Drug editing for prediction of protein-drug binding affinity

Identifier:  TFG:9591

Handle: https://hdl.handle.net/20.500.11797/TFG9591

Authors:  Lacambra Chen, Joel

Abstract:
This Bachelor's Thesis presents a Python tool that allows users to visualize and edit molecules, as well as predict their affinity for the main protease of SARS-CoV-2 using graphical neural network models (GCN, GIN, and GINE). The interface, developed with PySide6 and RDKit, is interactive, lightweight, and customizable. Machine learning techniques with PyTorch Geometric were used to train and evaluate the models.