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

1. John Overington
EMBL-EBI
jpo@ebi.ac.uk
Kinases: The
Clinical Kinome
and role in
Neglected Disease

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. 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. 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. The Clinical Kinome

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. Kinase Inhibitors in Clinical Development

8. Companies Developing Kinase Inhibitors

9. Kinase Inhibitor Attrition

10. Kinase Inhibitor Attrition
USAN to approved fraction! – ~0.2 is long term mean for all drugs across all classes

11. Productivity By Company
n.b. Includes all inhibitors, regardless of in-/cross-licensing activity

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. 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. Extraction & Curation of PK Data

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. Kinases in ChEMBL
• 625 protein kinase targets
• 601,895 kinase associated bioactivities

17. Kinases in ChEMBL

18. Kinases in ChEMBL

19. Kinase SARfari

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. 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. 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. SB-202190 SB-220025
SB-218078SB-203580
Insights into Selectivity/Promiscuity

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. 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. 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. Docking of GSK1132084A into M.tb. pknB
GSK1598164A and ATP docked to
active site of pknB crystal structure
(3F69)
GSK1598164A ATP

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. http://chembl.blogspot.com