Papers › Retrosynthesis Prediction with Conditional Graph Logic Network
Retrosynthesis Prediction with Conditional Graph Logic Network
Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song
Retrosynthesis is one of the fundamental problems in organic chemistry. The task is to identify reactants that can be used to synthesize a specified product molecule. Recently, computer-aided retrosynthesis is finding renewed interest from both chemistry and computer science communities. Most existing approaches rely on template-based models that define subgraph matching rules, but whether or not a chemical reaction can proceed is not defined by hard decision rules. In this work, we propose a new approach to this task using the Conditional Graph Logic Network, a conditional graphical model built upon graph neural networks that learns when rules from reaction templates should be applied, implicitly considering whether the resulting reaction would be both chemically feasible and strategic. We also propose an efficient hierarchical sampling to alleviate the computation cost. While achieving a significant improvement of 8.1% over current state-of-the-art methods on the benchmark dataset, our model also offers interpretations for the prediction.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Single-step retrosynthesis | USPTO-50k | GLN | Top-1 accuracy | 52.5 | #27 of 35 | Archive leaderboard | report |
| Single-step retrosynthesis | USPTO-50k | GLN | Top-10 accuracy | 83.7 | #27 of 35 | Archive leaderboard | report |
| Single-step retrosynthesis | USPTO-50k | GLN | Top-20 accuracy | 89 | #27 of 35 | Archive leaderboard | report |
| Single-step retrosynthesis | USPTO-50k | GLN | Top-3 accuracy | 69 | #27 of 35 | Archive leaderboard | report |
| Single-step retrosynthesis | USPTO-50k | GLN | Top-5 accuracy | 75.6 | #27 of 35 | Archive leaderboard | report |
| Single-step retrosynthesis | USPTO-50k | GLN | Top-50 accuracy | 92.4 | #27 of 35 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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