CACHE (Critical Assessment of Computational Hit-finding Experiments)

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

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.

Vienna University Archive, Department of Pharmaceutical Sciences, Department of Statistics and Operations Research
External organisation(s)
University of Toronto, Structural Genomics Consortium, Ontario Institute for Cancer Research, University of California, Riverside, University of California, San Diego, Aché Laboratórios Farmaceuticos S.A., Université du Québec à Montréal, Merck KGaA, University of New Mexico, Memorial Sloan-Kettering Cancer Center, IBM T. J. Watson Research Center, European Molecular Biology Laboratory Grenoble Outstation, Wellcome Genome Campus, Karolinska Institute, Sanofi-Aventis Deutschland GmbH, Bayer, AstraZeneca, University of California, San Francisco, Novartis Institutes for BioMedical Research, Cambridge, MA, USA., PostEra, University of Cambridge, Boehringer Ingelheim International GmbH, National Institue of Standards and Technology, US Department of Commerce, University of Maryland, Baltimore, University of Maryland, College Park, Alkermes, Drugs for Neglected Diseases Initiative, Relay Therapeutics, Takeda California, Inc., Takeda Pharmaceuticals U.S.A., Inc., University of London, University College Hospital, University College London, Freie Universität Berlin (FU), Humboldt-Universität zu Berlin, Charité - Universitätsmedizin Berlin, University of North Carolina at Charlotte, University of North Carolina at Chapel Hill
Nature reviews chemistry
No. of pages
Publication date
Peer reviewed
Austrian Fields of Science 2012
301207 Pharmaceutical chemistry
ASJC Scopus subject areas
Chemical Engineering(all), Chemistry(all)
Portal url