solublempnn-noise030

OFoldX pipeline artifact for biomolecular design generation, using the proteinmpnn architecture.

Disclaimer

This model card was generated by the OFoldX team for an OFoldX pipeline artifact. The upstream model authors did not write this card unless explicitly stated otherwise.

OFoldX is pre-alpha research software. Check the source checkpoint, upstream release, and local validation before using the artifact for scientific or operational decisions.

Model Details

ProteinMPNN sequence-design model for protein backbones, including soluble and membrane variants.

Converted SolubleMPNN sequence-design checkpoint for soluble protein backbones.

Model Provenance

• Upstream Project: SolubleMPNN
• Source Release: https://github.com/dauparas/LigandMPNN
• Primary Paper: Computational design of soluble and functional membrane protein analogues
• Upstream License: MIT for upstream ProteinMPNN and LigandMPNN code/model parameters

Model Specification

Field	Value
Repository	oteam/solublempnn-noise030
Artifact Kind	pipeline
Task	design_generation
Architecture	proteinmpnn
Entrypoint	ofoldx.pipelines.design.DesignPipeline

Checkpoint metadata: k_neighbors=48; the noiseXXX suffix identifies the training-noise variant.

Links

• Hub repository: oteam/solublempnn-noise030
• Upstream paper: Computational design of soluble and functional membrane protein analogues
• Upstream repository: SolubleMPNN
• Source checkpoint release: https://github.com/dauparas/LigandMPNN
• Code: ofoldx/pipelines/design.py
• Project repository: https://github.com/OTeam-AI4S/OFoldX
• Issues: https://github.com/OTeam-AI4S/OFoldX/issues

Usage

The artifact depends on the ofoldx library. Install it with pip:

pip install ofoldx

Pipeline Usage

Load the artifact from oteam/solublempnn-noise030 with the OFoldX task pipeline. Use AutoModel or AutoProcessor only when you need lower-level control:

from ofoldx.pipelines import Pipeline

pipeline = Pipeline.from_pretrained("oteam/solublempnn-noise030")

When a matching processor is available, load it with AutoProcessor.from_pretrained(...) and pass the processed batch to the model.

Interface

• Task: design_generation
• Artifact kind: pipeline
• Architecture: proteinmpnn
• Runtime files: manifest.json, config.json, and model.safetensors when present

Training Details

OFoldX did not train these weights. This repository contains a converted checkpoint and OFoldX runtime metadata for loading it.

Training Data

The SolubleMPNN work trains like ProteinMPNN on PDB assemblies as of 2021-08-02, filtered to X-ray/cryo-EM structures better than 3.5 A and fewer than 10,000 residues, while excluding annotated transmembrane PDB entries. OFoldX does not redistribute the training set.

Training Procedure

Upstream SolubleMPNN follows ProteinMPNN-style fixed-backbone inverse-folding training with 48-neighbor noisy-backbone checkpoint variants. OFoldX converts released SolubleMPNN checkpoints into model.safetensors; it does not run SolubleMPNN training.

Evaluation

OFoldX conversion reports and contract tests validate artifact structure and checkpoint loading. Task-level scientific evaluation should be checked against the corresponding upstream model release or paper.

Limitations

• This artifact is distributed for research use.
• Inputs must match the model-specific processor and expected biomolecular representation.
• OFoldX is pre-alpha, so APIs and artifact metadata may still change before a stable release.

Citation

Please cite the upstream SolubleMPNN work for the source checkpoint. If OFoldX supports your work, please also cite or link the OFoldX project repository.

@article{solublempnn2024membrane,
  title = {Computational design of soluble and functional membrane protein analogues},
  journal = {Nature},
  year = {2024},
  doi = {10.1038/s41586-024-07601-y}
}

Contact

Please use OFoldX GitHub issues for questions or comments about this model card.

License

The Hub license metadata, when present, reflects the source checkpoint or upstream project license. The OFoldX project license is not yet finalized. The source checkpoint is associated with the upstream license noted above: MIT for upstream ProteinMPNN and LigandMPNN code/model parameters. Review both OFoldX and upstream terms before redistribution or production use.