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ProteinGym mutation effects
Predict the fitness effects of mutations across 217 deep mutational scans (placeholder)
| 1 | # ProteinGym mutation effects |
| 2 | |
| 3 | > **Placeholder.** This benchmark is here so the benchmark panel can be tried out. Its baseline is from the blueprint or the literature as of 2026-10-19 and must be checked again; every route and score after it is made up. |
| 4 | |
| 5 | ## Task |
| 6 | |
| 7 | Predict how mutations change a protein’s fitness, scored against the 217 deep mutational scanning assays of ProteinGym v1.3: enzyme activity, binding, expression, organismal fitness and stability. The score is the mean Spearman correlation over assays; the baseline is the S2F sequence–structure model at 0.4556, as in AutoSOTA’s report. Routes may use multiple sequence alignments, structures and any public pretrained protein language model. |
| 8 | |
| 9 | ## How to take part |
| 10 | |
| 11 | Start a route from `main` (the baseline) or from any route on the leaderboard, keep your files in the route's folder, and push: the verifier scores every commit. Say what your route changes with tags, and keep the misses: a route that scores worse is a result too. |