cdna-display-proteolysis-pipeline

Description

• This repo includes only scripts related to a manuscript titled "Mega-scale experimental analysis of protein folding stability in biology and protein design"
• URL: https://www.biorxiv.org/content/10.1101/2022.12.06.519132v3
• You can find the following all tables required for the pipelines above here
• URL: https://doi.org/10.5281/zenodo.7844779

Environment and Installation

We tested the following pipeline using Python 3.8 or 3.9 on Ubuntu Ubuntu 16.04.7 LTS and Red Hat Enterprise Linux Server 7.9 (Maipo). GPU is not essential to run the pipeline but highly recommended to accelerate the process. It usually takes ~30min to install all the requirements using Conda.

To install the requirements, you can use the env file:

conda env create -f env/protease-pipeline.yml
conda activate protease-pipeline

Scripts on github

env (.yml file for requirement installation)

protease-pipeline.yml

Pipeline_K50_dG (a main pipeline to generate K50/dG [folding stability] from NGS data)

STEP1_module.ipynb
STEP1_run.ipynb
STEP2_run.ipynb
STEP3_run.ipynb
STEP4_module.ipynb
STEP4_run.ipynb
STEP5_module.ipynb
STEP5_run.ipynb
Raw_NGS_counts_overlapped_seqs_STEP1_lib1_lib2.csv
Raw_NGS_counts_overlapped_seqs_STEP1_lib2_lib3.csv
Raw_NGS_counts_overlapped_seqs_STEP1_lib1_lib4.csv
Raw_NGS_counts_overlapped_seqs_STEP1_lib2_lib4.csv
Raw_NGS_counts_overlapped_seqs_STEP1_lib3_lib4.csv
STEP1_out_protease_concentration_trypsin
STEP1_out_protease_concentration_chymotrypsin

Using GPU, it will take ~30min for STEP1, ~1 hr for STEP2, ~10 hrs for STEP3, ~30min for STEP4, and ~1 hr for STEP5.

Pipeline_figure_model

Burial_side_chain_contact_Fig3_Fig6.ipynb
Additive_model_Fig4.ipynb
Classification_model_Fig5.ipynb
Data_quality_filtering_script.ipynb

Pipeline_qPCR_data: a pipeline to analyze qPCR data (related to Fig. S1)

Raw_qPCR_data_FigS1.csv
Process_qPCR_data.ipynb

Files on Zenodo

Raw_NGS_count_tables.zip

NGS_count_lib1.csv
NGS_count_lib2.csv
NGS_count_lib3.csv
NGS_count_lib4.csv

K50_dG_tables.zip

K50_dG_lib1.csv
K50_dG_lib2.csv
K50_dG_lib3.csv
K50_dG_lib4.csv

Processed_K50_dG_datasets.zip

K50_dG_Dataset1_Dataset2.csv
K50_Dataset3.csv
Single_DMS_list.csv
Double_DMS_list.csv 
Triple_DMS_list.csv
Heat_maps_single_DMS.pdf
Heat_maps_double_DMS.pdf

Data_tables_for_figs.zip

dG_extdG_data_Fig1.csv
dG_site_feature_Fig3.csv
dG_for_double_mutants_Fig4.csv
dG_non_redundant_natural_Fig5.csv
dG_GEMME_non_redundant_natural_Fig6.csv

Pipeline_qPCR_data.zip

Raw_qPCR_data_FigS1.csv
Process_qPCR_data.ipynb

Pipeline_K50_dG.zip

STEP1_module.ipynb
STEP1_run.ipynb
STEP2_run.ipynb
STEP3_run.ipynb
STEP4_module.ipynb
STEP4_run.ipynb
STEP5_module.ipynb
STEP5_run.ipynb
Raw_NGS_counts_overlapped_seqs_STEP1_lib1_lib2.csv
Raw_NGS_counts_overlapped_seqs_STEP1_lib2_lib3.csv
Raw_NGS_counts_overlapped_seqs_STEP1_lib1_lib4.csv
Raw_NGS_counts_overlapped_seqs_STEP1_lib2_lib4.csv
Raw_NGS_counts_overlapped_seqs_STEP1_lib3_lib4.csv
K50_scrambles_for_STEP3.csv
STEP1_out_protease_concentration_trypsin
STEP1_out_protease_concentration_chymotrypsin
STEP3_unfolded_model_params

Pipeline_figure_model.zip

Burial_side_chain_contact_Fig3_Fig6.ipynb
Additive_model_Fig4.ipynb
Classification_model_Fig5.ipynb

AlphaFold_model_PDBs.zip

Blueprints_for_EEHH.zip

eehh_EA_GBB_AGBB.bp
eehh_GG_GBB_AGBB.bp
eehh_XX_XXX_XXXX.bp