Theoretical and Computational Chemistry

‘Ring Breaker’: Neural Network Driven Synthesis Prediction of the Ring System Chemical Space


Ring systems in pharmaceuticals, agrochemicals and dyes are ubiquitous chemical motifs. Whilst the synthesis of common ring systems is well described, and novel ring systems can be readily 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.

Version notes

Version (3) - Revisions, Manuscript under review


Thumbnail image of Ringbreaker_Manuscript_Revision_Thakkar_v2.pdf

Supplementary material

Thumbnail image of Ringbreaker_Manuscript_Revision_Thakkar_Supplementary_v2.pdf
Ringbreaker Manuscript Revision Thakkar Supplementary v2
Thumbnail image of
SI common ringformations
Thumbnail image of TOC.tiff