SlideShare a Scribd company logo
in partnership with
Probe Miner
Harnessing large-scale public data for the objective
assessment of chemical probes
Albert A. Antolin, Joe E. Tym, Angeliki Komianou, Ian Collins, Paul Workman & Bissan Al-Lazikani
Department of Data Science and Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK.
2018 AACR National Meeting, Chicago, USA.
Disclosure Information
AACR National Meeting
Albert A. Antolin
I have no personal financial relationships to disclose.
Employee of ICR which has multiple commercial interactions
and
I will not discuss off-label use and/or investigational use in my
presentation.
2
Previous LiteratureOnline search enginesCompound vendor catalogs
Limitations of current approaches to chemical probe selection
3
Liu, et al. Clin Cancer Res, 2012
Blagg & Workman, Cancer Cell, 2017
The Chemical Probes Portal and potential for synergies
•  Expert-curated resource that recommends probes for specific targets
4
Arrowsmith, et. al., Nat Chem Biol, 2015
Synergistic
Genuine PARP
inhibitor
Can we exploit large-scale public data
for the objective assessment and prioritization of
bioactive compounds as potential chemical probes?
5
Methods: Sources of Data
•  canSAR (https://cansar.icr.ac.uk/)
•  Integrated multidisciplinary curated data
6
Tym, et. al., Nucleic Acids Res., 2016
>150,000 visitors in 2016
> 2.1 M chemical compounds
14.6 M bioactivity data points
2.8 M mutations from patients
> 228,000 clinical trials
Chemical probes for the human proteome
•  Systematically and objectively analyzing compounds available in public
databases as chemical probes
7
Antolin, et. al., Cell Chem Biol., 2018
Human proteome
∼20,171 proteins
NAR, 2016
https://cansar.icr.ac.uk/
The Druggable proteome 8
Antolin, et. al., Cell Chem Biol., 2018
Human proteome
∼20,171 proteins
NAR, 2016
22 – 40%
Druggable proteome
Nature Rev. Drug Discov. 2013
Sci. Trans Med., 2016
Probing the liganded proteome 9
Antolin, et. al., Cell Chem Biol., 2018
Human proteome
∼20,171 proteins
NAR, 2016
22 – 40%
Druggable
11%
Liganded
2,220 proteins
How well can we
probe the biology
of this liganded
proteome?
Assessing the quality of chemical probes in public databases
Minimum-quality criteria
10
Antolin, et. al., Cell Chem Biol., 2018
Human proteome
∼20,171 proteins
NAR, 2016
22 – 40%
11%
Target
Potency
≤ 100 nM
Target
Selectivity
10-fold
>1 protein
Cell
Potency
< 10 µM
Workman & Collins, Chem. Biol., 2010
How much of the liganded proteome can we probe? 11
Antolin, et. al., Cell Chem Biol., 2018
Human proteome
∼20,171 proteins
NAR, 2016
22 – 40%
11%
Target
Potency
74%
Target
Selectivity
40%
Cell
Potency
55%
Minimally acceptable probes
Target Potency,
Cell Potency
& Target Selectivity
9%
We can probe for less than 2% of the human proteome
We don’t have the appropiate tools for target validation
12
Antolin, et. al., Cell Chem Biol., 2018
Human proteome
∼20,171 proteins
NAR, 2016
22 – 40%
11%
Minimally acceptable probes
Target Potency,
Cell Potency
& Target Selectivity
9%
We can probe for less than 2% of the human proteome
We don’t have the appropriate tools for target validation
13
Antolin, et. al., Cell Chem Biol., 2018
Human proteome
∼20,171 proteins
NAR, 2016
22 – 40%
11%
1.4%
We need more and
better chemical probes
to cover the proteome
Objective and quantitative assessment of chemical probes
From fitness factors to scores
14
Workman & Collins, Chem. Biol., 2010
Objective and quantitative assessment of chemical probes
From fitness factors to scores
15
Antolin, et. al., Cell Chem Biol., 2018
•  Compound-protein affinity values
•  Compound-cell line affinity values
•  Compound chemical structures
6 Chemical Probe Scores
Probe Miner website resource
User-friendly resource for the objective assessment of chemical probes
16
Antolin, et. al., Cell Chem Biol., 2018
http://probeminer.icr.ac.uk
Overview page
Summaries of the data and statistical analysis using our algorithm
17
Antolin, et. al., Cell Chem Biol., 2018
Overview page
Easy-to-navigate distribution of the 20 highest-ranking probes
18
Antolin, et. al., Cell Chem Biol., 2018Antolin, et. al., Cell Chem Biol., 2018
Overview Page
Compound viewer interactively linked to the distribution
19
Antolin, et. al., Cell Chem Biol., 2018Antolin, et. al., Cell Chem Biol., 2018
Overview Page
Compound viewer interactively linked to the distribution
20
Antolin, et. al., Cell Chem Biol., 2018Antolin, et. al., Cell Chem Biol., 2018
Individual chemical probe page
Extended details on raw data, protein affinity profile and cross-references
21
Antolin, et. al., Cell Chem Biol., 2018
The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If the red x still appears, you may have to delete the image and then insert it again.
