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 SARSCoV2-VHH-E 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 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>
Note that output_dir and name are optional. By default, the resulting jpgs are placed in the same directory as the input. For example:
python visualize_alphafold_results.py --input_dir runs/RBD/RBD
After this, two .png files should have been created in that 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/.