| # 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. | |