Protein-Ligand Binding Affinity Prediction using ML

This repository is maintained for the documentation and coding of the MSc project in Bioinformatics Lab @ Uni-Freiburg. Please read the file [repo]/report/report.pdf to get an idea of the project. All references have been quoted to the best of my knowledge. If any discrepencies are found, please report using "Reporting Issues" option.

Setup

• Please clone the repository. Let this folder be repo
• Go inside the repo folder. cd repo
• Create the required conda environment using the exported conda environment. conda env create -f conda_environment/environment.yml If the environment is already created, then update it using the command conda env update --file conda_environment/environment.yml --prune
• This creates a conda environment called msc-project. Activate the conda environment.
  conda activate msc-project

Running the model.

• Go to the folder model. cd model
• Run any model of your choice. At this time the Random Forest Regressor gives the best result.
  python random_forest_regresser.py [Execution ID]
  The Execution ID is optional. Use the same number to reproduce your results.
• The above should create 2 plots plotting predicted y value vs expected y value.
  accuracy_validate.png - Shows how good the model fits on our validation data.
  accuracy_train.png - Shows how good the model fits on our training data.

Reporting Issues / Requesting Features

• Please use Report issue or request feature for this purpose.

Diagrams curtesy

https://app.diagrams.net/

MIT License

Copyright (c) 2021 Abdus Salam Khazi