A501-3DAC-AlphaFold

Requirements

The required dependencies for the analysis procedures are PyMOL, matplotlib, numpy, pandas and seaborn, you can install the requirements by

# if you have conda environment
conda create -n A501_3DAC python=3.8
conda install pymol matplotlib numpy pandas seaborn biopython scipy

You might also need jupyter notebook to run notebook files.

1 ParaFold

We used a parallelized version of AlphaFold which called ParaFold for high-throughput structure prediction. The installation and usage of ParaFold is available from ParaFold. Here we provide scripts for submitting multiple structure prediction jobs using ParaFold.

2 Result analysis

We used our python scripts (in jupyter notebook format) to do structural analysis (hydrogen bond, salt bridge, disulfur bind, secondary structure, SASA, etc.). In this repo, we provided a demo to run the notebook using 20 example AlphaFold structure.

Detail guide can be found in notebook.

3 Structure sequence alignment

We conduct structure and sequence alignment for all predicted structures from 7 enzymes in 24 species.

First, you should download the prediction results from https://zenodo.org/record/6387901#.Yu15YHYzaUk

Then, the jupyter notebook 3_structure_sequence_alignment/result_analysis.ipynb will help you calculate the sequence identity and structure RMSD, results saved in ./3_structure_sequence_alignment/result folder

Finally 3_structure_sequence_alignment/figure.ipynb is used for plot figures in our context.

4 Proteome-wide analysis

The proteome-wide structural feature data in csv format and analysis code is in ./4_proteome_wide_analysis

5 Figure Scripts

Scripts for figures in main text and supplementary file is available at ./5_figures