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Building innovative
drug discovery alliances
Classification and analysis of 22 million
commercially available compounds
ChemAxon EUGM May 2013
PAGE
Agenda
 About Evotec
 About EVOsource
 Calculating Properties
 Analysis of the data
 Final Thoughts
1
PAGE 1) Manfred Eigen (*1927), German biophysical chemist and one of the worldwide leading pioneers in biotechnology. In 1967, he won the Nobel Prize in Chemistry for his
work on a special measuring method of fast chemical reactions, which, until then, were considered to be immeasurable. He initiated the foundation of Evotec AG.
A global company with a complete offering
Evotec worldwide operations
Sales representation (Boston, Tokyo)
Operations & sales representation
2
San Francisco,
US
~30 employees
 Compound
Procurement
 Compound QC
and storage
Abingdon,
UK
~215 employees
 Med Chem
 Comp Chem
 DMPK
 Structural biology
Munich,
Germany
~30 employees
 Phospho-
proteomics
 Chemical
proteomics
Göttingen, Germany
~50 employees
 Metabolics
 Regenerative
Medicine
Thane,
India
~130 employees
 Library synthesis &
mgmt.
 Development
chemistry
Hamburg,
Germany
~200 employees
 Screening
 HTS,NMR
 in vitro & in vivo
biology
Manfred Eigen1) Campus
PAGE
Agenda
 About Evotec
 About EVOsource
 Calculating Properties
 Analysis of the data
 Final thoughts
3
PAGE
EVOsource
4
Compound Sourcing
 Multiple search terms
 Single or combination
Category Count
 Suppliers 218
 Catalogues 539
 Unique
Compounds
22156696
 Parts 92490159
PAGE
EVOsource
5
Compound selection
 Can order from stores
 Can see if ordered
 Can order from supplier
 Can request a quote
 Can see if available in another
lab (or site)
 Additional information displayed
 JChem Cartridge accessed
through Java Persistence API
 Marvin Applet
 Structure to Name
 Standardizer
PAGE
The challenges of loading supplier catalogues
Integrated Cyclic Process
Process
Contact
Receive
Prepare
Load
 Receive catalogues
– New catalogues
– Catalogue updates
 Prepare catalogues
– Convert to SD file
– Structure Checker
– Structure to Name
– Name to Structure
 Contact Suppliers
– Existing suppliers
– Preferred suppliers
– New suppliers
 Process
– Fix errors
– Expire old data
 Load catalogue data
– Multiple parallel
processes
6
PAGE
Agenda
 About Evotec
 About EVOsource
 Calculating Properties
 Analysis of the data
 Final Thoughts
7
PAGE
Drug likeness categories
Classification of compounds
Feature count is defined as: # of 5- and 6-membered aromatic rings + # of Lipinski acceptors + # of Lipinski donors
Drug like
No SS fails
Lipinski fails ≤ 1
Additional property
constraints:
MOE LogP ≤ 6
MW ≤ 600
Rot bonds ≤ 10
EVO LogS ≥ -7
TPSA ≤ 180
Amber
No red SS fails
Lipinski fails ≤ 1
or
No SS fails
Lipinski fails ≤ 2
Red
Everything else!
Lead like
No SS fails
No Lipinski fails
Additional property
constraints:
MOE LogP ≤ 3.5
MW ≤ 350
Rot bonds ≤ 6
EVO LogS ≥ -5
TPSA ≤ 140
Fragments
No SS fails
No FSS fails
Lip. donors 1-3
Lip. acc. 0-4
MOE LogP ≤ 3.0
MW 150-350
Rot bonds ≤ 5
EVO LogS ≥ -3
TPSA ≤ 70
Feature count 4-7
8
PAGE
Property calculations
Historical process
Historical process
Export all structures
calculate properties using MOE
Structural alerts using MOE
Stored in a MOE database
Problems
Only available to Comp Chem Group
Difficult to update and time consuming
Different values using different tools – chemists use ChemAxon tools
to calculate properties
9
PAGE
Property calculations
New process stage 1
 Calculate simple properties
 Use ChemAxon JChem cartridge calculations where available
 Weekly job that calculates properties for new structures
 LogS uses MOE to calculate
 LogS manually updated every 2 months
10
PAGE
Calculated Results
Breakdown of chemical space by simple descriptors
MW HBD
HBA
logP RotB
11
PAGE
MOE SMARTS converted to ChemAxon format
Structural alerts using two types of filter
 121 SMARTS Structural Alerts – general screening compounds
 19 SMARTS Fragment filters – fragment screening
Assign compounds to category – fragment, lead like
etc.
