README.md

metadata

pretty_name: ProteinBase Interactions
license: mit
language:
  - en
tags:
  - protein-protein-interaction
  - binder-design
  - antibody
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data.csv

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