Retrosynthesis Prediction via Search in (Hyper) Graph
Zixun Lan Binjie Hong Jiajun Zhu Zuo Zeng Zhenfu Liu Limin Yu Fei Ma
Predicting reactants from a specified core product stands as a fundamental
challenge within organic synthesis, termed retrosynthesis prediction. Recently,
semi-template-based methods and graph-edits-based methods have achieved good
performance in terms of both interpretability and accuracy. However, due to
their mechanisms these methods cannot predict complex reactions, e.g.,
reactions with multiple reaction center or attaching the same leaving group to
more than one atom. In this study we propose a semi-template-based method, the
\textbf{Retro}synthesis via \textbf{S}earch \textbf{i}n (Hyper) \textbf{G}raph
(RetroSiG) framework to alleviate these limitations. In the proposed method, we
turn the reaction center identification and the leaving group completion tasks
as tasks of searching in the product molecular graph and leaving group
hypergraph respectively. As a semi-template-based method RetroSiG has several
advantages. First, RetroSiG is able to handle the complex reactions mentioned
above by its novel search mechanism. Second, RetroSiG naturally exploits the
hypergraph to model the implicit dependencies between leaving groups. Third,
RetroSiG makes full use of the prior, i.e., one-hop constraint. It reduces the
search space and enhances overall performance. Comprehensive experiments
demonstrated that RetroSiG achieved competitive results. Furthermore, we
conducted experiments to show the capability of RetroSiG in predicting complex
reactions. Ablation experiments verified the efficacy of specific elements,
such as the one-hop constraint and the leaving group hypergraph.