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# Docking@HOME

**Distributed and Parallel Molecular Docking Platform**

[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
[![BOINC](https://img.shields```bibtex

@software{docking_at_home_2025,

  title={Docking@HOME: Distributed Molecular Docking Platform},

  author={OpenPeer AI and Riemann Computing Inc. and Bleunomics and Andrew Magdy Kamal},

  year={2025},

  url={https://huggingface.co/OpenPeerAI/DockingAtHOME}

}

```e/BOINC-Enabled-green.svg)](https://boinc.berkeley.edu/)

[![HuggingFace](https://img.shields.io/badge/%F0%9F%A4%97-Models-yellow)](https://huggingface.co/)



## Overview



Docking@HOME is a cutting-edge distributed computing platform that leverages the power of volunteer computing, GPU acceleration, decentralized networking, and AI-driven orchestration to perform large-scale molecular docking simulations. This project combines multiple state-of-the-art technologies to democratize drug discovery and computational chemistry.



### Key Features



- 🧬 **AutoDock Integration**: Uses AutoDock Suite 4.2.6 for molecular docking simulations

- 🚀 **GPU Acceleration**: CUDPP-powered parallel processing for enhanced performance

- 🌐 **Distributed Computing**: BOINC framework for volunteer computing at scale

- 🔗 **Decentralized Networking**: Distributed Network Settings-based coordination using the Decentralized Internet SDK

- 🤖 **AI Orchestration**: Cloud Agents for intelligent task distribution and optimization

- 📊 **HuggingFace Integration**: Model cards and datasets for reproducible research



## Architecture



```
┌─────────────────────────────────────────────────────────────┐
│                    Docking@HOME Platform                     │
├─────────────────────────────────────────────────────────────┤
│  ┌──────────────┐  ┌──────────────┐  ┌─────────────────┐  │
│  │ Cloud Agents │  │ Decentralized│  │  BOINC Server   │  │
│  │ (AI Routing) │◄─┤  Internet    │◄─┤  (Task Mgmt)    │  │
│  └──────────────┘  └──────────────┘  └─────────────────┘  │
│         ▼                                      ▼            │
│  ┌──────────────────────────────────────────────────────┐  │
│  │         Distributed Worker Nodes (BOINC Clients)     │  │
│  │  ┌──────────────┐        ┌──────────────┐           │  │
│  │  │   AutoDock   │◄──────►│    CUDPP     │           │  │
│  │  │  (Docking)   │        │ (GPU Accel)  │           │  │
│  │  └──────────────┘        └──────────────┘           │  │
│  └──────────────────────────────────────────────────────┘  │
└─────────────────────────────────────────────────────────────┘
```



## Components



### 1. AutoDock Suite (v4.2.6)

Core molecular docking engine that predicts binding modes and affinities of small molecules to protein targets.



### 2. CUDPP (CUDA Data Parallel Primitives Library)

Provides GPU-accelerated parallel primitives for enhancing AutoDock's computational performance.



### 3. BOINC (Berkeley Open Infrastructure for Network Computing)

Distributed computing middleware that manages volunteer computing resources globally.



### 4. The Decentralized Internet SDK

Enables Distributed Network Settings-based coordination, ensuring transparency and decentralization of task distribution.



### 5. Cloud Agents

AI-powered orchestration layer that optimizes task scheduling and resource allocation based on workload characteristics.



## Authors & Contributors



- **OpenPeer AI** - AI/ML Integration & Cloud Agents

- **Riemann Computing Inc.** - Distributed Computing Architecture

- **Bleunomics** - Bioinformatics & Drug Discovery Expertise

- **Andrew Magdy Kamal** - Project Lead & System Integration



## Installation



### Prerequisites



- C++ compiler (GCC 7+ or MSVC 2019+)

- CUDA Toolkit 11.0+ (for GPU acceleration)

- Python 3.8+

- Node.js 16+ (for the Decentralized Internet SDK)

- BOINC client/server software



### Build Instructions



```bash

# Clone the repository

git clone https://huggingface.co/OpenPeerAI/DockingAtHOME

cd DockingAtHOME



# Initialize submodules

git submodule update --init --recursive



# Build the project

mkdir build && cd build

cmake ..

make -j$(nproc)



# Install

sudo make install

```

### Docker Installation

```bash

docker pull your-org/docking-at-home:latest

docker run -d --gpus all your-org/docking-at-home:latest

```

## Quick Start

### Web GUI (Recommended!)

