PPI binding affinity Prediction through deep learning

Published: 19 April 2023| Version 1 | DOI: 10.17632/vsbd5m9f93.1
Pallavi M Shanthappa


A prediction tool for predicting the binding affinities and dissociation constants of protein complexes using a machine learning and deep learning method based on the protein sequence is developed. The steps to run the tool is as follows. The first command set FLASK_APP=app.py sets the environment variable FLASK_APP to app.py, which is the name of the Flask application file. The second command set FLASK_ENV=development sets the environment variable FLASK_ENV to development, which indicates that Flask should run in development mode. The third command flask run -p 3121 explain is running the Flask application by executing the flask run command with the additional argument -p 3121, which specifies that the application should be run on port 3121.the Flask application is running on the local development server at the address The message also indicates that the server is set to automatically restart when changes are made to the code (* Restarting with stat).



Amrita Vishwa Vidyapeetham


Binding Protein, Protein-Protein Interaction, Bond Dissociation Energy, Molecular Affinity