deepmodeling/Uni-Mol
A series of deep-learning pre-trained models for 3D molecular representation, quantum chemical property prediction, and protein-ligand docking.
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Uni-Mol provides universal 3D molecular representation learning through pre-trained transformer-based models. The suite includes Uni-Mol for molecule property and binding pose prediction, Uni-Mol+ for quantum chemical modeling and conformation generation, Uni-Mol Tools for automated property prediction, and Uni-Mol Docking for protein-ligand complex structure prediction. The models are based on 3D spatial graph architectures and rank among top performers on benchmarks like OGB-LSC and OC20.
Frequently asked
- What is deepmodeling/Uni-Mol?
- A series of deep-learning pre-trained models for 3D molecular representation, quantum chemical property prediction, and protein-ligand docking.
- Is Uni-Mol open source?
- Yes — deepmodeling/Uni-Mol is open source, released under the MIT license.
- What language is Uni-Mol written in?
- deepmodeling/Uni-Mol is primarily written in Python.
- How popular is Uni-Mol?
- deepmodeling/Uni-Mol has 1.1k stars on GitHub.
- Where can I find Uni-Mol?
- deepmodeling/Uni-Mol is on GitHub at https://github.com/deepmodeling/Uni-Mol.