SMR kinase meeting October 2013

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Presentation from the SMR kinase meeting held at NHLI on Thursday 3rd October 2013

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SMR kinase meeting October 2013

  1. 1. John Overington EMBL-EBI jpo@ebi.ac.uk Kinases: The Clinical Kinome and role in Neglected Disease
  2. 2. Overview • Establishing a View of the Clinical Kinome • Sources of Kinase SAR data – ChEMBL and Kinase SARfari • Community precompetitive efforts – GSK PKIS • Kinase inhibitors in neglected disease – Tuberculosis HTS analysis
  3. 3. What is the Current Clinical Kinome? • No simple way of finding out • Classic ‘competitive intelligence’ problem – Many commercial systems exist – expensive and closed – No redistribution, no integration, no freedom! • We built our own dataset – There is a lot of interesting stuff on the internet – PRISM – Proactive Retrieval of Interesting Structures and Mechanisms – Open Data
  4. 4. What is the Current Clinical Kinome? • Phased strategy to building – Approvals – US/Europe/Japan – USAN/INN Process documents – Clinical Trials (http://www.clinicaltrials.gov) – Company pipeline documents – Chinese compound vendors • Focus on highest phase, chemical structure, research codes, intended efficacy targets – Not commercial/deal information, specific trials, outcomes, etc.
  5. 5. The Clinical Kinome
  6. 6. Clinical Kinome • 396 Clinical stage human kinase inhibitors – 30 Approved small molecule kinase inhibitors • 15 -tinib – tyrosine kinase inhibitors • 7 -rolimus – mTor inhibitors • 4 -rafenib – Raf inhibitors • 2 -anib – angiogenesis inhibitors • 1 -metinib – met inhibitor • 1 -dil – Rho kinase inhibitor (Japan only) – 36 Phase 3 – 138 Phase 2 – 192 Phase 1 • Phase 1:2 ratio is atypical due to many trials being phase 1/2 oncology trials • Assembling an Open Access physical panel ca. 270 inhibitors
  7. 7. Kinase Inhibitors in Clinical Development
  8. 8. Companies Developing Kinase Inhibitors
  9. 9. Kinase Inhibitor Attrition
  10. 10. Kinase Inhibitor Attrition USAN to approved fraction! – ~0.2 is long term mean for all drugs across all classes
  11. 11. Productivity By Company n.b. Includes all inhibitors, regardless of in-/cross-licensing activity
  12. 12. Polypharmacology of Kinase Inhibitors US launched Tofacitinib Tozasertib (Ph. II) LapatinibGefitinibErlotinib Staurosporine (no trials) Sunitinib Sorafenib Imatinib Dasatinib Adapted from Ghoreschi et al, Nature Immunology 10, 356 - 360 (2009)
  13. 13. Drug Pharmacokinetics Imatinib, 200 mg uid Concentration(ng/mL) Time (hr) 0 500 1000 1500 48 96 144 192 2400 • Large ‘tides’ of target exposure during dosing schedule Filppula et al, Clin. Pharmacol & Therap (2013) 94 383-389
  14. 14. Extraction & Curation of PK Data
  15. 15. Imatinib Target Spectra 6.0 Tyrosine-protein kinase FYN 5.38 ATP-binding cassette sub-family G member 2 5.39 c-Jun N-terminal kinase 1 5.40 Serine/threonine-protein kinase 17A 5.41 c-Jun N-terminal kinase 3 5.50 Dual specificity protein kinase CLK4 5.53 Mixed lineage kinase 7 5.59 Tyrosine-protein kinase FGR 5.62 Tyrosine-protein kinase FRK 5.64 Maternal embryonic leucine zipper kinase 5.72 Serine/threonine-protein kinase GAK 5.72 Ephrin type-A receptor 8 5.77 Serine/threonine-protein kinase RAF 5.77 Interleukin-1 receptor-associated kinase 1 5.92 Tyrosine-protein kinase LCK 7.00 Platelet-derived growth factor receptor alpha 7.09 Carbonic anhydrase 15 7.11 Carbonic anhydrase IX 7.12 Platelet-derived growth factor receptor beta 7.14 Tyrosine-protein kinase ABL 7.20 Platelet-derived growth factor receptor 7.30 Discoidin domain-containing receptor 2 7.34 Epithelial discoidin domain-containing receptor 1 7.37 Carbonic anhydrase I 7.50 Carbonic anhydrase II 7.52 Tyrosine-protein kinase ABL2 7.94 Carbonic anhydrase XII 6.01 Homeodomain-interacting protein kinase 4 6.02 Tyrosine-protein kinase Lyn 6.05 Carbonic anhydrase III 6.28 Tyrosine-protein kinase BLK 6.28 Carbonic anhydrase XIV 6.33 BCR/ABL p210 fusion protein 6.41 Carbonic anhydrase VI 6.41 Phosphatidylinositol-5-phosphate 4-kinase type-2 gamma 6.42 Macrophage colony stimulating factor receptor 6.54 Stem cell growth factor receptor 6.62 Bcr/Abl fusion protein 6.66 Carbonic anhydrase VII 6.96 7.0 8.0 Imatinib 400 mg single dose from Jawhari et al (2011) J. Bioequiv. Availab. 