Prediction Flavoprotein EM

This repository contains the data and script used for the manuscript "Machine learning for efficient prediction of protein redox potential: the flavoproteins case" submitted to the Journal of Chemical Information and Modeling.

Flavoprotein Datset

The Flavoproteins Dataset is available at data/dataset.xlsx. For each flavoprotein used in this work we report:

- PDB-ID 
- Organism and Family
- Classification and Cofactor-type
- Technique resolution
- Em, E1, E2
- Reference of the experimental work

REPO ORGANIZATION

All the scripts used to reproduce the work are here reported:

• Em predict.py: for the ML pipeline used to test the performance of the various ML models;
• Features Calculator.py: features computation of the flavoprotein PDB files reported in data/dataset.xlsx;
• ML_models.py: contains all the machine learning models hparams;
• SHAP_analysis.ipynb: notebook for SHAP analysis;
• HeatMap.py: script to create the table of performance of the various estimator for different combinations of radii r1 and r2;
• env.yml: yaml file to create a mamba env from file.

ENVIROMENT

We suggest to create a mamba env to run the script as follow:

• install mamba
• git clone https://github.com/CompBtBs/Prediction_Flavoprotein_EM.git
• cd Prediction_Flavoprotein_EM
• mamba env create -f env.yml
• install PyBioMed using pip