| --- |
| tags: |
| - Biology |
| - RNA Design |
| - Inverse Folding |
| - Geometric Deep Learning |
| license: agpl-3.0 |
| library_name: ofoldx |
| pipeline_tag: other |
| --- |
| |
| # gRNAde |
|
|
| Pre-trained models for RNA inverse folding from one or more backbone conformations. |
|
|
| ## Disclaimer |
|
|
| This is an UNOFFICIAL implementation of the [gRNAde: Geometric Deep Learning for 3D RNA inverse design](https://arxiv.org/abs/2305.14749) by Chaitanya K. Joshi, et al. |
|
|
| The OFFICIAL repository of gRNAde is at [chaitjo/geometric-rna-design](https://github.com/chaitjo/geometric-rna-design). |
|
|
| **The team releasing gRNAde did not write this model card for this model so this model card has been written by the OFoldX team.** |
|
|
| ## Model Details |
|
|
| gRNAde uses a geometric-vector perceptron (GVP) encoder and an autoregressive nucleotide decoder for RNA inverse folding. |
| The encoder combines one or more aligned conformations before predicting RNA identities. The v1 graph incorporates |
| sequence order, explicit secondary-structure base pairs, and optional P, C4', and base-nitrogen geometry; the v0.3.2 graph |
| uses spatial geometry without sequence or base-pair edge channels. |
|
|
| Please refer to the [Training Details](#training-details) section for more information on the training process. |
|
|
| ### Variants |
|
|
| - **v1**: [gRNAde](https://huggingface.co/oteam/grnade) and the [ODesign checkpoint](https://huggingface.co/oteam/grnade-odesign). |
| - **v0.3.2, 1 state**: [all](https://huggingface.co/oteam/grnade-v0.3.2-1state-all), |
| [das](https://huggingface.co/oteam/grnade-v0.3.2-1state-das), [multi](https://huggingface.co/oteam/grnade-v0.3.2-1state-multi). |
| - **v0.3.2, 2 states**: [all](https://huggingface.co/oteam/grnade-v0.3.2-2state-all). |
| - **v0.3.2, 3 states**: [all](https://huggingface.co/oteam/grnade-v0.3.2-3state-all), |
| [das](https://huggingface.co/oteam/grnade-v0.3.2-3state-das), [multi](https://huggingface.co/oteam/grnade-v0.3.2-3state-multi). |
| - **v0.3.2, 5 states**: [all](https://huggingface.co/oteam/grnade-v0.3.2-5state-all), |
| [das](https://huggingface.co/oteam/grnade-v0.3.2-5state-das), [multi](https://huggingface.co/oteam/grnade-v0.3.2-5state-multi). |
|
|
| ### Model Specification |
|
|
| | Variant | Encoder Blocks | Decoder Blocks | Node Scalar / Vector Size | Edge Scalar / Vector Size | Input Edge Channels | Num Parameters (M) | |
| | ------- | -------------- | -------------- | ------------------------- | ------------------------- | ------------------- | ------------------ | |
| | v1 | 4 | 4 | 128 / 16 | 64 / 4 | 132 | 2.157 | |
| | v0.3.2 | 4 | 4 | 128 / 16 | 64 / 4 | 131 | 2.157 | |
|
|
| ### Links |
|
|
| - **Code**: [ofoldx.models.grnade](https://github.com/OTeam-AI4S/OFoldX/tree/main/ofoldx/models/grnade) |
| - **Paper**: [gRNAde: Geometric Deep Learning for 3D RNA inverse design](https://arxiv.org/abs/2305.14749); |
| [Generative inverse design of RNA structure and function with gRNAde](https://www.biorxiv.org/content/10.1101/2025.11.29.691298) |
| - **Developed by**: Chaitanya K. Joshi, Arian R. Jamasb, Ramon Viñas, Charles Harris, Simon V. Mathis, Alex Morehead, |
| Rishabh Anand, and Pietro Liò |
| - **Model type**: Multi-conformation GVP encoder with an autoregressive RNA sequence decoder |
| - **Original Repository**: [chaitjo/geometric-rna-design](https://github.com/chaitjo/geometric-rna-design) |
|
|
| ## Usage |
|
|
| The model file depends on the [`ofoldx`](https://ofoldx.valtech.ai/) library. You can install it using pip: |
|
|
| ```bash |
| pip install ofoldx |
| ``` |
|
|
| ### Direct Use |
|
|
| #### RNA Sequence Design |
|
