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Dataset Card for SPIN-PPI
Dataset Summary
SPIN-PPI is a dataset and processed-resource collection for structure-guided protein–protein interaction (PPI) prediction with adaptive structural prior integration.
The dataset supports the manuscript:
SPIN-PPI: Adaptive structural prior integration for memory-efficient protein–protein interaction prediction
This dataset repository provides raw PPI interaction files, protein sequence dictionaries, protein structure files, and processed data used by the SPIN-PPI training and evaluation pipeline.
The repository currently supports five benchmark datasets:
- SHS27k
- SHS148k
- STRING
- SYS30k
- SYS60k
The corresponding GitHub repository provides source code, training scripts, inference scripts, preprocessing utilities, ESMC embedding-generation scripts, and reproducibility instructions.
Dataset Description
What the dataset contains
SPIN-PPI supports multi-type PPI prediction under structure-guided and resource-aware settings. Each benchmark contains protein pairs and interaction labels. The released resources can be used to construct residue-level heterogeneous structural-prior graphs with the following relation channels:
| Prior channel | Description |
|---|---|
SEQ |
Sequence adjacency between neighboring residues |
STR-KNN |
Local structural neighborhoods based on Cα K-nearest neighbors |
STR-DIS |
Distance-thresholded structural contacts |
SURF |
Exposed-surface proximity derived from solvent-accessible surface information |
LRR-REGION |
LRR-region connectivity derived from structure-aware LRR annotation |
SPIN-PPI adaptively calibrates these structural priors and compresses residue-level features into protein-level representations for downstream GraphConv-based PPI prediction.
Supported benchmarks
| Dataset | Species / source context | Approximate scale |
|---|---|---|
| SHS27k | Human PPI benchmark from the SHS-style benchmark family | ~27k protein-pair records |
| SHS148k | Human PPI benchmark from the SHS-style benchmark family | ~148k protein-pair records |
| STRING | Human PPI benchmark derived from STRING-style resources | Benchmark split provided in this release |
| SYS30k | Yeast PPI benchmark constructed under the same SHS-style protocol | ~30k protein-pair records |
| SYS60k | Yeast PPI benchmark constructed under the same SHS-style protocol | ~60k protein-pair records |
Splits
The manuscript uses the following split strategies:
randombfsdfs
The train/validation/test ratio is 6:2:2.
BFS and DFS splits are used as harder graph-topology generalization settings than random splits.
Dataset Files
This Hugging Face dataset repository currently contains the following archives:
| Archive | Description | Size |
|---|---|---|
Sparse-SP-PPI_raw_data.zip |
Raw PPI interaction files and sequence dictionaries | ~32.4 MB |
Sparse-SP-PPI_pdb_structures.zip |
Protein structure files used for structural-prior graph construction | ~1.82 GB |
Sparse-SP-PPI_processed_data.zip |
Processed data used by the SPIN-PPI training and evaluation pipeline | ~1.36 GB |
Note: The archive names retain the legacy prefix
Sparse-SP-PPIfor compatibility with the original data release. They correspond to the SPIN-PPI dataset used in the manuscript.
Precomputed ESMC embeddings are not distributed as a separate archive in this Hugging Face release. Instead, ESMC-600M residue embeddings can be generated from the released protein sequences using the embedding-generation scripts provided in the GitHub repository.
Data Fields
PPI interaction files
Interaction files are tab-separated and follow the format:
protein1 protein2 interaction_type
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