Table 1.
Performance of our RetroExplainer and the state-of-the-art methods on USPTO-50K benchmarks
| Model | Top-k accuracy (%) | |||||||
|---|---|---|---|---|---|---|---|---|
| Reaction class known | Reaction class unknown | |||||||
| k = 1 | 3 | 5 | 10 | 1 | 3 | 5 | 10 | |
| Fingerprint-based | ||||||||
| RetroSim41 | 52.9 | 73.8 | 81.2 | 88.1 | 37.3 | 54.7 | 63.3 | 74.1 |
| NeuralSym8 | 55.3 | 76.0 | 81.4 | 85.1 | 44.4 | 65.3 | 72.4 | 78.9 |
| Sequence-based | ||||||||
| SCROP59 | 59.0 | 74.8 | 78.1 | 81.1 | 43.7 | 60.0 | 65.2 | 68.7 |
| LV-Transformer23 | - | - | - | - | 40.5 | 65.1 | 72.8 | 79.4 |
| AutoSynRoute60 | - | - | - | - | 43.1 | 64.6 | 71.8 | 78.7 |
| TiedTransformer61 | - | - | - | - | 47.1 | 67.1 | 73.1 | 76.3 |
| MolBART62 | - | - | - | - | 55.6 | - | 74.2 | 80.9 |
| Retroformer63 | 64.0 | 82.5 | 86.7 | 90.2 | 53.2 | 71.7 | 76.6 | 82.1 |
| RetroPrime64 | 64.8 | 81.6 | 85.0 | 86.9 | 51.4 | 70.8 | 74.0 | 76.1 |
| R-SMILES65 | - | - | - | 56.3 | 79.2 | 86.2 | 91.0 | |
| DualTF46 | 65.7 | 81.9 | 84.7 | 85.9 | 53.6 | 70.7 | 74.6 | 77.0 |
| Graph-based | ||||||||
| GLN36 | 64.2 | 79.1 | 85.2 | 90.0 | 52.5 | 69.0 | 75.6 | 83.7 |
| G2Gs17 | 61.0 | 81.3 | 86.0 | 88.7 | 48.9 | 67.6 | 72.5 | 75.5 |
| G2GT18 | - | - | - | - | 54.1 | 69.9 | 74.5 | 77.7 |
| GTA16 | - | - | - | - | 51.1 | 67.6 | 73.8 | 80.1 |
| GraphRetro33 | 63.9 | 81.5 | 85.2 | 88.1 | 53.7 | 68.3 | 72.2 | 75.5 |
| Graph2SMILES39 | - | - | - | - | 52.9 | 66.5 | 70.0 | 72.9 |
| RetroXpert32 | 62.1 | 75.8 | 78.5 | 80.9 | 50.4 | 61.1 | 62.3 | 63.4 |
| GET38 | 57.4 | 71.3 | 74.8 | 77.4 | 44.9 | 58.8 | 62.4 | 65.9 |
| LocalRetro57 | 63.9 | 86.8 | 92.4 | 96.0 | 53.4 | 77.5 | 85.9 | 92.4 |
| RetroExplainer (Ours) | 66.8 | 88.0 | 92.5 | 95.8 | 57.7 | 79.2 | 84.8 | 91.4 |
The performance regarding existing methods is derived from their references. The best-performing results are marked in bold.