| --- |
| license: apache-2.0 |
| pretty_name: MORAD Targets |
| viewer: false |
| tags: |
| - rna |
| - rna-design |
| - inverse-folding |
| - structural-biology |
| - reinforcement-learning |
| size_categories: |
| - n<1K |
| --- |
| |
| # MORAD Targets |
|
|
| RNA 3D backbone targets used to train and evaluate |
| **MORAD: Reinforcement Learning with Multi-Objective Rewards for RNA Inverse Design**. |
|
|
| [Paper](https://arxiv.org/abs/2610.13305) · |
| [Project page](https://gabrile166.github.io/MORAD/) · |
| [Code](https://github.com/Gabrile166/MORAD) · |
| [Model](https://huggingface.co/MORAD-RNA/MORAD-RIDE) |
|
|
| ## Splits |
|
|
| | File | Targets | Length (nt) | Used for | |
| |---|:---:|:---:|---| |
| | `data/train.pt` | 527 | 27–258 (median 75) | MORAD training | |
| | `data/test.pt` | 153 | 15–186 (median 65) | evaluation | |
|
|
| The test set is built separately from the training set. It comprises 71 |
| [RNA3DB](https://github.com/marcellszi/rna3db) entries, drawn from RNA3DB |
| components that contain no training target, and 82 entries curated from the |
| [RCSB PDB](https://www.rcsb.org/). No test sequence exactly matches a training |
| sequence. When the native sequences are folded with RhoFold+, the median GDT-TS |
| is 0.6400 on the training set and 0.6014 on the test set. |
|
|
| ## Format |
|
|
| Each file is a `torch.save`d dictionary with a `targets` list. Every target holds |
|
|
| | Field | Content | |
| |---|---| |
| | `metadata` | `target_id`, native `sequence`, `length`, `structure_hash` and source identifiers | |
| | `ref_backbone_coords` | backbone coordinates (P, C4′, N1/N9), `[L, 3, 3]` | |
| | `ref_c4p_coords` | C4′ coordinates, `[L, 3]` | |
| | `mask_coords` | coordinate-validity mask, `[L]` | |
| | `raw_record` | backbone features consumed by RIDE and the C1′ trace | |
|
|
| ```python |
| import torch |
| |
| test = torch.load("data/test.pt", map_location="cpu", weights_only=False) |
| target = test["targets"][0] |
| print(target["metadata"]["target_id"], target["metadata"]["length"]) |
| ``` |
|
|
| ## Download |
|
|
| ```bash |
| huggingface-cli download MORAD-RNA/MORAD-Targets --repo-type dataset --local-dir MORAD-Targets |
| ``` |
|
|
| Inside the [code repository](https://github.com/Gabrile166/MORAD), |
| `bash scripts/download_assets.sh data` places the files where the configs expect |
| them. SHA-256 checksums are listed in `SHA256SUMS`. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{tang2026morad, |
| title = {{MORAD}: Reinforcement Learning with Multi-Objective Rewards for {RNA} Inverse Design}, |
| author = {Tang, Jixin and Guo, Ji and Zhao, Jun}, |
| year = {2026}, |
| eprint = {2610.13305}, |
| archivePrefix = {arXiv}, |
| primaryClass = {cs.LG}, |
| url = {https://arxiv.org/abs/2610.13305} |
| } |
| ``` |
|
|
