“Ring Breaker”: Neural Network Driven Synthesis Prediction of the Ring System Chemical Space

Thakkar, Amol; Selmi, Nidhal; Reymond, Jean-Louis; Engkvist, Ola; Bjerrum, Esben Jannik (2020). “Ring Breaker”: Neural Network Driven Synthesis Prediction of the Ring System Chemical Space. Journal of medicinal chemistry, 63(16), pp. 8791-8808. American Chemical Society 10.1021/acs.jmedchem.9b01919

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Ring systems in pharmaceuticals, agrochemicals, and dyes are ubiquitous chemical motifs. While the synthesis of common ring systems is well described and novel ring systems can be readily and computationally enumerated, the synthetic accessibility of unprecedented ring systems remains a challenge. “Ring Breaker” uses a data-driven approach to enable the prediction of ring-forming reactions, for which we have demonstrated its utility on frequently found and unprecedented ring systems, in agreement with literature syntheses. We demonstrate the performance of the neural network on a range of ring fragments from the ZINC and DrugBank databases and highlight its potential for incorporation into computer aided synthesis planning tools. These approaches to ring formation and retrosynthetic disconnection offer opportunities for chemists to explore and select more efficient syntheses/synthetic routes.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Chemistry, Biochemistry and Pharmaceutical Sciences (DCBP)

UniBE Contributor:

Thakkar, Amol Vijay and Reymond, Jean-Louis

Subjects:

500 Science > 570 Life sciences; biology
500 Science > 540 Chemistry

ISSN:

0022-2623

Publisher:

American Chemical Society

Language:

English

Submitter:

Sandra Tanja Zbinden Di Biase

Date Deposited:

19 Jan 2021 10:31

Last Modified:

19 Jan 2021 10:39

Publisher DOI:

10.1021/acs.jmedchem.9b01919

BORIS DOI:

10.48350/148850

URI:

https://boris.unibe.ch/id/eprint/148850

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