Published October 18, 2021 | Version v1
Preprint Open

CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding

Creators

  • 1. Structural Genomics Consortium, University of Toronto, Toronto, Ontario, Canada
  • 2. Ontario Institute for Cancer Research, Toronto, Ontario, Canada and Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada
  • 3. Department of Chemistry and Biochemistry, UC San Diego, La Jolla, CA, USA and Drug Design Data Resource, University of California, San Diego, La Jolla, CA, USA
  • 4. Aché Laboratórios Farmacêuticos, Guarulhos, São Paulo, Brazil
  • 5. Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
  • 6. Mila, University of Montreal, Québec, Canada
  • 7. Merck Healthcare KGaA, Darmstadt, Germany
  • 8. Department of Internal Medicine, University of New Mexico School of Medicine, University of New Mexico Albuquerque, Albuquerque, NM, USA
  • 9. Computational and Systems Biology Program Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
  • 10. Healthcare & Life Sciences Research, IBM TJ Watson Research Center, New York, USA
  • 11. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK and Open Targets, Wellcome Genome Campus, Hinxton, UK
  • 12. Department of Pharmaceutical Sciences, University of Vienna, Vienna, Austria
  • 13. Structural Genomics Consortium, Department of Medicine, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden
  • 14. Skaggs School of Pharmacy and Pharmaceutical Sciences, UC San Diego, La Jolla, CA, USA and Drug Design Data Resource, University of California, San Diego, La Jolla, CA, USA
  • 15. Sanofi-Aventis Deutschland GmbH, R&D, Integrated Drug Discovery, Frankfurt am Main, Germany
  • 16. Research and Development, Bayer AG, Pharmaceuticals, Wuppertal, Germany
  • 17. Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
  • 18. Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA
  • 19. Novartis Institutes for BioMedical Research, Emeryville, CA, USA
  • 20. Merck Healthcare KGaA, Computational Chemistry & Biologics, Darmstadt, Germany
  • 21. PostEra Inc., San Franciso, CA, USA and Department of Physics, University of Cambridge, Cambridge, UK
  • 22. Boehringer Ingelheim Pharma GmbH & Co. KG, Medicinal Chemistry, Biberach an der Riss, Germany
  • 23. Institute for Bioscience and Biotechnology Research, Rockville, MD, USA and Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, USA
  • 24. Alkermes, Inc., Waltham, MA, USA
  • 25. Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA and University of New Mexico Comprehensive Cancer Center, Albuquerque, NM, USA
  • 26. Drugs for Neglected Diseases initiative, Geneva, Switzerland
  • 27. Relay Therapeutics, Boston, MA, USA
  • 28. Global Research Externalization, Takeda California, Inc., San Diego, CA, USA
  • 29. Structural Genomics Consortium, University of Toronto, Toronto, Ontario, Canada and Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada
  • 30. Bayer AG, Open Innovation – Public Private Partnerships, Pharmaceuticals, Berlin, Germany
  • 31. School of Pharmacy, University College London, London, UK
  • 32. In Silico Toxicology and Structural Bioinformatics, Institute of Physiology, Charité Universitätsmedizin Berlin, Berlin, Germany
  • 33. Structural Genomics Consortium, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Description

Computational approaches in drug discovery and development hold great promise, with artificial intelligence methods undergoing widespread contemporary use, but the experimental validation of these new approaches is frequently inadequate. We are initiating Critical Assessment of Computational Hit-finding Experiments (CACHE) as a public benchmarking project that aims to accelerate the development of small molecule hit-finding algorithms by competitive assessment. Compounds will be identified by participants using a wide range of computational methods for dozens of protein targets selected for different types of prediction scenarios, as well as for their potential biological or pharmaceutical relevance. Community-generated predictions will be tested centrally and rigorously in an experimental hub(s), and all data, including the chemical structures of experimentally tested compounds, will be made publicly available without restrictions. The ability of a range of computational approaches to find novel compounds will be evaluated, compared, and published. The overarching goal of CACHE is to accelerate the development of computational chemistry methods by providing rapid and unbiased feedback to those developing methods, with an ancillary and valuable benefit of identifying new compound-protein binding pairs for biologically interesting targets. The initiative builds on the power of crowd sourcing and expands the open science paradigm for drug discovery.

Notes

ACKNOWLEDGEMENTS The Structural Genomics Consortium is a registered charity (no: 1097737) that receives funds from Bayer AG, Boehringer Ingelheim, Bristol Myers Squibb, Genentech, Genome Canada through Ontario Genomics Institute [OGI-196], Janssen, Merck KGaA (aka EMD in Canada and US), Pfizer, Takeda and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 875510. The JU receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA and Ontario Institute for Cancer Research, Royal Institution for the Advancement of Learning McGill University, Kungliga Tekniska Hoegskolan, Diamond Light Source Limited. This communication reflects the views of the authors and the JU is not liable for any use that may be made of the information contained herein. M. K. Gilson acknowledges funding from National Institute of General Medical Sciences (GM061300). J. J. Irwin acknowledges funding from National Institute of General Medical Sciences (GM133836). These findings are solely of the authors and do not necessarily represent the views of the NIH. The Lee laboratory at the University of Cambridge receives funding from multiple sources, including Pfizer, AstraZeneca, the Engineering and Physical Sciences Research Council and the Winton Programme for the Physics of Sustainability. T.I. Oprea and C. G. Bologa acknowledge funding from the National Institutes of Health Common Fund program, Illuminating the Druggable Genome (CA224370 and TR002278). COMPETING INTERESTS M. K. Gilson has an equity interest in and is a cofounder and scientific advisor of VeraChem LLC. J. J. Irwin is a co-founder of Blue Dolphin LLC, which undertakes fee-for-service ligand discovery. A.A. Lee is the chief scientific officer and a shareholder of PostEra Inc. T. I. Oprea has received honoraria from or consulted for Abbott, AstraZeneca, Chiron, Genentech, Infinity Pharmaceuticals, Merz Pharmaceuticals, Merck Darmstadt, Mitsubishi Tanabe, Novartis, Ono Pharmaceuticals, Pfizer, Roche, Sanofi and Wyeth, and is on the Scientific Advisory Board of ChemDiv and InSilico Medicine.

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Additional details

Funding

EUbOPEN – EUbOPEN: Enabling and Unlocking biology in the OPEN 875510
European Commission