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Structure-based prediction of cross-reactive peptides

Here, we provide documentation and code for the de novo prediction of cross-reactive peptides using the 10LH:PHOX2B/HLA-A*24:02 complex as an example.

For a detailed description of the implementation, please refer to our manuscript: Sun, Florio, & Gupta et al., Structural principles of peptide-centric Chimeric Antigen Receptor recognition guide therapeutic expansion. bioRxiv doi.org/10.1101/2023.05.24.542108

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System requirements:

  • MacOS/Linux (tested on MacOS 12.6.3)
  • Rosetta (tested on 2020.08)
  • Anaconda (tested on 4.11.0)
    • Python 3.8+ (tested on 3.8.15)
    • platformdirs
    • PyMOL
    • tqdm

Installation:

  1. Create a conda environment using the provided YAML file using the following command: conda env create -f environment.yml This step takes roughly 5 minutes on a normal desktop computer, depending on internet speed.
  2. Obtain Rosetta via https://www.rosettacommons.org/software/license-and-download
  3. (Optional) Download the latest version of HLA3DB via https://hla3db.research.chop.edu/ and directly replace the MHC_pdbs folder. Note that this repository contains a static version of HLA3DB downloaded on April 28th, 2023.

Usage

  1. Activate the conda environment: conda activate pc_car
  2. Run the prediction: python predict_cr_peptides.py. The script takes ~40 minutes to run on a normal desktop computer.

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