| --- |
| license: cc-by-4.0 |
| task_categories: |
| - text-generation |
| language: |
| - en |
| tags: |
| - peptide |
| - HELM |
| - chemistry |
| - drug-discovery |
| - antimicrobial-peptide |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # PepForge — Training Data |
|
|
| Training data for [PepForge](https://github.com/wqx1999/PepForge), a hierarchical deep learning framework for generating peptides with special connections using HELM notation. |
|
|
| ## Overview |
|
|
| | Category | Description | Size | |
| |----------|-------------|------| |
| | **Raw HELM data** | Generation corpus (383,817 molecules) + AMP corpus (11,026 active peptides) | ~80 MB | |
| | **Generation splits** | Train/val/test + per-stage hierarchical (layout/content) | ~395 MB | |
| | **Prediction splits** | AMP 5-class classification (train/val/test/train_active/unlabeled_pool) | ~43 MB | |
| | **Tokenizers** | Layout + content monomer vocabularies | <1 MB | |
| | **Monomer library** | HELM monomer definitions and R-group rules | <1 MB | |
| | **Embeddings** | Pre-computed ChemBERTa monomer embeddings (384-dim) | <1 MB | |
|
|
| Total size: ~520 MB |
|
|
| Data sources: PubChem, CycPeptMPDB, ChEMBL, DBAASP, UniProt, MacrocycleDB (all publicly available). The AMP corpus is restricted to **CLSI MIC-only DBAASP** measurements (2026-04-28 update). |
|
|
| ## Generation Corpus |
|
|
| `Data/all_peptides/HELM.csv` — 383,817 unique molecules in HELM notation, deduplicated by InChIKey. |
|
|
| | Split | Records | File | Size | |
| |-------|--------:|------|------| |
| | train | 307,055 | `Generation/processed/train.jsonl` | 210 MB | |
| | val | 38,381 | `Generation/processed/val.jsonl` | 26 MB | |
| | test | 38,381 | `Generation/processed/test.jsonl` | 26 MB | |
|
|
| Per-stage hierarchical splits in `Generation/processed/hierarchical/`: |
|
|
| | Stage | Train | Val | Test | |
| |-------|------:|----:|----:| |
| | Layout (block-type sequences) | 307,055 | 38,381 | 38,381 | |
| | Content (monomer sequences per block) | 387,948 | 48,294 | 48,529 | |
|
|
| Average blocks per HELM (train split): 1.26. |
|
|
| ## AMP Prediction Corpus |
|
|
| `Data/amp_peptides/HELM.csv` — 11,026 antimicrobial peptides with curated MIC values, restricted to CLSI MIC measurements only (DBAASP, MIC-only filter). |
|
|
| 5-class label scheme (activity bins [8, 32, 128] μg/mL): |
|
|
| | Class | Definition | |
| |-------|------------| |
| | `background` | not classified active | |
| | `class_1` | MIC ≥ 128 μg/mL | |
| | `class_2` | 32 ≤ MIC < 128 μg/mL | |
| | `class_3` | 8 ≤ MIC < 32 μg/mL | |
| | `class_4` | MIC < 8 μg/mL | |
|
|
| | Split | Records | background | class_1 | class_2 | class_3 | class_4 | |
| |-------|--------:|---------:|--------:|--------:|--------:|--------:| |
| | train | 17,640 | 8,820 | 1,858 | 2,495 | 2,847 | 1,620 | |
| | val | 2,206 | 1,103 | 250 | 310 | 364 | 179 | |
| | test | 2,206 | 1,103 | 232 | 312 | 360 | 199 | |
| | train_active | 8,820 | – | 1,858 | 2,495 | 2,847 | 1,620 | |
| | unlabeled_pool| 47,467 | 47,467 | – | – | – | – | |
|
|
| `train_active.jsonl` excludes the background class for active-only training experiments. `unlabeled_pool.jsonl` contains additional background peptides used for negative-mining experiments. |
|
|
| ## Quick Start |
|
|
| ```bash |
| git clone https://github.com/wqx1999/PepForge.git |
| cd PepForge |
| python install.py # Installs env + downloads all models & data |
| ``` |
|
|
| For details, see the [GitHub repository](https://github.com/wqx1999/PepForge). |
|
|
| ## File Structure |
|
|
| ``` |
| pepforge-training-data/ |
| ├── Data/ |
| │ ├── all_peptides/HELM.csv (75 MB, 383,817 molecules) |
| │ └── amp_peptides/HELM.csv (4.9 MB, 11,026 active peptides) |
| ├── Generation/processed/ |
| │ ├── {train,val,test}.jsonl |
| │ ├── stats.json |
| │ └── hierarchical/ |
| │ ├── {train,val,test}_layout.jsonl |
| │ ├── {train,val,test}_content.jsonl |
| │ └── {train,val,test}_hierarchical_stats.json |
| ├── Prediction/processed/ |
| │ ├── {train,val,test}.jsonl |
| │ ├── train_active.jsonl |
| │ └── unlabeled_pool.jsonl |
| ├── Tokenizers/ |
| │ ├── content_vocab.json |
| │ └── layout_vocab.json |
| ├── Monomer/HELMLibrary.json |
| └── Embeddings/ |
| ├── monomer_embeddings.pt (384-dim, ChemBERTa) |
| └── monomer_embeddings.manifest.json |
| ``` |
|
|
| ## Related Resources |
|
|
| - **Code**: [wqx1999/PepForge](https://github.com/wqx1999/PepForge) |
| - **Models**: [pepforge-model](https://huggingface.co/qingxin1999/pepforge-model) |
| - **Generated library**: [pepforge-generated-data](https://huggingface.co/datasets/qingxin1999/pepforge-generated-data) |
| - **Figure data**: [pepforge-fig-data](https://huggingface.co/datasets/qingxin1999/pepforge-fig-data) |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{wang2026pepforge, |
| title={PepForge: Hierarchical HELM-Based Peptide Generation}, |
| author={Wang, Qingxin and Süssmuth, Roderich D.}, |
| journal={bioRxiv}, |
| year={2026}, |
| doi={10.64898/2026.05.29.728379}, |
| url={https://www.biorxiv.org/content/10.64898/2026.05.29.728379v1} |
| } |
| ``` |
|
|
| ## License |
|
|
| CC-BY-4.0 |
|
|
