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Challenges and Recommendations for Obtaining Chemical
  Structures of Industry-Provided Repurposing Candidates




Christopher Southan 1, Antony J. Williams2 and Sean Ekins3,4


                      1   TW2Informatics, Göteborg, Sweden
                    2 Royal Society of Chemistry, Wake Forest, NC.
                  3 Collaborations in Chemistry, Fuquay Varina, NC.
 4Collaborative Drug Discovery, 1633 Bayshore Highway, Suite 342, Burlingame, CA

                                      94010, USA.
Why old drugs ? Why repurposing?
                                            More cost effective R&D?
                                            Repurposing/ repositioning -
                                             Quicker to bring to market?


                                            Recent focus on neglected &
                                             rare diseases
                                            Over 7000 diseases affecting
                                             less than 200,000
                                            1000’s of diseases with no
                                             treatments
                                            >300 orphan drugs approved
                                             since 1983




Ekins S, Williams AJ, Krasowski MD and Freundlich JS, Drug Disc Today, 16: 298-310, 2011
From data hoarding           Pharma company data
   to open data             hoarding - to open data


              (IMDB)




              Me




              Linked Open
              data cloud
              2011
              (Wikipedia)
“Off the Shelf R&D”
              Rare diseases need cures




       All pharmas have assets on shelf that
       reached clinic

       Find new uses for these molecules

       Get to the patient faster
Finding Promiscuous Old Drugs for New Uses


                                                everolimus

                                                          5-fluorouracil




                                                     ceftriaxone




Could In silico / in vitro repositioning find leads-drugs quicker?
Approximate small-molecule drug and
        proto-drug numbers
 Historical development entry         ~35,000

 Approached regulatory entry (INNs)   ~7,000

 Between clinical phases              ~15,000

 In active trials                     ~1,500

 FDA approved                         ~1,400

 INNs issued per year                 ~150

 Discontinued (post approval)         ~50

 New approvals per year               ~15
MRC/AstraZeneca: Mechanisms of
          Disease Call assets


                                                        Launched
                                                        Dec 2011




http://goo.gl/R8trN
http://www.mrc.ac.uk/Fundingopportunities/Calls/MoD/M
RC008389
22 molecules
from
AstraZeneca
NCATS

                                                 May 2012 the National
                                                 Institutes of Health
                                                 (NIH) National
                                                 Center for Advancing
                                                 Translational Sciences
                                                 (NCATS) launched
                                                 the ‘Discovering New
                                                 Therapeutic Uses for
                                                 Existing Molecules’
                                                 program.




 http://goo.gl/FWchw
http://www.ncats.nih.gov/research/reengineering/rescue-
repurpose/therapeutic-uses/directory.html
Library of Industry Provided Reagents

                            Consists of 58 ‘parked’
                            therapeutic agents

                            contributed by eight
                            drug companies,

                            To be evaluated by
                            academics as a
                            repurposing pilot
                            effort funded by
                            NCATS




No structures provided on website!
It started with a blog!




http://goo.gl/uTswV   Southan et al., DDT, 18: 58-70 (2013)
Pooling resources




http://goo.gl/FW6Bl
                        http://goo.gl/NXPVs
Searching for one member of the NCATS list

JNJ-39393406, using a standard Google search,
provides >1000 hits (some are highlighted here)
Patterns of information disclosures




                    Southan et al., DDT, 18: 58-70 (2013)
Different forms of compounds
provided by the analyses of Southan and Lipinski
(protonation state and tautomerization).

Found by AJW - manual review of the ChemFOlder
file




                                   http://goo.gl/yIcVy




                            Southan et al., DDT, 18: 58-70 (2013)
Single stereocenter inversion difference

detected during the analyses of Southan and
Lipinski for GSK1004723.




                          Southan et al., DDT, 18: 58-70 (2013)
Repurposing by similarity to known drugs




                     Southan et al., DDT, 18: 58-70 (2013)
Repurposing by similarity to known drugs




                      Southan et al., DDT, 18: 58-70 (2013)
Cutting to the
   chase
   Several months led to
   structures


   12 of 22 MRC cpds

   41 of 56 NCATS cpds

   Also ran predictions with
   TB and malaria Bayesian
   models (data on
   request)




Southan et al., DDT, 18: 58-70 (2013)
Making molecules public




Drew molecules in
MMDS app

Tweeted them with
#drugrepurposing
#oddt

Visible and
downloadable in
Open Drug
Discovery Teams
Mobile app (free)

Mol Informatics, 31: 585-597, 2012
Adding links to most similar targets in
          CHEMBL using CDD
                            Data currently in a
                            private vault

                            Potential target
                            inference by ligand
                            similarity

                            Will make public

                            Validation
Challenges
Despite the comprehensive interrogation of data sources, some
representations remain equivocal

Organizations allocating the company codes have the primary
provenance for the fidelity of the relationship between database
electronic structure representations and their own results in vitro, in
vivo and in the clinic.


