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Expand Up @@ -9,18 +9,16 @@ Welcome to the official repository for the Uni-Mol series methods!

| Fold | In Short | Description |
|------------------------|---------------------------|-------------|
| [Uni-Mol](./unimol/) | Molecule Representation Framework | Uni-Mol is a universal 3D molecular representation learning framework designed for various downstreams tasks. You can use Uni-Mol in various molecule related tasks, including molecule property prediction, binding pose prediction etc. Released with [Zhou et al. 2022](https://openreview.net/forum?id=6K2RM6wVqKu) (ICLR 2023 version).|
| [Uni-Mol+](./unimol_plus/) | Molecule Quantumn Chemical Modeling | Un-Mol+ is design for molecule quantumn chemical property prediction, and ranks the 1st in two well-known benchmarks, OGB-LSC and OC20. You can use Uni-Mol+ in molecule geometry related tasks, such as conformation generation and optimization, quantumn property prediction. Released with [Lu et al. 2023](https://arxiv.org/pdf/2303.16982) (Nat Comm, Aug 2024). |
| [Uni-Mol Tools](./unimol_tools/) | Molecule Property Prediction Tools | Uni-Mol tools is a easy-use wrappers for automatic property prediction, representation with Uni-Mol. You can install with `pip install unimol-tools`. Released with [Gao et al. 2023](https://arxiv.org/pdf/2304.12239). (Arixv, Apr 2023).|
| [Uni-Mol Docking](./unimol_docking_v2/) | Protein Ligand Docking Tools | Uni-Mol Docking achieves industry-leading performance in complex structure prediction, comparable to AlphaFold3. You can use Uni-Mol Docking for target docking with given pockets. Released with [E Alcaide et al. 2024](https://arxiv.org/pdf/2405.11769). (Arixv, May 2024).|
| [Uni-Mol](./unimol/) | Molecule Representation Framework | Uni-Mol is a universal 3D molecular representation learning framework designed for various downstreams tasks. You can use Uni-Mol in various molecule related tasks, including molecule property prediction, binding pose prediction etc. Released with [Zhou et al. 2022](https://openreview.net/forum?id=6K2RM6wVqKu) (ICLR 2023).|
| [Uni-Mol+](./unimol_plus/) | Molecule Quantumn Chemical Modeling | Un-Mol+ is design for molecule quantumn chemical property prediction, and ranks the 1st in two well-known benchmarks, OGB-LSC and OC20. You can use Uni-Mol+ in molecule geometry related tasks, such as conformation generation and optimization, quantumn property prediction. Released with [Lu et al. 2023](https://www.nature.com/articles/s41467-024-51321-w) (Nat Comm, Aug 2024). |
| [Uni-Mol Tools](./unimol_tools/) | Molecule Property Prediction Tools | Uni-Mol tools is a easy-use wrappers for automatic property prediction, representation with Uni-Mol. You can install with `pip install unimol-tools`. Released with [Gao et al. 2023](https://arxiv.org/pdf/2304.12239). (Arixv Report, Apr 2023).|
| [Uni-Mol Docking](./unimol_docking_v2/) | Protein Ligand Docking Tools | Uni-Mol Docking achieves industry-leading performance in complex structure prediction, comparable to AlphaFold3. You can use Uni-Mol Docking for target docking with given pockets. Released with [E Alcaide et al. 2024](https://arxiv.org/pdf/2405.11769). (Arixv Report, May 2024).|


Uni-Mol: A Universal 3D Molecular Representation Learning Framework
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[[Paper](https://openreview.net/forum?id=6K2RM6wVqKu)], [[Uni-Mol Docking Colab](https://colab.research.google.com/github/deepmodeling/Uni-Mol/blob/main/unimol/notebooks/unimol_binding_pose_demo.ipynb)]

Authors: Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu, Zhewei Wei, Linfeng Zhang, Guolin Ke
[[Paper](https://openreview.net/forum?id=6K2RM6wVqKu)], [[Uni-Mol Property Prediction Service](https://bohrium.dp.tech/apps/qsar-web-new)],[[Uni-Mol Docking Service](https://bohrium.dp.tech/apps/unimoldockingv2)]

<p align="center"><img src="unimol/figure/overview.png" width=60%></p>
<p align="center"><b>Schematic illustration of the Uni-Mol framework</b></p>
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News
----
**Aug 19 2024**: Uni-Mol+ is accepted by Nature Communications, reference: [Data-driven quantum chemical property prediction leveraging 3D conformations with Uni-Mol+](https://www.nature.com/articles/s41467-024-51321-w).

**Jul 1 2024**: We release [Uni-Mol2 arxiv report](https://arxiv.org/pdf/2406.14969), the largest molecular pretraining model to date with 1.1B parameters through pretraining on 800M conformations.

**May 20 2024**: We release Uni-Mol Docking V2, including data, model and weight.

**Jul 7 2023**: We update a new version of Uni-Mol+, including the model setting for OC20 and a better performance on PCQM4MV2.
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