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README.md

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+# ProteinBase Interactions
+
+## Overview
+
+Each row represents a single binder-target pair with:
+
+- the ProteinBase binder identifier
+- the binder sequence
+- the target name
+- the target sequence
+- an experimental binding-strength label
+- a binary classification label
+- design-class metadata
+- an `antibody` flag indicating whether the binder is an antibody-derived design (`Nanobody` or `scFv`)
+
+## Schema
+
+The dataset contains the following columns:
+
+- `proteinbase_id`: Original ProteinBase binder ID.
+- `binder_name`: Binder name uploaded by the original protein designers.
+- `target`: Common name of the target protein.
+- `target_sequence`: Amino acid sequence of the target protein.
+- `binder_sequence`: Amino acid sequence of the binder protein.
+- `binding_strength`: Labels designated by Proteinbase. The possible values are `None`, `Weak`, `Medium`, and `Strong`.
+- `label`: Binary benchmark label derived from `binding_strength`. `0` corresponds to `None`; `1` corresponds to `Weak`, `Medium`, or `Strong`.
+- `value`: KD value for the binder-target pair, when KD measurements exist.
+- `max_similarity_to_any_database`: Maximum sequence similarity to any reference database as extracted from the raw ProteinBase evaluations.
+- `design_class`: Binder design class (e.g. scFv, miniprotein, peptide)
+- `antibody`: `True` for `Nanobody` and `scFv` binders, `False` otherwise.
+
+## Filtering
+
+Rows are retained only if all of the following are true:
+
+- the raw entry contains at least one target
+- the binder is marked as expressed (poor expression yield does not indicate non-binding)
+
+Recognized design classes are split into two groups:
+
+- non-antibody binders:
+  - `Miniprotein`
+  - `Other`
+  - `Peptide`
+- antibody binders:
+  - `Nanobody`
+  - `scFv`
+
+Additional similarity filtering is applied only to non-antibody binders:
+
+- non-antibody rows are kept only if `max_similarity_to_any_database <= 50`
+- antibody rows are retained regardless of this non-antibody threshold, and are marked by `antibody=True`
+
+## Label Definition
+
+The binary classification label is defined as:
+
+- `label = 0` if `binding_strength == "None"`
+- `label = 1` if `binding_strength` is `Weak`, `Medium`, or `Strong`
+
+## Binding Affinity Value
+
+The `value` column stores:
+
+- the minimum KD value across available KD measurements for the corresponding binder-target pair
+
+If no numeric KD is available, `value` is left blank.
+
+## Raw Source Collections
+
+This dataset is currently constructed from the following ProteinBase collections:
+
+- `proteinbase_collection_adaptyv-egfr-competition-round-1.csv`
+- `proteinbase_collection_adaptyv-egfr-competition-round-2.csv`
+- `proteinbase_collection_adaptyv-x-muni-hackathon-ai-agents-vs-humans.csv`
+- `proteinbase_collection_bindcraft1-revalidation.csv`
+- `proteinbase_collection_boltzgen-release.csv`
+- `proteinbase_collection_boolean-biotech-vhh-competition-2025.csv`
+- `proteinbase_collection_cradle-egfr-competition.csv`
+- `proteinbase_collection_dsm-round-1.csv`
+- `proteinbase_collection_egfr-round1-second-submission.csv`
+- `proteinbase_collection_evodiff-validation.csv`
+- `proteinbase_collection_evolved-2024-bio-x-ml-team-silica-egfr-nanobodies.csv`
+- `proteinbase_collection_evolved-hackathon.csv`
+- `proteinbase_collection_gem-x-adaptyv-rbx1-binder-design-competition-results.csv`
+- `proteinbase_collection_mog-dfm-spotlight.csv`
+- `proteinbase_collection_mosaic-development.csv`
+- `proteinbase_collection_mosaic-multispecifics.csv`
+- `proteinbase_collection_nipah-binder-competition-results.csv`
+- `proteinbase_collection_pd-l1-foldcraft.csv`
+- `proteinbase_collection_pro-1-validation.csv`
+- `proteinbase_collection_protrl-validation.csv`
+- `proteinbase_collection_rfdiffusion-re-validation.csv`