Problems
 Took 6 months to calculate substructure search as had to be broken into
small chunks
 MOE SMARTS not automatically converted to ChemAxon format
Property calculations
New process stage 2
12
PAGE
Quantitative Estimate of Drug-likeness (QED)
New process stage 3
Quantifying the chemical beauty of drugs, A. L. Hopkins et al, Nature Chemistry 2012, 4, 90–9813
 QED calculation is based on similar parameters used to assign compounds to the Evotec
categories, each parameter is weighted from a model fitting
 A proof of concept was carried out on a subset of our screening collection
 Literature weights were modified with a bias in favour of structural alerts
 LogD was substituted for ALogP to consider ionisation
 QED calculation runs as a weekly job
Weighted QED
Relativefrequency
0.49 0.67
PAGE
What is a beautiful molecule?
Evotec weighted QED
14
QED = medium
QED = high
QED = low
PAGE
Agenda
 About Evotec
 About EVOsource
 Calculating Properties
 Analysis of the data
 Final Thoughts
15
PAGE
EVOsource composition
16
EVOsource composition
for Evotec drug-likeness classes
Weighted QED
Relativefrequency
15.3%
2.9M
26.9%
5.3M
57.8%
11.1M
0.49 0.67
EVOsource composition
for QED index
Lead-like 3.1M
Fragment-like 1M
Red 2.1M
Amber 4.2M
Drug-like 8.1M
PAGE
Excellent agreement of QED and Evotec flags to
discriminate between different drug-like classes
17
0.670.49
Relativefrequency
Weighted QED
QED index profile of each Evotec drug-likeness class
PAGE
EVOsource QED distribution shows large
overlap with orally available drugs
18
0.670.49
Weighted QED
Relativefrequency
Orally available
(682 analyzed out of 770)
EVOsource
Orally available drugs
EVOSource
PAGE
Agenda
 About Evotec
 About EVOsource
 Calculating Properties
 Analysis of the data
 Final Thoughts
19
PAGE
Final thoughts and Acknowledgements
 EVOsource provides:
 A useful tool for our chemists in ordering compounds for our clients
 A tool for our Computational Chemists to do analyses of chemical space to better support our clients in
library design
 QED calculation is providing a useful tool for filtering data to quickly make virtual
libraries
 QED has been added to latest version of ChEMBL
20
Thanks to:
Dr Oliver Barker
Dr Mirco Meniconi
Catherine Reisser
Dr Dan Warner
Your contact:
Building innovative
drug discovery alliances
Ian Berry Bob Marmon
Manager, Informatics Senior Applications Developer
+44.(0).1235.441451 Office +44.(0).1235.441402 Office
+44.(0) 7802.438044 Mobile +44.(0).1235.861561 Switchboard
+44.(0).1235.441503 Fax +44.(0).1235.441503 Fax
ian.berry@evotec.com bob.marmon@evotec.com

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EUGM 2013 - Ian Berry, Bob Marmon (Evotec): Classification and analysis of 21 million commercially available compounds

  • 1. Building innovative drug discovery alliances Classification and analysis of 22 million commercially available compounds ChemAxon EUGM May 2013
  • 2. PAGE Agenda  About Evotec  About EVOsource  Calculating Properties  Analysis of the data  Final Thoughts 1
  • 3. PAGE 1) Manfred Eigen (*1927), German biophysical chemist and one of the worldwide leading pioneers in biotechnology. In 1967, he won the Nobel Prize in Chemistry for his work on a special measuring method of fast chemical reactions, which, until then, were considered to be immeasurable. He initiated the foundation of Evotec AG. A global company with a complete offering Evotec worldwide operations Sales representation (Boston, Tokyo) Operations & sales representation 2 San Francisco, US ~30 employees  Compound Procurement  Compound QC and storage Abingdon, UK ~215 employees  Med Chem  Comp Chem  DMPK  Structural biology Munich, Germany ~30 employees  Phospho- proteomics  Chemical proteomics Göttingen, Germany ~50 employees  Metabolics  Regenerative Medicine Thane, India ~130 employees  Library synthesis & mgmt.  Development chemistry Hamburg, Germany ~200 employees  Screening  HTS,NMR  in vitro & in vivo biology Manfred Eigen1) Campus
  • 4. PAGE Agenda  About Evotec  About EVOsource  Calculating Properties  Analysis of the data  Final thoughts 3
  • 5. PAGE EVOsource 4 Compound Sourcing  Multiple search terms  Single or combination Category Count  Suppliers 218  Catalogues 539  Unique Compounds 22156696  Parts 92490159
  • 6. PAGE EVOsource 5 Compound selection  Can order from stores  Can see if ordered  Can order from supplier  Can request a quote  Can see if available in another lab (or site)  Additional information displayed  JChem Cartridge accessed through Java Persistence API  Marvin Applet  Structure to Name  Standardizer
