| --- |
| license: other |
| license_name: mixed-see-below |
| license_link: https://github.com/DeepBio-Scientific/MIRAGE#provenance--licensing |
| task_categories: |
| - tabular-regression |
| tags: |
| - binding-affinity |
| - drug-discovery |
| - protein-ligand |
| - benchmark |
| - data-leakage |
| pretty_name: MIRAGE |
| configs: |
| - config_name: redundancy |
| data_files: redundancy/test-*.parquet |
| default: true |
| - config_name: temporal |
| data_files: temporal/test-*.parquet |
| --- |
| |
| # MIRAGE: Measuring Interpolation and Redundancy in Affinity GEneralization |
|
|
| A benchmark for measuring whether a protein–ligand **binding-affinity** model generalises |
| beyond protein families that are heavily represented in the PDB, or whether its reported |
| accuracy is carried by that redundancy. |
|
|
| Frontier co-folding affinity models (Boltz-2, Nesso-1, …) report Pearson ≈ 0.6 on standard |
| benchmarks. When the same models are stratified by protein-family size, that accuracy is |
| concentrated on well-represented families and **collapses to ≈ 0 on singleton families** — |
| exactly the case that matters when starting a program against a novel target. |
|
|
| ## Configs |
|
|
| ### `redundancy` (18,759 rows, default) |
| PDBbind-derived protein–ligand complexes with experimental affinity, annotated with |
| protein-family size so accuracy can be stratified by redundancy. |
|
|
| | column | description | |
| |---|---| |
| | `id` | PDB code | |
| | `sequence` | protein chain (single-letter) | |
| | `smiles` | ligand SMILES (from the deposited structure) | |
| | `pK` | experimental −log10(Kd/Ki/IC50); **higher = stronger** | |
| | `affinity_type` | `Kd` / `Ki` / `IC50` | |
| | `year` | PDB deposition year | |
| | `family_id` | MMseqs2 30%-identity cluster representative | |
| | `family_size` | number of complexes in that family (**the redundancy axis**) | |
| | `redundancy_bin` | `1`, `2-5`, `6-20`, `21-80`, `81-300`, `301+` | |
| | `ligand_nn_tanimoto` | ECFP4 nearest-neighbour similarity to any other ligand | |
| | `in_core` | member of the balanced 3,360-target quick-eval subset | |
|
|
| ### `temporal` (649 rows) |
| One structurally novel, post-2021-09-30 target (**OpenBind EV-A71 2A protease**), with |
| measured KD and shipped baselines. Tests within-target ranking on data that no model with |
| a ≤ 2021 cutoff could have seen. |
|
|
| | column | description | |
| |---|---| |
| | `id` | Fragalysis code | |
| | `sequence` | target protein | |
| | `smiles` | ligand SMILES | |
| | `pKD` | experimental −log10(KD); higher = stronger | |
| | `baseline_molecular_weight`, `baseline_clogp`, `ref_boltz2` | reference predictions | |
|
|
| ## Usage |
|
|
| ```python |
| import mirage |
| |
| def my_model(sequence, smiles): |
| return score # higher = stronger binder |
| |
| print(mirage.run_redundancy(my_model).summary()) |
| print(mirage.run_temporal(my_model).summary()) |
| ``` |
|
|
| See <https://github.com/DeepBio-Scientific/MIRAGE> for the harness, baselines, and CLI. |
|
|
| ## Provenance & licensing |
|
|
| - **Redundancy set** is derived from **PDBbind** (protein sequences from the PDB; SMILES |
| from deposited ligands; affinities from PDBbind's curated literature values). Only derived |
| annotations are redistributed here, under MIT. Users should observe PDBbind's own terms |
| when using the underlying structures. |
| - **Temporal set** is derived from the **OpenBind A71EV2A** release (CC0) and its public |
| benchmark repository. |
|
|
| Family sizes are computed with MMseqs2 at 30% sequence identity / 80% coverage. |
|
|
