Uni-Mol
github.com/deepmodeling/uni-molUniversal 3D molecular pretraining framework with 209M conformations, scaling to 1.1B parameters (Uni-Mol2) on 800M conformations for molecular property prediction, docking, and quantum chemistry (ICLR 2023, NeurIPS 2024)
Sourced from
- Awesome AI for Science — github.com/deepmodeling/uni-mol
- GitHub — github.com/deepmodeling/uni-mol
Related resources
Deep learning library for Chemistry based on Tensorflow
General-purpose deep learning backbone for molecular modeling
Powerful and flexible machine learning platform for drug discovery, providing comprehensive tools for molecular property prediction, generative models, knowledge graph reasoning, and reaction prediction with PyTorch backend (1.5K+ stars)
Deep learning framework for molecular docking extending AutoDock Vina with convolutional neural network scoring functions, achieving superior virtual screening enrichment and pose prediction across diverse target classes; widely adopted in pharmaceutical structure-based drug design (J. Cheminformatics, 915+ stars, actively maintained)
Structure-aware protein language model using 3D structural vocabulary (Foldseek) for joint sequence-structure pretraining, achieving SOTA on protein engineering and fitness prediction benchmarks (ICML 2024, Westlake University & Repl)
Unified benchmarking framework for protein representation learning, providing standardized interfaces for pre-training and diverse downstream tasks including structure prediction, fitness prediction, and property prediction across multiple protein datasets and model architectures (ICLR 2024, 273+ stars, MIT License)