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The official ProteinMPNN docker image.
Maintained by: https://gitee.com/openeuler/cloudnative.
Where to get help: https://gitee.com/openeuler/cloudnative, https://gitee.com/openeuler/community.
ProteinMPNN is a deep learning-based protein sequence design method. It generates protein sequences that fold into given backbone structures with high accuracy.
Learn more on https://github.com/dauparas/ProteinMPNN.
The tag of each proteinmpnn docker image is consist of the version of proteinmpnn and the version of basic image. The details are as follows
| Tag | Currently | Architectures |
|---|---|---|
| https://gitee.com/openeuler/openeuler-docker-images/blob/master/HPC/proteinmpnn/1.0.1/24.03-lts-sp4/Dockerfile | ProteinMPNN 1.0.1 on openEuler 24.03-LTS-SP4 | amd64, arm64 |
| https://gitee.com/openeuler/openeuler-docker-images/blob/master/HPC/proteinmpnn/1.0.1/24.03-lts-sp3/Dockerfile | ProteinMPNN 1.0.1 on openEuler 24.03-LTS-SP3 | amd64, arm64 |
In this usage, users can select the corresponding {Tag} and container startup options based on their requirements.
Pull the openeuler/proteinmpnn image from docker
bashdocker pull openeuler/proteinmpnn:{Tag}
Start a ProteinMPNN instance
bashdocker run -it --rm openeuler/proteinmpnn:{Tag} bash
Run a simple example
bash# Inside the container cd /opt/ProteinMPNN # Step 1: Parse PDB files to jsonl format python3 helper_scripts/parse_multiple_chains.py \ --input_path inputs/PDB_monomers/pdbs/ \ --output_path parsed_pdbs.jsonl # Step 2: Run protein sequence design python3 protein_mpnn_run.py \ --jsonl_path parsed_pdbs.jsonl \ --out_folder outputs/ \ --num_seq_per_target 2 \ --sampling_temp "0.1"
Design with custom PDB files
bash# Mount local directory and run docker run -it --rm -v /path/to/pdbs:/pdbs openeuler/proteinmpnn:{Tag} bash # Inside the container, parse and design cd /opt/ProteinMPNN python3 helper_scripts/parse_multiple_chains.py \ --input_path /pdbs/ \ --output_path /pdbs/parsed_pdbs.jsonl python3 protein_mpnn_run.py \ --jsonl_path /pdbs/parsed_pdbs.jsonl \ --out_folder /pdbs/outputs/ \ --num_seq_per_target 10
If you have any questions or want to use some special features, please submit an issue or a pull request on https://gitee.com/openeuler/openeuler-docker-images.
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