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# Changelog
All notable changes to the Docking@HOME project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [1.0.0] - 2025-11-19
### Added
#### Core Features
- AutoDock 4.2.6 integration for molecular docking
- CUDA/CUDPP GPU acceleration for parallel docking
- BOINC distributed computing framework integration
- The Decentralized Internet SDK for Distributed Network Settings-based coordination
- Cloud Agents AI-powered task orchestration
- HuggingFace model card and integration
#### Components
- C++ BOINC wrapper with client/server support
- CUDA kernels for GPU-accelerated docking
- Genetic algorithm implementation on GPU
- JavaScript decentralized coordinator
- Python Cloud Agents orchestrator
- Command-line interface (CLI)
- Python API
#### Build System
- CMake build configuration
- Python package setup
- Node.js package configuration
- Cross-platform support
#### Documentation
- Comprehensive README with architecture diagrams
- HuggingFace Model Card
- Contributing guidelines
- License (GPL-3.0)
- Example workflows
- Configuration guides
#### Features
- Task submission and tracking
- Real-time progress monitoring
- Result retrieval and analysis
- GPU benchmarking
- Worker node management
- System statistics
- Auto-scaling recommendations
### Authors
- 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
### Technical Specifications
- Support for PDBQT format (ligands and receptors)
- GPU acceleration with CUDA
- Distributed computing via BOINC
- Distributed Network Settings coordination via the Decentralized Internet SDK
- AI optimization via Cloud Agents
- Performance: ~2,000 runs/hour on single RTX 3090
- Distributed: 100,000+ runs/hour on 1000 nodes
### Known Limitations
- Requires CUDA-capable GPU for optimal performance
- Limited receptor flexibility (rigid docking)
- Simplified solvation models
- Requires external validation of results
---
## Future Releases
### [1.1.0] - Planned
- Enhanced flexibility modeling
- Improved solvation models
- Web-based user interface
- Real-time visualization
- Enhanced metal coordination handling
### [2.0.0] - Planned
- Machine learning scoring functions
- Multi-receptor ensemble docking
- Enhanced Cloud Agents integration
- Advanced distributed network features
- Native cloud deployment support
---
**Note**: For detailed changes in each release, see the [HuggingFace Releases](https://huggingface.co/OpenPeerAI/DockingAtHOME/discussions) page.
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