```bash

# Install dependencies

pip install -r requirements.txt



# Start the GUI server

python start.py



# Open browser to: http://localhost:8080

```

The GUI provides:
- 🖱️ **Drag-and-drop** file upload
- 📊 **Real-time** progress monitoring
- 📈 **Live statistics** dashboard
- 🎯 **Interactive** job management
- 📱 **Responsive** design

### Command Line

```bash

# Run docking from terminal

docking-at-home dock -l molecule.pdbqt -r protein.pdbqt



# Start server

docking-at-home server --port 8080



# Start worker

docking-at-home worker --local

```

### Python API

```python

from docking_at_home.server import job_manager, initialize_server

import asyncio



async def main():

    await initialize_server()

    

    job_id = await job_manager.submit_job(

        ligand_file="molecule.pdbqt",

        receptor_file="protein.pdbqt",

        num_runs=100,

        use_gpu=True

    )

    

    # Monitor progress

    while True:

        job = job_manager.get_job(job_id)

        if job["status"] == "completed":

            print(f"Best energy: {job['results']['best_energy']}")

            break

        await asyncio.sleep(1)



asyncio.run(main())

```

### Running on Localhost

```bash

# Start the local server

docking-at-home server --port 8080



# In another terminal, run the worker

docking-at-home worker --local

```

## Configuration

Configuration files are located in `config/`:

- `autodock.conf` - AutoDock parameters
- `boinc_server.conf` - BOINC server settings
- `gpu_config.conf` - CUDPP and GPU settings
- `decentralized.conf` - Distributed Network Settings
- `cloud_agents.conf` - AI orchestration parameters

## API Documentation

Full API documentation is available at [docs/API.md](docs/API.md)

## Performance

On a typical configuration:
- **CPU-only**: ~100 docking runs/hour
- **Single GPU (RTX 3090)**: ~2,000 docking runs/hour
- **Distributed (1000 nodes)**: ~100,000+ docking runs/hour

## Use Cases

- 🔬 Drug Discovery and Virtual Screening
- 🧪 Protein-Ligand Binding Studies
- 📚 Large-Scale Chemical Library Screening
- 🎓 Educational Computational Chemistry
- 🌍 Pandemic Response (e.g., COVID-19 drug discovery)

## Contributing

We welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.

## License

This project is licensed under the GNU General Public License v3.0 - see [LICENSE](LICENSE) for details.

Individual components retain their original licenses:
- AutoDock: GNU GPL v2
- BOINC: GNU LGPL v3
- CUDPP: BSD License

## Citation

If you use Docking@HOME in your research, please cite:

```bibtex

@software{docking_at_home_2025,

  title={Docking@HOME: A Distributed Platform for Molecular Docking},

  author={OpenPeer AI and Riemann Computing Inc. and Bleunomics and Andrew Magdy Kamal},

  year={2025},

  url={https://huggingface.co/OpenPeerAI/DockingAtHOME}

}

```

## HuggingFace Integration

Model cards and datasets are available at:
- 🤗 [https://huggingface.co/OpenPeerAI/DockingAtHOME](https://huggingface.co/OpenPeerAI/DockingAtHOME)

## Support

- 📧 Email: andrew@bleunomics.com
- � Issues: [HuggingFace Issues](https://huggingface.co/OpenPeerAI/DockingAtHOME/discussions)
- 🤗 Community: [HuggingFace Discussions](https://huggingface.co/OpenPeerAI/DockingAtHOME/discussions)

## Acknowledgments

- The AutoDock development team at The Scripps Research Institute
- BOINC project at UC Berkeley
- CUDPP developers
- Lonero Team for the Decentralized Internet SDK
- OpenPeer AI for Cloud Agents framework

---

**Made with ❤️ by the open-source computational chemistry community**