|
| You can use this model directly with a pipeline for RNA sequence design from a backbone and secondary structure: |
|
|
| ```python |
| import ofoldx |
| from ofoldx.io import read_structure |
| |
| structure, _ = read_structure("rna.cif") |
| pipeline = ofoldx.pipeline("design", model="oteam/grnade") |
| result = pipeline(structure, secondary_structure="((((....))))", num_candidates=4, temperature=0.2) |
| ``` |
|
|
| The dot-bracket string covers the selected RNA chain; use `instance_id` when the structure contains several RNA instances. |
| Each candidate contains its molecular target, design record, and sequence scores. |
|
|
| ### Downstream Use |
|
|
| #### Multi-Conformation Design |
|
|
| You can condition one sequence design on multiple aligned conformations of the same RNA: |
|
|
| ```python |
| import ofoldx |
| from ofoldx.io import read_structure |
| |
| open_structure, _ = read_structure("rna_open.cif") |
| closed_structure, _ = read_structure("rna_closed.cif") |
| pipeline = ofoldx.pipeline("design", model="oteam/grnade") |
| result = pipeline((open_structure, closed_structure), secondary_structure="((((....))))") |
| ``` |
|
|
| The conformations must contain the same RNA sequence. The first is the design target; later conformations supply |
| structural context. |
|
|
| ## Training Details |
|
|
| gRNAde is trained to recover RNA nucleotide identities from one or more backbone conformations. |
|
|
| ### Training Data |
|
|
| The gRNAde authors' [RNASolo dataset](https://huggingface.co/datasets/chaitjo/gRNAde_datasets) contains RNA structures |
| from the Protein Data Bank at 4 Å resolution or better, with a 31 October 2023 cutoff. |
|
|
| ### Training Procedure |
|
|
| gRNAde uses autoregressive RNA sequence recovery from structural context. The released label-smoothing value was `0.05`. |
|
|
| OFoldX provides [`GrnadeLoss`][ofoldx.models.grnade.GrnadeLoss] for training and fine-tuning. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{joshi2025grnade, |
| title={g{RNA}de: Geometric Deep Learning for 3D RNA inverse design}, |
| author={Joshi, Chaitanya K and Jamasb, Arian R and Vi{\~n}as, Ramon and |
| Harris, Charles and Mathis, Simon V and Morehead, Alex and |
| Anand, Rishabh and Li{\`o}, Pietro}, |
| booktitle={International Conference on Learning Representations}, |
| year={2025} |
| } |
| ``` |
|
|
| > [!NOTE] |
| > The artifacts distributed in this repository are part of the OFoldX project. |
| > If OFoldX supports your research, please cite the OFoldX project as follows: |
|
|
| ```bibtex |
| @software{chen2026ofoldx, |
| author = {Chen, Zhiyuan}, |
| title = {OFoldX}, |
| year = {2026}, |
| url = {https://github.com/OTeam-AI4S/OFoldX}, |
| } |
| ``` |
|
|
| ## Contact |
|
|
| Please use GitHub issues of [OFoldX](https://github.com/OTeam-AI4S/OFoldX/issues) for any questions or comments on the model implementation or model card. |
|
|
| Please contact the authors of the [gRNAde paper](https://arxiv.org/abs/2305.14749) for questions or comments on the paper/model. |
|
|
| ## License |
|
|
| The model weights, implementation, configuration, and documentation distributed by OFoldX are licensed under the |
| [GNU Affero General Public License](https://github.com/OTeam-AI4S/OFoldX/blob/main/license.md). |
|
|
| For additional terms and clarifications, please refer to our [License FAQ](https://github.com/OTeam-AI4S/OFoldX/blob/main/license-faq.md). |
|
|
| The upstream gRNAde source is MIT-licensed. |
|
|
| ```spdx |
| SPDX-License-Identifier: AGPL-3.0-or-later |
| ``` |
|
|
| [ofoldx.models.grnade.GrnadeLoss]: https://ofoldx.valtech.ai/models/grnade/#ofoldx.models.grnade.GrnadeLoss |
|
|
