Metadata-Version: 2.4
Name: CondenSimAdapter
Version: 1.0.1
Summary: Automated CG-to-AA workflow for protein condensate simulations
Author-email: Xiaojing Tian <tianxj15@tsinghua.org>
License: GPL-3.0
Project-URL: Homepage, https://github.com/hanlab-computChem/CondenSimAdapter
Project-URL: Documentation, https://github.com/hanlab-computChem/CondenSimAdapter#readme
Project-URL: Repository, https://github.com/hanlab-computChem/CondenSimAdapter
Project-URL: Issues, https://github.com/hanlab-computChem/CondenSimAdapter/issues
Project-URL: Changelog, https://github.com/hanlab-computChem/CondenSimAdapter/blob/main/CHANGELOG.md
Keywords: protein,condensate,simulation,coarse-grained,molecular-dynamics,openmm
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: <3.12,>=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
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Requires-Dist: numpy<2.0,>=1.26
Requires-Dist: tqdm>=4.0
Requires-Dist: pydantic>=2.0
Requires-Dist: openmm>=8.2
Requires-Dist: mdtraj>=1.10
Requires-Dist: MDAnalysis<3.0,>=2.6
Requires-Dist: biopython>=1.81
Requires-Dist: parmed
Requires-Dist: gromacswrapper
Requires-Dist: scipy>=1.10
Requires-Dist: matplotlib>=3.5
Requires-Dist: networkx>=2.8
Requires-Dist: numba>=0.60
Requires-Dist: jinja2
Requires-Dist: statsmodels
Requires-Dist: PeptideConstructor
Requires-Dist: torch<2.2,>=2.1
Requires-Dist: dgl>=2.1
Requires-Dist: e3nn>=0.5
Requires-Dist: torchdata<0.8,>=0.7
Requires-Dist: ml-collections>=0.1
Provides-Extra: dev
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Dynamic: license-file

# CondenSimAdapter

CondenSimAdapter is an automated workflow for protein condensate simulations, covering the main stages from coarse-grained (CG) to all-atom (AA).

## Installation

### Quick Start

```bash
# 1. Create a conda environment
conda create -n conden python=3.11 -y
conda activate conden

# 2. Install from PyPI
pip install CondenSimAdapter

# 3. Verify installation
adapter --version
```

### Standard Installation

```bash
pip install CondenSimAdapter
```

This installs **everything** including:
- Core simulation tools (OpenMM, MDAnalysis, mdtraj)
- Neural network backmapping (PyTorch, DGL, e3nn)

**Requirements:** CUDA-capable GPU with CUDA >= 12.1

## Development Installation

If you want to modify the source code:

```bash
git clone https://github.com/hanlab-computChem/CondenSimAdapter.git
cd CondenSimAdapter
pip install -e ".[dev]"
```

## Testing

```bash
# Run tests
pytest tests/

# Run with coverage
pytest tests/ --cov=CondenSimAdapter
```

## Usage

### Command Line Interface

```bash
# Show help
adapter --help

# Run backmapping
adapter backmap -c cg_structure.pdb -o aa_structure.pdb

# Check model status
adapter models status
```

### Python API

```python
from CondenSimAdapter import backmap

# Backmap CG structure to AA
backmap.convert("cg_input.pdb", "aa_output.pdb")
```

## Requirements

- Python >= 3.10, < 3.12 (3.11 recommended)
- CUDA >= 12.1 (for ML features)
- GROMACS >= 2023 (install separately)

## Links

- **PyPI**: https://pypi.org/project/CondenSimAdapter/
- **Documentation**: https://github.com/hanlab-computChem/CondenSimAdapter#readme
- **Issues**: https://github.com/hanlab-computChem/CondenSimAdapter/issues

## License

GPL-3.0
