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bindflow

https://github.com/australian-structural-biology-computing/bindflow

Science Score: 57.0%

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Repository

Basic Info
  • Host: GitHub
  • Owner: Australian-Structural-Biology-Computing
  • License: mit
  • Language: Nextflow
  • Default Branch: main
  • Size: 353 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 1
  • Open Issues: 2
  • Releases: 0
Created about 1 year ago · Last pushed 7 months ago
Metadata Files
Readme Changelog Contributing License Citation

README.md

Australian-Structural-Biology-Computing/bindflow

GitHub Actions CI Status GitHub Actions Linting StatusCite with Zenodo nf-test

Nextflow run with conda run with docker run with singularity Launch on Seqera Platform

Introduction

Australian-Structural-Biology-Computing/bindflow is a bioinformatics pipeline that generates protein binders for user-defined hotspot residues on a target protein structure. The pipeline will be executed until a user-defined number of designs pass the in-silico quality control criteria.

bindflow workflow

Bindflow is a wrapper around the BindCraft tool to allow convenient execution on HPC infrastructure. BindCraft includes 4 core binder design modules within a single tool. 1. Structure proposal (AlphaFold2 multimer hallucination) 2. Sequence design (SolubleMPNN) 3. Structure prediction (AlphaFold2) 4. Post-design quality control (PyRosetta)

[!WARNING] Post-design QC filtering is conducted with PyRosetta. Users must agree to the PyRosetta license terms.

Usage

[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

csv id,binder_name,starting_pdb,chains,target_hotspot_residues,min_length,max_length,number_of_final_designs,settings_advanced,settings_filters demo,PDL1,PDL1.pdb,A,"56",65,150,10,default_4stage_multimer.json,default_filters.json

Each row represents a single design instance. Detailed documentation describing job parameters can be found in the BindCraft documentation. Briefly: - id is a unique job identifier - binder_name is an identifier for the protein target. - starting_pdb contains the target structure in PDB format. - chains defines the target chains in the startingpdb. - **targethotspotresidues** defines the residue indices of the targetpdb which will be targeted by the design process. - min_length defines the minimum length of the designed binder. - max_length defines the maximum length of the designed binder. - numberoffinal_designs defines the number of binders required to pass QC criteria before the job is complete. - settings_advanced defines advanced BindCraft settings (JSON format). - settings_filters defines advanced BindCraft filter settings (JSON format).

Workloads can be distributed over multiple GPUs by setting the --batches command line argument to split the number of final designs in to separate batches.

Now, you can run the pipeline using:

bash nextflow run Australian-Structural-Biology-Computing/bindflow \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --outdir <OUTDIR> --batches 1

[!WARNING] Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

Credits

Australian-Structural-Biology-Computing/bindflow was originally written by Ziad Al-Bkhetan and Thomas Litfin.

We thank the following people for their extensive assistance in the development of this pipeline:

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT 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.

Owner

  • Name: Australian Structural Biology Computing
  • Login: Australian-Structural-Biology-Computing
  • Kind: organization

Citation (CITATIONS.md) 

# Australian-Structural-Biology-Computing/bindflow: Citations

## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/)

> Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031.

## [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/)

> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311.

## Pipeline tools

- [BindCraft](https://www.biorxiv.org/content/10.1101/2024.09.30.615802v3)

  > Pacesa M, Nickel L, Schellhaas C, Schmidt J, Pyatova E, Kissling L, Barendse P, Choudhury J, Kapoor S, Alcaraz-Serna A, Cho Y. BindCraft: one-shot design of functional protein binders. bioRxiv. 2024 Oct 1:2024-09.

- [AlphaFold2](https://www.nature.com/articles/s41586-021-03819-2)

  > Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, Tunyasuvunakool K, Bates R, Žídek A, Potapenko A, Bridgland A. Highly accurate protein structure prediction with AlphaFold. nature. 2021 Aug;596(7873):583-9.

- [AlphaFold Multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v2)

  > Evans R, O’Neill M, Pritzel A, Antropova N, Senior A, Green T, Žídek A, Bates R, Blackwell S, Yim J, Ronneberger O. Protein complex prediction with AlphaFold-Multimer. biorxiv. 2021 Oct 4:2021-10.

- [SolubleMPNN](https://www.nature.com/articles/s41586-024-07601-y)

  > Goverde CA, Pacesa M, Goldbach N, Dornfeld LJ, Balbi PE, Georgeon S, Rosset S, Kapoor S, Choudhury J, Dauparas J, Schellhaas C. Computational design of soluble and functional membrane protein analogues. Nature. 2024 Jul 11;631(8020):449-58.

- [PyRosetta](https://academic.oup.com/bioinformatics/article/26/5/689/212442)

  > S. Chaudhury, S. Lyskov & J. J. Gray, "PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta," Bioinformatics, 26(5), 689-691 (2010)

- [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/)

  > Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924.

## Software packaging/containerisation tools

- [Anaconda](https://anaconda.com)

  > Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.

- [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/)

  > Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.

- [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/)

  > da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671.

- [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241)

  > Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. doi: 10.5555/2600239.2600241.

- [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/)

  > Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675.

GitHub Events

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Last Year
  • Issues event: 2
  • Issue comment event: 4
  • Member event: 1
  • Push event: 21
  • Pull request event: 7
  • Fork event: 1
  • Create event: 3

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