Avoid duplication of effort by others

Companies interested in verifying or correcting our assignments,
or even surfacing de novo their hitherto blinded mappings, are
welcome to contact us.
Recommendations
Authors to ensure their drafted PubMed abstract encapsulates the
code name-to-structure mapping by having the code name and
IUPAC juxtaposed in the abstract text (in the title is even better)

Inclusion in the abstract of the Human Genome Organization
(HUGO) Gene Nomenclature Committee (HGNC) gene symbol for
the primary target (or other major protein database identifier for
non-human targets)

Before resource-intensive experimental testing it would therefore
be valuable to run a battery of in silico methods to predict,
prospectively, potential new targets and new uses and reduce off-
target or safety risks

Provide repurposing opportunities that were not envisaged in the
initial proposal calls.
Acknowledgments
 Chris Lipinski
 Dr Jeremy Yang and colleagues (University of New Mexico) for
  kindly providing access to the Smartsfilter web
 application
 Alex Clark (MMI)
 Steve Carney & Reviewers at DDT
 Mike Travers
 Barry Bunin

 Disclaimer
 We accept no responsibility for
 the correctness of the structures
You can find me @...                                      CDD Booth 205
PAPER ID: 13433
PAPER TITLE: “Dispensing processes profoundly impact biological assays and computational and statistical
analyses”
April 8th 8.35am Room 349

PAPER ID: 14750
PAPER TITLE: “Enhancing High Throughput Screening For Mycobacterium tuberculosis Drug Discovery
Using Bayesian Models”
April 9th 1.30pm Room 353
PAPER ID: 21524

PAPER TITLE: “Navigating between patents, papers, abstracts and databases using public sources and
tools”
April 9th 3.50pm Room 350
PAPER ID: 13358

PAPER TITLE: “TB Mobile: Appifying Data on Anti-tuberculosis Molecule Targets”
April 10th 8.30am Room 357

PAPER ID: 13382
PAPER TITLE: “Challenges and recommendations for obtaining chemical structures of industry-provided
repurposing candidates”
April 10th 10.20am Room 350

PAPER ID: 13438
PAPER TITLE: “Dual-event machine learning models to accelerate drug discovery”
April 10th 3.05 pm Room 350

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Challenges and recommendations for obtaining chemical structures of industry

