InteractBind: A Large-Scale Protein-Ligand Interaction Dataset for Binding Prediction

InteractBind is a physically grounded, large-scale dataset for protein–ligand interaction modeling. It was created by Zhaohan-Meng and last updated on Hugging Face in May 2026. The dataset is designed to provide interpretable and interaction-aware supervision for binding prediction, moving beyond coarse-grained labels.

Use Cases

• Training interaction-aware binding prediction models based on physically grounded interaction data.
• Benchmarking protein-ligand models to assess if they learn binding sites or just binding likelihood.
• Developing interpretable machine learning methods for computational drug discovery.

Strengths

• Dataset is described as 'large-scale', suggesting a substantial number of data points.
• Provides 'physically grounded' and 'interpretable' supervision for protein-ligand interactions.
• Explicitly addresses a gap in datasets that offer only 'coarse-grained supervision' like binary labels.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and sample data are unknown, which may limit suitability assessment.
• License information is not provided, which could restrict usage.

Provenance

Source

Hugging Face dataset by author Zhaohan-Meng.

Collection Method

Method of data gathering is not specified in the provided description.

Freshness

Last updated 2026-05-29 11:22:06; freshness should be verified.