The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Automated De Novo Drug Design: Are We Nearly There Yet?
Abstract
Medicinal chemistry and, in particular, drug design have often been perceived as more of an art than a science. The many unknowns of human disease and the sheer complexity of chemical space render decision making in medicinal chemistry exceptionally demanding. Computational models can assist the medicinal chemist in this endeavour. Provided here is an overview of recent examples of automated de novo molecular design, a discussion of the concepts and computational approaches involved, and the daring prediction of some of the possibilities and limitations of drug design using machine intelligence.
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Citations
Cites
How to improve R&D productivity: the pharmaceutical industry's grand challenge
Paul, S. M., Mytelka, D. S., Dunwiddie, C. T., Persinger, C. C., Munos, B. H., Lindborg, S. R., & Schacht, A. L. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3078 · Cited by 3,566
Planning chemical syntheses with deep neural networks and symbolic AI
Segler, M. H. S., Preuss, M., & Waller, M. P. (2018) · Nature · doi:10.1038/nature25978 · Cited by 1,847
Schneider, G. (2018) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2017.232 · Cited by 910
Self-citationComputer‐Assisted Synthetic Planning: The End of the Beginning
Szymkuć, S., Gajewska, E. P., Klucznik, T., Molga, K., Dittwald, P., Startek, M., Bajczyk, M., & Grzybowski, B. A. (2016) · Angewandte Chemie International Edition · doi:10.1002/anie.201506101 · Cited by 611
How artificial intelligence is changing drug discovery
Fleming, N. (2018) · Nature · doi:10.1038/d41586-018-05267-x · Cited by 546
Drug discovery in pharmaceutical industry: productivity challenges and trends
Khanna, I. (2012) · Drug Discovery Today · doi:10.1016/j.drudis.2012.05.007 · Cited by 479
De Novo Design of Bioactive Small Molecules by Artificial Intelligence
Merk, D., Friedrich, L., Grisoni, F., & Schneider, G. (2018) · Molecular Informatics · doi:10.1002/minf.201700153 · Cited by 373
Self-citationEntangled Conditional Adversarial Autoencoder for de Novo Drug Discovery
Polykovskiy, D., Zhebrak, A., Vetrov, D., Ivanenkov, Y., Aladinskiy, V., Mamoshina, P., Bozdaganyan, M., Aliper, A., Zhavoronkov, A., & Kadurin, A. (2018) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.8b00839 · Cited by 278
DOGS: Reaction-Driven de novo Design of Bioactive Compounds
Hartenfeller, M., Zettl, H., Walter, M., Rupp, M., Reisen, F., Proschak, E., Weggen, S., Stark, H., & Schneider, G. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002380 · Cited by 251
Self-citation
Cited by
Artificial intelligence in drug discovery and development
Paul, D., Sanap, G., Shenoy, S., Kalyane, D., Kalia, K., & Tekade, R. K. (2021) · Drug Discovery Today · doi:10.1016/j.drudis.2020.10.010 · Cited by 1,695
Rethinking drug design in the artificial intelligence era
Schneider, P., Walters, W. P., Plowright, A. T., Sieroka, N., Listgarten, J., Goodnow, R. A., Fisher, J., Jansen, J. M., Duca, J. S., Rush, T. S., et al. (2020) · Nature Reviews Drug Discovery · doi:10.1038/s41573-019-0050-3 · Cited by 894
Self-citationA Review on Applications of Computational Methods in Drug Screening and Design
Lin, X., Li, X., & Lin, X. (2020) · Molecules · doi:10.3390/molecules25061375 · Cited by 718
Bender, A., & Cortés-Ciriano, I. (2021) · Drug Discovery Today · doi:10.1016/j.drudis.2020.12.009 · Cited by 405
Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development
Sarkar, C., Das, B., Rawat, V. S., Wahlang, J. B., Nongpiur, A., Tiewsoh, I., Lyngdoh, N. M., Das, D., Bidarolli, M., & Sony, H. T. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24032026 · Cited by 347
Metadata
- Authors
- Schneider, G., & Clark, D. E.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2019-05-17
- Volume
- 58
- Issue
- 32
- Pages
- 10792-10803
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2912328818
- Cited by
- 164
- References
- 9
- FWCI
- 13.75
- Type
- journal article
- Language
- en
- Open access
- closed
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