The Chemical Probes Portal & Probe Miner
SYNERGIES
22
PARP1: Large-scale assessment highlights recent data 23
Antolin, et. al., Cell Chem Biol., 2018
Probe Miner and The Chemical Probes Portal:
Overall synergy
24
Antolin, et. al., Cell Chem Biol., 2018
Larger number of
publications and data
assessed
Information from journals not covered
by public medicinal chemistry
databases and in depth analysis of
selectivity and in vivo data.
ABCC8: wider coverage of Probe Miner
Probe Miner 2,220 targets; The Chemical Probes Portal > 140 targets
25
PDPK1: the value of expert curation in the Portal
and the challenge of automatically assessing selectivity
26
Challenging
comparison
when information
varies significantly
#1 #2
SMYD2: The value of regular updates of information 27
Data
Update
Future Plans
•  We will maintain Probe Miner and update it regularly to ensure topicality
•  We are already liaising with The Chemical Probes Portal to identify new
probes for expert assessment
•  We are already starting to extract and include selected chemical biology data
from a wider range of journals that are currently missing from medicinal
chemistry databases
28
Conclusions
•  Probe Miner: objective assessment of potential chemical
probes from large-scale literature data
•  We do not have enough high-quality chemical probes:
selectivity is the biggest hurdle
•  We urgently need to test selectivity more thoroughly and improve
how this data is captured in public databases
•  Synergy from the complimentary use of the experience and
knowledge of experts with large-scale computational data
analysis.
29
<2%
in partnership with
Thank you!
Bissan Al-Lazikani Paul Workman
DEPARTMENT OF DATA SCIENCE
Joe Tym
Angeliki Komianou
Elizabeth Coker
Costas Mitsopoulos
Carmen Rodriguez-Gonzalvez
Veronica Garcia-Perez
Sheng Yu
Catherine Fletcher
Sebastian Poetsrl
James Campbell
Patrizio di Micco
STMP Team
Paul Clarke
Chi Zhang
Alexia Hervieu
Ian Collins
Probe Miner AACR Annual Meeting, Chicago, 2018

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Probe Miner AACR Annual Meeting, Chicago, 2018

  • 1. in partnership with Probe Miner Harnessing large-scale public data for the objective assessment of chemical probes Albert A. Antolin, Joe E. Tym, Angeliki Komianou, Ian Collins, Paul Workman & Bissan Al-Lazikani Department of Data Science and Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK. 2018 AACR National Meeting, Chicago, USA.
  • 2. Disclosure Information AACR National Meeting Albert A. Antolin I have no personal financial relationships to disclose. Employee of ICR which has multiple commercial interactions and I will not discuss off-label use and/or investigational use in my presentation. 2
  • 3. Previous LiteratureOnline search enginesCompound vendor catalogs Limitations of current approaches to chemical probe selection 3 Liu, et al. Clin Cancer Res, 2012 Blagg & Workman, Cancer Cell, 2017
  • 4. The Chemical Probes Portal and potential for synergies •  Expert-curated resource that recommends probes for specific targets 4 Arrowsmith, et. al., Nat Chem Biol, 2015 Synergistic Genuine PARP inhibitor
  • 5. Can we exploit large-scale public data for the objective assessment and prioritization of bioactive compounds as potential chemical probes? 5
  • 6. Methods: Sources of Data •  canSAR (https://cansar.icr.ac.uk/) •  Integrated multidisciplinary curated data 6 Tym, et. al., Nucleic Acids Res., 2016 >150,000 visitors in 2016 > 2.1 M chemical compounds 14.6 M bioactivity data points 2.8 M mutations from patients > 228,000 clinical trials
  • 7. Chemical probes for the human proteome •  Systematically and objectively analyzing compounds available in public databases as chemical probes 7 Antolin, et. al., Cell Chem Biol., 2018 Human proteome ∼20,171 proteins NAR, 2016 https://cansar.icr.ac.uk/
  • 8. The Druggable proteome 8 Antolin, et. al., Cell Chem Biol., 2018 Human proteome ∼20,171 proteins NAR, 2016 22 – 40% Druggable proteome Nature Rev. Drug Discov. 2013 Sci. Trans Med., 2016
  • 9. Probing the liganded proteome 9 Antolin, et. al., Cell Chem Biol., 2018 Human proteome ∼20,171 proteins NAR, 2016 22 – 40% Druggable 11% Liganded 2,220 proteins How well can we probe the biology of this liganded proteome?
