| # DrugRNA Dataset | |
| This repository contains the RNA-small molecule interaction prediction dataset used in the paper "LLM Agents Enable RNA–Small Molecule Interaction Prediction at Performance Comparable to Human-Designed Models". | |
| ## Dataset Description | |
| The dataset is derived from the RNAInter repository and contains experimentally validated RNA-compound interactions. It includes 45,049 RNA–compound pairs spanning 3,258 unique RNAs and 345 unique compounds, with a 1:4 positive/negative ratio. | |
| ## Data Splits | |
| The dataset is organized into three evaluation scenarios: | |
| ### 1. In-Distribution Split (`in_distribution/`) | |
| - **Purpose**: Standard 80/10/10 train/validation/test split for head-to-head performance comparison | |
| - **Characteristics**: Complete entity overlap, testing interpolation within known molecular space | |
| - **Files**: | |
| - `train_text.csv` (36,040 samples, 20.0% positive) | |
| - `val_text.csv` (4,504 samples, 19.8% positive) | |
| - `test_text.csv` (4,505 samples, 20.2% positive) | |
| - **Total**: 45,049 samples with 3,258 unique RNAs and 345 unique compounds | |
| ### 2. Full Out-of-Domain Split (`full_ood/`) | |
| - **Purpose**: Cold-start prediction with entirely novel entities | |
| - **Characteristics**: Zero overlap for both RNAs and compounds between training and test sets | |
| - **Files**: | |
| - `train_text.csv` (21,794 samples, 18.4% positive) | |
| - `val_text.csv` (1,081 samples, 22.1% positive) | |
| - `test_text.csv` (1,020 samples, 24.2% positive) | |
| - `DATASET_REPORT.md` (detailed statistics and construction methodology) | |
| - **Total**: 23,895 samples with 3,142 unique RNAs and 363 unique compounds | |
| ### 3. Compound Out-of-Domain Split (`compound_ood/`) | |
| - **Purpose**: Virtual screening of novel compounds against known RNA targets | |
| - **Characteristics**: Zero compound overlap, complete RNA reuse (86% of training RNAs appear in test) | |
| - **Files**: | |
| - `train_text.csv` (31,576 samples, 21.0% positive) | |
| - `val_text.csv` (6,694 samples, 20.1% positive) | |
| - `test_text.csv` (6,779 samples, 15.2% positive) | |
| - `DATASET_REPORT.md` (detailed statistics and construction methodology) | |
| - **Total**: 45,049 samples with 3,258 unique RNAs and 345 unique compounds | |
| ## Data Format | |
| Each CSV file contains the following columns: | |
| - `rna_id`: RNA identifier | |
| - `compound_id`: Compound identifier (PubChem CID) | |
| - `rna_sequence`: RNA nucleotide sequence (A, U, G, C) | |
| - `compound_smiles`: SMILES string representation of the compound | |
| - `label`: Binary interaction label (1 = interaction, 0 = no interaction) | |
| ## Scripts | |
| The `scripts/` folder contains: | |
| - `create_disjoint_splits.py`: Script used to generate the out-of-domain splits with strict entity disjointness | |
| ## Data Sources | |
| - **RNAs**: Mapped from NCBI, Ensembl, miRBase, and circBase | |
| - **Compounds**: Mapped from PubChem | |
| - **Interactions**: Curated from RNAInter repository with experimental evidence | |
| ## Citation | |
| If you use this dataset in your research, please cite: | |
| ```bibtex | |
| @article{drugrna2025, | |
| title={LLM Agents Enable RNA–Small Molecule Interaction Prediction at Performance Comparable to Human-Designed Models}, | |
| author={...}, | |
| journal={...}, | |
| year={2025} | |
| } | |
| ``` | |
| ## License | |
| This dataset is provided for research purposes. Please refer to the original data sources for specific licensing information. | |
| ## Contact | |
| For questions or issues, please open an issue on the GitHub repository or contact the authors. | |