  • 7. PAGE The challenges of loading supplier catalogues Integrated Cyclic Process Process Contact Receive Prepare Load  Receive catalogues – New catalogues – Catalogue updates  Prepare catalogues – Convert to SD file – Structure Checker – Structure to Name – Name to Structure  Contact Suppliers – Existing suppliers – Preferred suppliers – New suppliers  Process – Fix errors – Expire old data  Load catalogue data – Multiple parallel processes 6
  • 8. PAGE Agenda  About Evotec  About EVOsource  Calculating Properties  Analysis of the data  Final Thoughts 7
  • 9. PAGE Drug likeness categories Classification of compounds Feature count is defined as: # of 5- and 6-membered aromatic rings + # of Lipinski acceptors + # of Lipinski donors Drug like No SS fails Lipinski fails ≤ 1 Additional property constraints: MOE LogP ≤ 6 MW ≤ 600 Rot bonds ≤ 10 EVO LogS ≥ -7 TPSA ≤ 180 Amber No red SS fails Lipinski fails ≤ 1 or No SS fails Lipinski fails ≤ 2 Red Everything else! Lead like No SS fails No Lipinski fails Additional property constraints: MOE LogP ≤ 3.5 MW ≤ 350 Rot bonds ≤ 6 EVO LogS ≥ -5 TPSA ≤ 140 Fragments No SS fails No FSS fails Lip. donors 1-3 Lip. acc. 0-4 MOE LogP ≤ 3.0 MW 150-350 Rot bonds ≤ 5 EVO LogS ≥ -3 TPSA ≤ 70 Feature count 4-7 8
  • 10. PAGE Property calculations Historical process Historical process Export all structures calculate properties using MOE Structural alerts using MOE Stored in a MOE database Problems Only available to Comp Chem Group Difficult to update and time consuming Different values using different tools – chemists use ChemAxon tools to calculate properties 9
  • 11. PAGE Property calculations New process stage 1  Calculate simple properties  Use ChemAxon JChem cartridge calculations where available  Weekly job that calculates properties for new structures  LogS uses MOE to calculate  LogS manually updated every 2 months 10
  • 12. PAGE Calculated Results Breakdown of chemical space by simple descriptors MW HBD HBA logP RotB 11
  • 13. PAGE MOE SMARTS converted to ChemAxon format Structural alerts using two types of filter  121 SMARTS Structural Alerts – general screening compounds  19 SMARTS Fragment filters – fragment screening Assign compounds to category – fragment, lead like etc. Problems  Took 6 months to calculate substructure search as had to be broken into small chunks  MOE SMARTS not automatically converted to ChemAxon format Property calculations New process stage 2 12
  • 14. PAGE Quantitative Estimate of Drug-likeness (QED) New process stage 3 Quantifying the chemical beauty of drugs, A. L. Hopkins et al, Nature Chemistry 2012, 4, 90–9813  QED calculation is based on similar parameters used to assign compounds to the Evotec categories, each parameter is weighted from a model fitting  A proof of concept was carried out on a subset of our screening collection  Literature weights were modified with a bias in favour of structural alerts  LogD was substituted for ALogP to consider ionisation  QED calculation runs as a weekly job Weighted QED Relativefrequency 0.49 0.67
  • 15. PAGE What is a beautiful molecule? Evotec weighted QED 14 QED = medium QED = high QED = low
  • 16. PAGE Agenda  About Evotec  About EVOsource  Calculating Properties  Analysis of the data  Final Thoughts 15
  • 17. PAGE EVOsource composition 16 EVOsource composition for Evotec drug-likeness classes Weighted QED Relativefrequency 15.3% 2.9M 26.9% 5.3M 57.8% 11.1M 0.49 0.67 EVOsource composition for QED index Lead-like 3.1M Fragment-like 1M Red 2.1M Amber 4.2M Drug-like 8.1M
  • 18. PAGE Excellent agreement of QED and Evotec flags to discriminate between different drug-like classes 17 0.670.49 Relativefrequency Weighted QED QED index profile of each Evotec drug-likeness class
  • 19. PAGE EVOsource QED distribution shows large overlap with orally available drugs 18 0.670.49 Weighted QED Relativefrequency Orally available (682 analyzed out of 770) EVOsource Orally available drugs EVOSource
  • 20. PAGE Agenda  About Evotec  About EVOsource  Calculating Properties  Analysis of the data  Final Thoughts 19
  • 21. PAGE Final thoughts and Acknowledgements  EVOsource provides:  A useful tool for our chemists in ordering compounds for our clients  A tool for our Computational Chemists to do analyses of chemical space to better support our clients in library design  QED calculation is providing a useful tool for filtering data to quickly make virtual libraries  QED has been added to latest version of ChEMBL 20 Thanks to: Dr Oliver Barker Dr Mirco Meniconi Catherine Reisser Dr Dan Warner
  • 22. Your contact: Building innovative drug discovery alliances Ian Berry Bob Marmon Manager, Informatics Senior Applications Developer +44.(0).1235.441451 Office +44.(0).1235.441402 Office +44.(0) 7802.438044 Mobile +44.(0).1235.861561 Switchboard +44.(0).1235.441503 Fax +44.(0).1235.441503 Fax ian.berry@evotec.com bob.marmon@evotec.com