  • 10. Assessing the quality of chemical probes in public databases Minimum-quality criteria 10 Antolin, et. al., Cell Chem Biol., 2018 Human proteome ∼20,171 proteins NAR, 2016 22 – 40% 11% Target Potency ≤ 100 nM Target Selectivity 10-fold >1 protein Cell Potency < 10 µM Workman & Collins, Chem. Biol., 2010
  • 11. How much of the liganded proteome can we probe? 11 Antolin, et. al., Cell Chem Biol., 2018 Human proteome ∼20,171 proteins NAR, 2016 22 – 40% 11% Target Potency 74% Target Selectivity 40% Cell Potency 55%
  • 12. Minimally acceptable probes Target Potency, Cell Potency & Target Selectivity 9% We can probe for less than 2% of the human proteome We don’t have the appropiate tools for target validation 12 Antolin, et. al., Cell Chem Biol., 2018 Human proteome ∼20,171 proteins NAR, 2016 22 – 40% 11%
  • 13. Minimally acceptable probes Target Potency, Cell Potency & Target Selectivity 9% We can probe for less than 2% of the human proteome We don’t have the appropriate tools for target validation 13 Antolin, et. al., Cell Chem Biol., 2018 Human proteome ∼20,171 proteins NAR, 2016 22 – 40% 11% 1.4% We need more and better chemical probes to cover the proteome
  • 14. Objective and quantitative assessment of chemical probes From fitness factors to scores 14 Workman & Collins, Chem. Biol., 2010
  • 15. Objective and quantitative assessment of chemical probes From fitness factors to scores 15 Antolin, et. al., Cell Chem Biol., 2018 •  Compound-protein affinity values •  Compound-cell line affinity values •  Compound chemical structures 6 Chemical Probe Scores
  • 16. Probe Miner website resource User-friendly resource for the objective assessment of chemical probes 16 Antolin, et. al., Cell Chem Biol., 2018 http://probeminer.icr.ac.uk
  • 17. Overview page Summaries of the data and statistical analysis using our algorithm 17 Antolin, et. al., Cell Chem Biol., 2018
  • 18. Overview page Easy-to-navigate distribution of the 20 highest-ranking probes 18 Antolin, et. al., Cell Chem Biol., 2018Antolin, et. al., Cell Chem Biol., 2018
  • 19. Overview Page Compound viewer interactively linked to the distribution 19 Antolin, et. al., Cell Chem Biol., 2018Antolin, et. al., Cell Chem Biol., 2018
  • 20. Overview Page Compound viewer interactively linked to the distribution 20 Antolin, et. al., Cell Chem Biol., 2018Antolin, et. al., Cell Chem Biol., 2018
  • 21. Individual chemical probe page Extended details on raw data, protein affinity profile and cross-references 21 Antolin, et. al., Cell Chem Biol., 2018 The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If the red x still appears, you may have to delete the image and then insert it again.
  • 22. The Chemical Probes Portal & Probe Miner SYNERGIES 22
  • 23. PARP1: Large-scale assessment highlights recent data 23 Antolin, et. al., Cell Chem Biol., 2018
  • 24. Probe Miner and The Chemical Probes Portal: Overall synergy 24 Antolin, et. al., Cell Chem Biol., 2018 Larger number of publications and data assessed Information from journals not covered by public medicinal chemistry databases and in depth analysis of selectivity and in vivo data.
  • 25. ABCC8: wider coverage of Probe Miner Probe Miner 2,220 targets; The Chemical Probes Portal > 140 targets 25
  • 26. PDPK1: the value of expert curation in the Portal and the challenge of automatically assessing selectivity 26 Challenging comparison when information varies significantly #1 #2
  • 27. SMYD2: The value of regular updates of information 27 Data Update
  • 28. Future Plans •  We will maintain Probe Miner and update it regularly to ensure topicality •  We are already liaising with The Chemical Probes Portal to identify new probes for expert assessment •  We are already starting to extract and include selected chemical biology data from a wider range of journals that are currently missing from medicinal chemistry databases 28
  • 29. Conclusions •  Probe Miner: objective assessment of potential chemical probes from large-scale literature data •  We do not have enough high-quality chemical probes: selectivity is the biggest hurdle •  We urgently need to test selectivity more thoroughly and improve how this data is captured in public databases •  Synergy from the complimentary use of the experience and knowledge of experts with large-scale computational data analysis. 29 <2%
  • 30. in partnership with Thank you! Bissan Al-Lazikani Paul Workman DEPARTMENT OF DATA SCIENCE Joe Tym Angeliki Komianou Elizabeth Coker Costas Mitsopoulos Carmen Rodriguez-Gonzalvez Veronica Garcia-Perez Sheng Yu Catherine Fletcher Sebastian Poetsrl James Campbell Patrizio di Micco STMP Team Paul Clarke Chi Zhang Alexia Hervieu Ian Collins