After a difficult start, medicinal chemists are now ready to embrace AI-based methods and concepts in drug discovery, explains Gisbert Schneider.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems
Minds and Machines Open Access 04 January 2023
-
Operationalising AI governance through ethics-based auditing: an industry case study
AI and Ethics Open Access 31 May 2022
-
Artificial intelligence in research and development for sustainability: the centrality of explicability and research data management
AI and Ethics Open Access 02 November 2021
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
References
Lee, V. H. Ther. Deliv. 1, 615–619 (2010).
Scannell, J. W., Blanckley, A., Boldon, H. & Warrington, B. Nat. Rev. Drug Discov. 11, 191–200 (2012).
Smietana, K., Siatkowski, M. & Møller, M. Nat. Rev. Drug Discov. 15, 379–380 (2016).
Mignani, S., Huber, S., Tomás, H., Rodrigues, J. & Majoral, J. P. Drug Discov. Today 21, 239–249 (2016).
Jordan, A. M. ACS Med. Chem. Lett. 9, 1150–1152 (2018).
Segler, M. H. S., Preuss, M. & Waller, M. P. Nature 555, 604–610 (2018).
Schütt, K. T., Arbabzadah, F., Chmiela, S., Müller, K. R. & Tkatchenko, A. Nat. Commun. 8, 13890 (2017).
Gupta, A. et al. Mol. Inf. 37, 1700111 (2018).
Merk, D., Grisoni, F., Friedrich, L. & Schneider, G. Commun. Chem. 1, 68 (2018).
Pierce, T. H. & Hohne, B. A. (eds) Artificial Intelligence Applications in Chemistry (American Chemical Society, Washington, 1986).
Gasteiger, J. & Zupan, J. Angew. Chem. Int. Ed. 32, 503–527 (1993).
Walters, W. P., Green, J., Weiss, J. R. & Murcko, M. J. Med. Chem. 54, 6405–6416 (2011).
Sanderson, K. Nat. Rev. Drug Discov. 14, 299–300 (2015).
Schneider, G. Nat. Rev. Drug Discov. 17, 97–113 (2018).
King, R. D. et al. Science 324, 85–89 (2009).
Schneider, P. & Schneider, G. J. Med. Chem. 59, 4077–4086 (2016).
Leeson, P. D. & Springthorpe, B. Nat. Rev. Drug Discov. 6, 881–890 (2007).
Begoli, E., Bhattacharya, T. & Kusnezov, D. Nat. Mach. Intell. 1, 20–23 (2019).
Seifert, V. A. Found. Chem. 19, 209–222 (2017).
Blakemore, D. C. et al. Nat. Chem. 10, 383–394 (2018).
Merk, D., Friedrich, L., Grisoni, F. & Schneider, G. Mol. Inf. 37, 1700153 (2018).
Coley, C. W., Green, W. H. & Jensen, K. F. Acc. Chem. Res. 51, 1281–1289 (2018).
Smith, J. S., Isayev, O. & Roitberg, A. E. Chem. Sci. 8, 3192–3203 (2017).
Schneider, G. Mol. Inf. 37, 1880131 (2018).
Hessler, G. & Baringhaus, K. H. Molecules 23, 2520 (2018).
Mak, K.-K. & Pichika, M. R. Artificial intelligence in drug development: present status and future prospects. Drug Discov. Today. https://doi.org/10.1016/j.drudis.2018.11.014 (2019).
Devillers, J. (ed.) Neural Networks in QSAR and Drug Design (Academic, Cambridge, 1996).
Lohmann, R., Schneider, G. & Wrede, P. Biopolymers 38, 13–29 (1996).
Schneider, G. & Wrede, P. Prog. Biophys. Mol. Biol. 70, 175–222 (1998).
Plowright, A. T. et al. Drug Discov. Today 17, 56–62 (2012).
Graubard, S. R. (ed.). The Artificial Intelligence Debate: False Starts, Real Foundations (MIT Press, Cambridge, 1988).
Topol, E. J. Nat. Med. 25, 44–56 (2019).
Goldberg, K. Nat. Mach. Intell. 1, 2–4 (2019).
Acknowledgements
I am grateful to the many colleagues, co-workers and students with whom I had the privilege to work on drug design with machine intelligence. This work was financially supported by the Novartis Forschungsstiftung (FreeNovation: AI in Drug Discovery) and the Swiss National Science Foundation (grant no. 205321_182176 to G.S.).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The author declares a potential financial conflict of interest as consultant to the pharmaceutical industry and co-founder of inSili.com GmbH, Zurich.
Rights and permissions
About this article
Cite this article
Schneider, G. Mind and machine in drug design. Nat Mach Intell 1, 128–130 (2019). https://doi.org/10.1038/s42256-019-0030-7
Published:
Issue Date:
DOI: https://doi.org/10.1038/s42256-019-0030-7
This article is cited by
-
Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR
Nature Reviews Drug Discovery (2024)
-
The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems
Minds and Machines (2023)
-
Operationalising AI governance through ethics-based auditing: an industry case study
AI and Ethics (2023)
-
MASSA Algorithm: an automated rational sampling of training and test subsets for QSAR modeling
Journal of Computer-Aided Molecular Design (2023)
-
Development of a proteochemometric-based support vector machine model for predicting bioactive molecules of tubulin receptors
Molecular Diversity (2022)