble Ligand Database AZ -> IMIM: Existing, literature-based NHR ligand database IMIM: Expand and systematically associate ligands to proteins

34. Name Nomenclature No. Annotations DAX NR0B1 Orphan SHP NR0B2 Orphan Thyroid hormone alpha NR1A1 41 Thyroid hormone beta NR1A2 48 Retinoic acid alpha NR1B1 168 Retinoic acid beta NR1B2 169 Retinoic acid gamma NR1B3 160 PPAR alpha NR1C1 73 PPAR beta NR1C2 16 PPAR gamma NR1C3 217 REV-ERB alpha NR1D1 Orphan REV-ERB beta NR1D2 Orphan ROR alpha NR1F1 0 ROR beta NR1F2 0 ROR gamma NR1F3 0 Oxysterol LXR beta NR1H2 32 Oxysterol LXR alpha NR1H3 35 Farnesoid FXR NR1H4 20 Vitamin D3 (VDR) NR1I1 12 Pregnane X (PXR) NR1I2 9 Constitutive Androstane alpha (CAR1) NR1I3 1 HNF4 alpha NR2A1 Orphan HNF4 gamma NR2A2 Orphan RXR alpha NR2B1 57 RXR beta NR2B2 32 RXR gamma NR2B3 0 TR2 NR2C1 Orphan TR4 NR2C2 Orphan Tailless homolog (TLX) NR2E2 Orphan Tailless (TLL) NR2E3 Orphan Photoreceptor-specific (PNR) NR2F1 Orphan COUP-TFI NR2F2 Orphan V-erbA related protein (EAR2) NR2F6 Orphan ER alpha NR3A1 67 ER beta NR3A2 57 ERR alpha NR3B1 0 ERR beta NR3B2 0 ERR gamma NR3B3 0 Glucocorticoid (GR) NR3C1 112 Mineralocorticoid (MR) NR3C2 20 Progesterone (PR) NR3C3 138 Androgen (AR) NR3C4 113 NGFI-B (HMR) NR4A1 Orphan NURR1 NR4A2 Orphan NOR1 NR4A3 Orphan Steroidogenic factor-1 (SF1) NR5A1 Orphan Fetoprotein TF (LRH-1,FTF) NR5A2 Orphan GCNF1 NR6A1 Orphan Step II - Associate Ligands with Proteins

35. WP 6.1 - CRPS Information Continuum Pathology Pathway Target Ligand Evolution

36. Step III - Associate Proteins with Pathways NHR Signalling Pathway database essentially finished No standard nomenclature (detailed report, including deficiencies) No cross-talk mapped, but association simple in PA

37. Step III - Associate Proteins with Pathways Information sources • Internet pathway databases • BioCarta (21 NR pathways) • Cell Signaling Technology (2 NR pathways) • ExPasy Biochemical pathways map (3 NR pathways) • Kyoto Encyclopedia of Genes and Genomes, KEGG (1 NR pathway) • Signal Transduction Knowledge Environment, STKE (2 NR pathways) • PathwayAssist • 1 NR pathway • ResNet database of protein interactions

38. Specific Activities: NHRs Pathology Pathway Target Ligand • Ligand to Target: IMIM and AZ identify relevant ligands and privileged structures. AZ to identify current PPARg agonists and communicate this list to Erasmus. • Target to Pathway: AZ, using the tool PathwayAssist and the target information from the previous step, identifies all pathways related to the targets. Erasmus use Collexis to differentiate or expand the pathways. • Pathway/Target to Genetic Variation and Clinical Adverse Events: Erasmus and AZ link individual members of the identified pathway to specific phenotypic information, i.e., phenotypes of genetic variants and deficiencies etc. Erasmus and AZ investigate whether any of the phenotypes identified from genetic variability are similar to the adverse effect patterns observed in PPARg agonist patients.

39. Timings and Effort Distribution

40. 01-07-04 Year 1 Start date End date 1 2 3 4 5 6 7 8 9 10 11 12 Jul'04 Aug'04 Sep'04 Oct'04 Nov'04 Dec'04 Jan'05 Feb'05 Mar'05 Apr'05 May'05 Jun'05 01-07-04 30-06-05 01-07-04 31-08-04 01-09-04 31-10-04 01-11-04 30-11-04 01-12-04 31-01-05 01-02-05 30-04-05 NHR Ligand Database Fully Annotated NHR Pathway Maps Assessment of Major Adverse Events Associated with Overall NHR progress report 01-08-04 30-06-05 01-08-04 30-09-04 01-10-04 30-10-04 01-11-04 30-11-04 01-12-04 28-02-05 01-03-05 30-04-05 01-04-05 30-06-05 Defined Biochemical Pathways Associated with CRPS CRPS Ligand Database Assessment of current drug use and CRPS prevalence CRPS Progress Report WP 6.1 Timelines

41. Technology Issues

42. Preliminary thoughts on what WP6.1 needs from WP 4 & 5: BMI • WP4: Data interoperability & management • - data storage: preferred format for structural data for both molecules and proteins (pdb,mol2,sdf,xml?) • - data storage: preferred value for pharmacological data for molecules (Ki,pKi,IC50,pIC50,all?) • - integrating approaches: standards on annotation of pathways for the mapping to targets and diseases • - integrating approaches: linking GO to phenotype data • WP5: Methods, Technologies & Tools • - existing methods for the high-throughput systematic construction of protein models • - list of existing publicly accessible databases of protein models • - existing tools on molecule2target2pathway2disease mapping and access to such information continuum

43. Preliminary thoughts on what WP6.1 needs from WP 4 & 5 BMI • WP4 Data: • clinical data: • -how are they represented in the database (classification/free text/lab results/etc) . • - how to query clinical data with specific symptom/disease questions • - definition of patient history (see general details on CRPS in draft proposal) • - how to translate questions to employed clinical classification systems textual data: • - how are diseases described in natural language text • - available thesauri for diseases, drugs, chemicals, molecules, genes/proteins, genetic data: • - cross references of database IDs There is often not a 1-to-1 mapping • - merging or splitting of IDs, how to deal with them • WP5 Methods: • - interfacing different kind of databases • - use of text mining techniques • - mapping of terminologies (part of granularity mentioned above). • - pathway analys tools

44. Catalogue of Technology Gaps ? • WP 4 & 5 reports give us a good overview of what is possible now • Propose a ’Gaps Forum’ in the very near future • WP6 feedback to WP 4 & 5 • Need to run projects for a time • 1st Forum mid-year next year (with SAB)?

46. Thiazolidenediones & PPARg Nuclear Hormone Receptors Several compounds marketed and in development for the treatment of dyslipidemias associated with type II diabetes mellitus Clear patterns of adverse events associated with this therapy. Result of Target or Off-Target Effects?

47. Why NHRs? • One of the largest groups of transcription factors • 49 known • They regulate a broad spectrum of processes, including reproduction, development and general metabolism • Tissue distribution of co-factors varies and different ligands induce NHR binding with different co-factors = tissue-specific therapeutics • Receptor cross-talk & structural similarity • Need for pathway mapping and annotation tools

48. Nuclear Hormone Receptors Primary Question: Can we associate clinical adverse events from PPARg agonists to activities on any of the other nuclear hormone receptors?

49. WP 6.1 Effort Distribution 3/4Q 04 Effort: 6 PM 9 PM 6 PM

50. Ligand library Match against 1º and 2º targets Identify secondary target pathways