  • 1. Challenges and Recommendations for Obtaining Chemical Structures of Industry-Provided Repurposing Candidates Christopher Southan 1, Antony J. Williams2 and Sean Ekins3,4 1 TW2Informatics, Göteborg, Sweden 2 Royal Society of Chemistry, Wake Forest, NC. 3 Collaborations in Chemistry, Fuquay Varina, NC. 4Collaborative Drug Discovery, 1633 Bayshore Highway, Suite 342, Burlingame, CA 94010, USA.
  • 2. Why old drugs ? Why repurposing?  More cost effective R&D?  Repurposing/ repositioning - Quicker to bring to market?  Recent focus on neglected & rare diseases  Over 7000 diseases affecting less than 200,000  1000’s of diseases with no treatments  >300 orphan drugs approved since 1983 Ekins S, Williams AJ, Krasowski MD and Freundlich JS, Drug Disc Today, 16: 298-310, 2011
  • 3. From data hoarding Pharma company data to open data hoarding - to open data (IMDB) Me Linked Open data cloud 2011 (Wikipedia)
  • 4. “Off the Shelf R&D” Rare diseases need cures All pharmas have assets on shelf that reached clinic Find new uses for these molecules Get to the patient faster
  • 5. Finding Promiscuous Old Drugs for New Uses everolimus 5-fluorouracil ceftriaxone Could In silico / in vitro repositioning find leads-drugs quicker?
  • 6. Approximate small-molecule drug and proto-drug numbers Historical development entry ~35,000 Approached regulatory entry (INNs) ~7,000 Between clinical phases ~15,000 In active trials ~1,500 FDA approved ~1,400 INNs issued per year ~150 Discontinued (post approval) ~50 New approvals per year ~15
  • 7. MRC/AstraZeneca: Mechanisms of Disease Call assets Launched Dec 2011 http://goo.gl/R8trN http://www.mrc.ac.uk/Fundingopportunities/Calls/MoD/M RC008389
  • 9. NCATS May 2012 the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS) launched the ‘Discovering New Therapeutic Uses for Existing Molecules’ program. http://goo.gl/FWchw http://www.ncats.nih.gov/research/reengineering/rescue- repurpose/therapeutic-uses/directory.html
  • 10. Library of Industry Provided Reagents Consists of 58 ‘parked’ therapeutic agents contributed by eight drug companies, To be evaluated by academics as a repurposing pilot effort funded by NCATS No structures provided on website!
  • 11. It started with a blog! http://goo.gl/uTswV Southan et al., DDT, 18: 58-70 (2013)
  • 13. Searching for one member of the NCATS list JNJ-39393406, using a standard Google search, provides >1000 hits (some are highlighted here)
  • 14. Patterns of information disclosures Southan et al., DDT, 18: 58-70 (2013)
  • 15. Different forms of compounds provided by the analyses of Southan and Lipinski (protonation state and tautomerization). Found by AJW - manual review of the ChemFOlder file http://goo.gl/yIcVy Southan et al., DDT, 18: 58-70 (2013)
  • 16. Single stereocenter inversion difference detected during the analyses of Southan and Lipinski for GSK1004723. Southan et al., DDT, 18: 58-70 (2013)
  • 17. Repurposing by similarity to known drugs Southan et al., DDT, 18: 58-70 (2013)
  • 18. Repurposing by similarity to known drugs Southan et al., DDT, 18: 58-70 (2013)
  • 19. Cutting to the chase Several months led to structures 12 of 22 MRC cpds 41 of 56 NCATS cpds Also ran predictions with TB and malaria Bayesian models (data on request) Southan et al., DDT, 18: 58-70 (2013)
  • 20. Making molecules public Drew molecules in MMDS app Tweeted them with #drugrepurposing #oddt Visible and downloadable in Open Drug Discovery Teams Mobile app (free) Mol Informatics, 31: 585-597, 2012
  • 21. Adding links to most similar targets in CHEMBL using CDD Data currently in a private vault Potential target inference by ligand similarity Will make public Validation
  • 22. Challenges Despite the comprehensive interrogation of data sources, some representations remain equivocal Organizations allocating the company codes have the primary provenance for the fidelity of the relationship between database electronic structure representations and their own results in vitro, in vivo and in the clinic. Avoid duplication of effort by others Companies interested in verifying or correcting our assignments, or even surfacing de novo their hitherto blinded mappings, are welcome to contact us.
  • 23. Recommendations Authors to ensure their drafted PubMed abstract encapsulates the code name-to-structure mapping by having the code name and IUPAC juxtaposed in the abstract text (in the title is even better) Inclusion in the abstract of the Human Genome Organization (HUGO) Gene Nomenclature Committee (HGNC) gene symbol for the primary target (or other major protein database identifier for non-human targets) Before resource-intensive experimental testing it would therefore be valuable to run a battery of in silico methods to predict, prospectively, potential new targets and new uses and reduce off- target or safety risks Provide repurposing opportunities that were not envisaged in the initial proposal calls.
  • 24. Acknowledgments  Chris Lipinski  Dr Jeremy Yang and colleagues (University of New Mexico) for kindly providing access to the Smartsfilter web  application  Alex Clark (MMI)  Steve Carney & Reviewers at DDT  Mike Travers  Barry Bunin Disclaimer We accept no responsibility for the correctness of the structures
  • 25. You can find me @... CDD Booth 205 PAPER ID: 13433 PAPER TITLE: “Dispensing processes profoundly impact biological assays and computational and statistical analyses” April 8th 8.35am Room 349 PAPER ID: 14750 PAPER TITLE: “Enhancing High Throughput Screening For Mycobacterium tuberculosis Drug Discovery Using Bayesian Models” April 9th 1.30pm Room 353 PAPER ID: 21524 PAPER TITLE: “Navigating between patents, papers, abstracts and databases using public sources and tools” April 9th 3.50pm Room 350 PAPER ID: 13358 PAPER TITLE: “TB Mobile: Appifying Data on Anti-tuberculosis Molecule Targets” April 10th 8.30am Room 357 PAPER ID: 13382 PAPER TITLE: “Challenges and recommendations for obtaining chemical structures of industry-provided repurposing candidates” April 10th 10.20am Room 350 PAPER ID: 13438 PAPER TITLE: “Dual-event machine learning models to accelerate drug discovery” April 10th 3.05 pm Room 350