https://github.com/seqeralabs/nf-chai
POC Nextflow pipeline to run the Chai-1, SOTA model for biomolecular structure prediction
https://github.com/seqeralabs/nf-chai
nextflow pipeline protein-structure structure-prediction
Last synced: 10 months ago
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POC Nextflow pipeline to run the Chai-1, SOTA model for biomolecular structure prediction
- Host: GitHub
- URL: https://github.com/seqeralabs/nf-chai
- Owner: seqeralabs
- License: mpl-2.0
- Created: 2024-11-20T10:11:45.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-16T18:26:57.000Z (over 1 year ago)
- Last Synced: 2025-08-10T05:59:37.205Z (10 months ago)
- Topics: nextflow, pipeline, protein-structure, structure-prediction
- Language: Nextflow
- Homepage:
- Size: 12.6 MB
- Stars: 11
- Watchers: 5
- Forks: 5
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Citation: CITATIONS.md
Awesome Lists containing this project
README
# nf-chai
[](https://github.com/seqeralabs/nf-chai/actions/workflows/ci.yml)
[](https://github.com/seqeralabs/nf-chai/actions/workflows/linting.yml)
[](https://www.nf-test.com)
[](https://www.nextflow.io/)
[](https://www.docker.com/)
[](https://sylabs.io/docs/)
[](https://cloud.seqera.io/launch?pipeline=https://github.com/seqeralabs/nf-chai)
## POC implementation of Chai-1 in Nextflow
## Introduction
**nf-chai** is a simple, proof-of-concept bioinformatics pipeline for running the [Chai-1](https://github.com/chaidiscovery/chai-lab) protein prediction algorithm on an input set of protein sequences in FASTA format. The pipeline has been written in Nextflow to generate results for downstream analysis in a reproducible, scalable and portable way.
## Usage
> [!NOTE]
> If you are new to Nextflow, please refer to [this page](https://nf-co.re/docs/usage/installation) on how to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) with `-profile test` before running the workflow on actual data.
First, prepare a FASTA file with entities supported by Chai-1 in the format highlighted below. You can also provide a directory with multiple FASTA files by specifying the `--input` parameter with a directory path like this: `--input "/path/to/fasta_files/*.fasta|*.fa"`.
`multiple_entities.fa`:
```txt
>protein|name=example-of-long-protein
AGSHSMRYFSTSVSRPGRGEPRFIAVGYVDDTQFVRFDSDAASPRGEPRAPWVEQEGPEYWDRETQKYKRQAQTDRVSLRNLRGYYNQSEAGSHTLQWMFGCDLGPDGRLLRGYDQSAYDGKDYIALNEDLRSWTAADTAAQITQRKWEAAREAEQRRAYLEGTCVEWLRRYLENGKETLQRAEHPKTHVTHHPVSDHEATLRCWALGFYPAEITLTWQWDGEDQTQDTELVETRPAGDGTFQKWAAVVVPSGEEQRYTCHVQHEGLPEPLTLRWEP
>protein|name=example-of-short-protein
AIQRTPKIQVYSRHPAENGKSNFLNCYVSGFHPSDIEVDLLKNGERIEKVEHSDLSFSKDWSFYLLYYTEFTPTEKDEYACRVNHVTLSQPKIVKWDRDM
>protein|name=example-peptide
GAAL
>ligand|name=example-ligand-as-smiles
CCCCCCCCCCCCCC(=O)O
```
Run the pipeline using CPUs with the command below:
```bash
nextflow run seqeralabs/nf-chai \
--input multiple_entities.fa \
--outdir \
-profile
```
Run the pipeline using GPUs with the command below:
```bash
nextflow run seqeralabs/nf-chai \
--input multiple_entities.fa \
--outdir \
--use_gpus \
-profile
```
Set the `--weights_dir` parameter to a location with the pre-downloaded weights required by Chai-1 to avoid having to download them every time you run the pipeline.
To further improve prediction performance using pre-built multiple sequence alignments (MSA) with evolutionary information, set the `--msa_dir` parameter to a location with [`*.aligned.pqt`](https://github.com/chaidiscovery/chai-lab/tree/main/examples/msas#adding-msa-evolutionary-information) format as required by Chai-1.
## Credits
nf-chai was originally written by the Seqera Team.
## Contributions and Support
If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).
## Citations
An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
This pipeline uses code and infrastructure developed and maintained by the [nf-core](https://nf-co.re) community, reused here under the [MIT license](https://github.com/nf-core/tools/blob/main/LICENSE).
> **The nf-core framework for community-curated bioinformatics pipelines.**
>
> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
>
> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).