As discussed before, AlphaFold does not automatically generate all visual outputs that are required for the interpretation of its predictions, but it stores information in python-specific .pkl files. Therefore, we supply a python script to do so, after prediction has finished.
In this exercise, you will generate the images from either your own AlphaFold outputs, or from the outputs for the SARSCoV1-VHH.72 protein complex. You can download them here. Upload this file to your $VSC_DATA/alphafold/runs/ directory.
Next, download the python script here.
To run the visualization, take the following steps:
module load Python/3.8.6-GCCcore-10.2.0 module load matplotlib/3.3.3-foss-2020b Important: for AlphaFold version 2.3.1 and later: this script has extra dependencies. This page will be updated, but for now you can load the following modules instead: module load AlphaFold/2.3.1-foss-2022a module load matplotlib/3.5.2-foss-2022a
python visualize_alphafold_results.py --input_dir <input_directory> --output_dir <output_directory> --name <prefix>
python visualize_alphafold_results.py --input_dir runs/RBD/RBD --output_dir . --name RBD
After this, two .jpg files should have been created in the output directory.
These steps and extra information can also be found at https://elearning.vib.be/courses/alphafold/lessons/alphafold-on-the-hpc/topic/alphafold-outputs/.