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# Unified All-Atom Molecule Generation with Neural Fields — MCPP Dataset
We curated a dataset of **186,685 MCP–protein complexes** (`mcpp_dataset.tar.gz`) starting from **641 protein–MCP complexes** from the **[RCSB PDB](https://www.rcsb.org/)** using a **“mutate-then-relax”** strategy:
We used this datase in FuncBind (see https://huggingface.co/papers/2511.15906).
## Dataset Generation Pipeline
1. **Mutation:**
MCPs were randomly mutated at **1 to 8 sites** using **213 distinct amino acids**.
2. **Relaxation:**
Mutated complexes were relaxed using **FastRelax in Rosetta**, which iteratively performs side-chain packing and all-atom minimization.
3. **Selection:**
The best complexes were chosen based on **lowest interface scores**.
---
## Dataset Statistics
- MCP lengths: **4–25 amino acids** (average 10)
- **78%** of MCPs contain one or more **non-canonical amino acids**
---
## Dataset Splits
The dataset is split using a clustering-based approach. The **test set** covers **100 protein pockets**:
| Split | File |
|---------------|----------------|
| Training set | `train_data.pt` |
| Validation set| `val_data.pt` |
| Test set | `test_data.pt` |
---
## How to Use
1. **Download and extract:**
```bash
tar -xvzf mcpp_dataset.tar.gz
```
2. **To generate MCP samples with Funcbind, :**
```bash
cp train_data.pt val_data.pt test_data.pt mcpp_dataset/ |