CACHE (Critical Assessment of Computational Hit-finding Experiments)
- Author(s)
- Suzanne Ackloo, Rima Al-awar, Rommie E. Amaro, Cheryl H. Arrowsmith, Hatylas Azevedo, Robert A. Batey, Yoshua Bengio, Ulrich A. K. Betz, Cristian G. Bologa, John D. Chodera, Wendy D. Cornell, Ian Dunham, Gerhard F. Ecker, Kristina Edfeldt, Aled M. Edwards, Michael K. Gilson, Claudia R. Gordijo, Gerhard Hessler, Alexander Hillisch, Anders Hogner, John J. Irwin, Johanna M. Jansen, Daniel Kuhn, Andrew R. Leach, Alpha A. Lee, Uta Lessel, Maxwell R. Morgan, John Moult, Ingo Muegge, Tudor Oprea, Benjamin G. Perry, Patrick Riley, Sophie A. L. Rousseaux, Kumar Singh Saikatendu, Vijayaratnam Santhakumar, Matthieu Schapira, Cora Scholten, Matthew H. Todd, Masoud Vedadi, Andrea Volkamer, Timothy M. Willson
- Abstract
One aspirational goal of computational chemistry is to predict potent and drug-like binders for any protein, such that only those that bind are synthesized. In this Roadmap, we describe the launch of Critical Assessment of Computational Hit-finding Experiments (CACHE), a public benchmarking project to compare and improve small-molecule hit-finding algorithms through cycles of prediction and experimental testing. Participants will predict small-molecule binders for new and biologically relevant protein targets representing different prediction scenarios. Predicted compounds will be tested rigorously in an experimental hub, and all predicted binders as well as all experimental screening data, including the chemical structures of experimentally tested compounds, will be made publicly available and not subject to any intellectual property restrictions. The ability of a range of computational approaches to find novel binders will be evaluated, compared and openly published. CACHE will launch three new benchmarking exercises every year. The outcomes will be better prediction methods, new small-molecule binders for target proteins of importance for fundamental biology or drug discovery and a major technological step towards achieving the goal of Target 2035, a global initiative to identify pharmacological probes for all human proteins.
Critical Assessment of Computational Hit-finding Experiments (CACHE) is a public benchmarking project to compare and improve computational small-molecule hit-finding approaches through cycles of prediction, compound synthesis and experimental testing. By that, CACHE will enable a more efficient and effective approach to hit identification and drug discovery.- Organisation(s)
- Department of Pharmaceutical Sciences
- External organisation(s)
- University of Toronto, Ontario Institute for Cancer Research, University of California, San Diego, Aché Laboratórios Farmaceuticos S.A., Merck KGaA, University of New Mexico, Sloan-Kettering Institute, Department of Developmental Biology, 1275 York Avenue, Box 252, New York, NY 10065, USA., IBM T. J. Watson Research Center, Wellcome Genome Campus, Karolinska Institute, Sanofi-Aventis Deutschland GmbH, Bayer AG, AstraZeneca, University of California, San Francisco, Novartis Institutes for BioMedical Research, PostEra, University of Cambridge, Boehringer Ingelheim International GmbH, University of Maryland, College Park, Alkermes, Drugs for Neglected Diseases Initiative, Relay Therapeutics, Takeda California, Inc., University College London, Charité – Universitätsmedizin Berlin, University of North Carolina at Chapel Hill, University of Montreal
- Journal
- Nature reviews chemistry
- Volume
- 6
- Pages
- 287-295
- No. of pages
- 9
- ISSN
- 2397-3358
- DOI
- https://doi.org/10.1038/s41570-022-00363-z
- Publication date
- 04-2022
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 301207 Pharmaceutical chemistry
- Keywords
- ASJC Scopus subject areas
- Chemical Engineering(all), Chemistry(all)
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/cache-critical-assessment-of-computational-hitfinding-experiments(ac5b1c9f-eb5c-4969-9ba6-1661df1fa9bb).html