3 161-164; Data is median pChEMBL values for human targets from ChEMBL 16 Concentration(ng.ml-1) Time (hr)
  16. 16. Kinases in ChEMBL • 625 protein kinase targets • 601,895 kinase associated bioactivities
  17. 17. Kinases in ChEMBL
  18. 18. Kinases in ChEMBL
  19. 19. Kinase SARfari
  20. 20. ‘Full Matrix’ Kinase Datasets in ChEMBL • Ambit Biosciences – 72 compounds against 442 targets – Nature Biotechnology 2011, 29 (11), 1046-1051 • Millipore – 158 compounds against 234 targets – 73,944 data points • DrugMatrix – 860 Compounds against 132 targets • 53 7TMs, 10 kinases, 7 P450s, 6 proteases, hERG, 54 others – https://ntp.niehs.nih.gov/drugmatrix/index.html • GSK Published Kinase Inhibitor Set (PKIS) – 367 inhibitors published by GSK covering >20 chemotypes – Measurements (so far) from 2 screening panels • Nanosyn and UNC
  21. 21. PKIS Compound Clustering (a) The size and diversity of the PKIS compound classes, with representative structures. The height of each bar represents the number of compounds within each class. The segments within each indicate different compound clusters, defined by a sphere exclusion method. Compound clustering was based upon Daylight Tanimoto fingerprint similarity (www.daylight.com) with a cluster radius of 0.85, as outlined by Taylor 68 and applied by Martin, Kofron and Traphagen 69. (b) Histograms of molecular weight and cLog P values for PKIS compounds.
  22. 22. Frequency of inhibition by the PKIS set Frequency of inhibition of kinases by the PKIS. Increasing size and red colour of circles is related to the number of PKIS compounds inhibiting each kinase by 50% at 0.1 µM compound.
  23. 23. SB-202190 SB-220025 SB-218078SB-203580 Insights into Selectivity/Promiscuity
  24. 24. Kinase Inhibitors & Neglected Disease • Much activity in Malaria and TB for kinase inhibitors – Questions over selectivity for host kinases? • Our own work has focused on HTS triage/target ID from a phenotypic TB screen
  25. 25. TB HTS • GSK Tres Cantos labs – L. Ballell, R.H. Bates, R.J. Young, D. Alvarez-Gomez, E. Alvarez-Ruiz, et al. (2013) ‘Fueling Open-Source Drug Discovery: 177 Small-Molecule Leads against Tuberculosis’. ChemMedChem. – All data in http://dx.doi.org/10.6019/CHEMBL2095176 • 776 potent M.tb BCG – 177 confirmed actives in M.tb H37Rv pathogenic strain • Three approaches to predict targets • Naïve Bayes models • Docking • Nearest neighbour – F. nez- nez, G. Papadatos, L. Yang, I.M. Wallace, V. Kumar, U. Pieper, A. Sali, J.R. Brown, J.P. Overington, & M.A. Marti-Renom. (2013) ‘Target prediction for an open access set of compounds active against Mycobacterium tuberculosis’, PLoS Comp. Biol. In press.
  26. 26. Kinases in M.Tb • Between 4 and 20 kinases in Mycobaterium spp. – pknA and pknB essential for M.tb viability – pknB predicted to be target for 4 GSK compound clusters
  27. 27. Docking of GSK1132084A into M.tb. pknB GSK1598164A and ATP docked to active site of pknB crystal structure (3F69) GSK1598164A ATP
  28. 28. Acknowledgements Krister Wennerberg Prson Gautam Bissan Al-Lazikani Francis Atkinson Mark Davies Gerard Van Westen George Papadatos Anne Hersey Bill Zuercher Jim Brown Francisco nez- nez Marc Marti-Renom cnag
  29. 29. http://chembl.blogspot.com

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