Synthetic organic chemistry underpins several areas of chemistry, including drug discovery, chemical biology, materials science and engineering. However, the execution of complex chemical syntheses in itself requires expert knowledge, usually acquired over many years of study and hands-on laboratory practice. The development of technologies with potential to streamline and automate chemical synthesis is a half-century-old endeavour yet to be fulfilled. Renewed interest in artificial intelligence (AI), driven by improved computing power, data availability and algorithms, is overturning the limited success previously obtained. In this Review, we discuss the recent impact of AI on different tasks of synthetic chemistry and dissect selected examples from the literature. By examining the underlying concepts, we aim to demystify AI for bench chemists in order that they may embrace it as a tool rather than fear it as a competitor, spur future research by pinpointing the gaps in knowledge and delineate how chemical AI will run in the era of digital chemistry.
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A.F.A. acknowledges Fundação para a Ciência e Tecnologia (FCT) Portugal for financial support through a PhD grant (PD/BD/143125/2019). T.R. is an investigador auxiliar supported by FCT Portugal (CEECIND/00887/2017). T.R. acknowledges FCT/FEDER (02/SAICT/2017, grant 28333) for funding. The authors thank the reviewers for their comments.
The authors declare no competing interests.
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Area of computer science that deals with the recognition, processing and analysis of human (natural) language.
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(LDA). A machine-learning method that finds linear combinations of features that separate classes, prior to dimensionality reduction and classification.
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(SVM). A machine-learning method that separates data points in hyperspace through mathematical functions called kernels.
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de Almeida, A.F., Moreira, R. & Rodrigues, T. Synthetic organic chemistry driven by artificial intelligence. Nat Rev Chem 3, 589–604 (2019). https://doi.org/10.1038/s41570-019-0124-0
Nature Reviews Chemistry (2021)
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Journal of Computer-Aided Molecular Design (2020)