MotifRetro: Exploring the Combinability-Consistency Trade-offs in
  retrosynthesis via Dynamic Motif Editing
Zhangyang Gao Xingran Chen Cheng Tan Stan Z. Li
Is there a unified framework for graph-based retrosynthesis prediction?
Through analysis of full-, semi-, and non-template retrosynthesis methods, we
discovered that they strive to strike an optimal balance between combinability
and consistency: \textit{Should atoms be combined as motifs to simplify the
molecular editing process, or should motifs be broken down into atoms to reduce
the vocabulary and improve predictive consistency?}
  Recent works have studied several specific cases, while none of them explores
different combinability-consistency trade-offs. Therefore, we propose
MotifRetro, a dynamic motif editing framework for retrosynthesis prediction
that can explore the entire trade-off space and unify graph-based models.
MotifRetro comprises two components: RetroBPE, which controls the
combinability-consistency trade-off, and a motif editing model, where we
introduce a novel LG-EGAT module to dynamiclly add motifs to the molecule. We
conduct extensive experiments on USPTO-50K to explore how the trade-off affects
the model performance and finally achieve state-of-the-art performance.