Lead Optimization in Protein Folding on CAMEO 183 targets 2022
10.5RMSD (Base)Baseline One-shot (150M)
Evaluation results
| Method | Links | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Baseline One-shot (150M)Backbone=DPLM-2, Parameters=150M2025.09 | 10.5 | — | — | 0.537 | — | — | 0.302 | — | — | |
| Random (MCTS-0)Configuration=MCTS-02025.09 | 10.5 | 10.53 | 0.14 | 0.537 | 0.813 | 0.281 | 0.302 | 0.403 | 0.107 | |
| Single-Expert (150M)Parameters=150M2025.09 | 10.5 | 10 | 0.5 | 0.537 | 0.809 | 0.272 | 0.302 | 0.426 | 0.124 | |
| Single-Expert (650M)Parameters=650M2025.09 | 10.5 | 9.24 | 1.29 | 0.537 | 0.811 | 0.273 | 0.302 | 0.45 | 0.147 | |
| Single-Expert (3B)Parameters=3B2025.09 | 10.5 | 9.73 | 0.79 | 0.537 | 0.81 | 0.271 | 0.302 | 0.434 | 0.132 | |
| SamplingMode=Sampling2025.09 | 10.5 | 9.97 | 0.52 | 0.537 | 0.804 | 0.264 | 0.302 | 0.422 | 0.118 | |
| MCTD-UCTConfiguration=UCT-variant2025.09 | 10.5 | 9.47 | 1.28 | 0.537 | 0.827 | 0.296 | 0.302 | 0.454 | 0.16 | |
| MCTD-MEConfiguration=Multi-Expert2025.09 | 10.5 | 9.41 | 1.32 | 0.537 | 0.827 | 0.296 | 0.302 | 0.456 | 0.16 |