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---
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---
# Apo2Mol Dataset
This repository hosts the dataset for **Apo2Mol: 3D Molecule Generation via Dynamic Pocket-Aware Diffusion Models** [[Paper](https://arxiv.org/abs/2511.14559), [Github](https://github.com/AIDD-LiLab/Apo2Mol)].
## Overview
**Apo2Mol Dataset** is a structure-based drug design (SBDD) resource developed for **pocket-based 3D ligand generation under protein structural dynamics**.
It contains **24,601 paired apo-holo protein structures**, along with their associated **ligands** and corresponding **binding pockets**, and includes a predefined train/validation/test split.
The dataset is organized using [**PLINDER Protein–Ligand Interaction (PLI) IDs**](https://www.plinder.sh/), where each entry contains a consistent and well-aligned set of structural components required for apo-to-holo modeling.
---
## Files in This Repository
This repository contains **two files**:
```text
β”œβ”€β”€ data_folder.tar.gz
β”œβ”€β”€ split_druglike_dict.pkl
```
---
## 1. `data_folder.tar.gz`
This archive contains all structural data files.
After extraction:
```bash
tar -xzf data_folder.tar.gz
```
you will obtain a directory:
```text
data_folder/
β”œβ”€β”€ <PLINDER_PLI_ID_1>/
β”‚ β”œβ”€β”€ receptor_holo_pocket10.pdb
β”‚ β”œβ”€β”€ receptor_apo_pocket10.pdb
β”‚ β”œβ”€β”€ ligand.sdf
β”‚ β”œβ”€β”€ receptor_holo_prot.pdb
β”‚ └── receptor_apo_prot.pdb
β”œβ”€β”€ <PLINDER_PLI_ID_2>/
β”‚ └── ...
```
Each subfolder is named by a **PLINDER PLI ID** and contains **exactly five files**:
| File name | Description |
| ---------------------------- | ----------------------------------------------------------|
| `receptor_holo_prot.pdb` | Full holo protein structure |
| `receptor_holo_pocket10.pdb` | Binding pocket* extracted from the holo protein structure |
| `receptor_apo_prot.pdb` | Full apo protein structure |
| `receptor_apo_pocket10.pdb` | Binding pocket* extracted from the apo protein structure |
| `ligand.sdf` | Bound ligand structure |
*For each complex, the holo pocket is defined as all residues within 10Γ… of any ligand atom, and the corresponding apo pocket is obtained by extracting the same residues from the unbound structure.
---
## 2. `split_druglike_dict.pkl`
This file defines the **data split** used in Apo2Mol.
It is a Python `dict` with three keys:
```python
{
"train": [...],
"valid": [...],
"test": [...]
}
```
Each entry is a tuple with the following structure:
```python
(
holo_pocket_path, apo_pocket_path, ligand_path,
holo_protein_path, apo_protein_path,
date, holo_apo_pocket_rmsd
)
```
### Field Description
| Index | Field | Description |
| ----- | ------------------- | ------------------------------------------------------------ |
| 0 | `holo_pocket_path` | Path to holo pocket structure (`receptor_holo_pocket10.pdb`) |
| 1 | `apo_pocket_path` | Path to apo pocket structure (`receptor_apo_pocket10.pdb`) |
| 2 | `ligand_path` | Path to ligand file (`ligand.sdf`) |
| 3 | `holo_protein_path` | Path to full holo protein structure |
| 4 | `apo_protein_path` | Path to full apo protein structure |
| 5 | `date` | Deposition or release date |
| 6 | `holo_apo_pocket_rmsd`| RMSD between apo and holo pockets |
**Example entry:**
```python
(
'3txj__1__1.A__1.K/receptor_holo_pocket10.pdb',
'3txj__1__1.A__1.K/receptor_apo_pocket10.pdb',
'3txj__1__1.A__1.K/1.K.sdf',
'3txj__1__1.A__1.K/receptor_holo_prot.pdb',
'3txj__1__1.A__1.K/receptor_apo_prot.pdb',
'2011-09-23',
1.3904783
)
```
All paths are **relative to `data_folder/`**.
---
## Loading Example
```python
import pickle
with open("split_druglike_dict.pkl", "rb") as f:
splits = pickle.load(f)
train_set = splits["train"]
```
---
## Citation
If you feel this dataset is useful in your research, please cite the following works:
### Apo2Mol
```bibtex
@article{zheng2025apo2mol,
title={Apo2Mol: 3D Molecule Generation via Dynamic Pocket-Aware Diffusion Models},
author={Zheng, Xinzhe and Jiang, Shiyu and Seabra, Gustavo and Li, Chenglong and Li, Yanjun},
journal={arXiv preprint arXiv:2511.14559},
year={2025}
}
```
### Acknowledgment
This dataset is built upon the [PLINDER (Protein-Ligand Interactions Dataset and Evaluation Resource)](https://www.plinder.sh/).
We thank the PLINDER team for developing and providing the comprehensive protein-ligand interaction data and infrastructure.
Users of this dataset should also acknowledge the original PLINDER work:
```bibtex
@inproceedings{durairaj24plinder,
title={PLINDER: The protein-ligand interactions dataset and evaluation resource},
author={Durairaj, Janani and Adeshina, Yusuf and Cao, Zhonglin and Zhang, Xuejin and Oleinikovas, Vladas and Duignan, Thomas and McClure, Zachary and Robin, Xavier and Rossi, Emanuele and Zhou, Guoqing and others},
booktitle={ICML'24 Workshop ML for Life and Material Science: From Theory to Industry Applications},
year={2024}
}
```