Drug Discovery Project

This project aims to explore the drug discovery field employing machine learning techniques. The chosen target of the project is BRAF (B-Raf proto-oncogene), a serine/threonine protein kinase that plays a critical role in the MAPK signalling pathway and that is involved in various cancers, such as melanomas and colorectal cancers.

Inhibition of BRAF represents a strategy to disrupt the hyperactive MAPK signaling cascade and block the growth of cancer cells presenting BRAF mutations. In fact, several BRAF inhibitors have been investigated in preclinical and clinical settings, showcasing promising anti-tumor activities.

For this reason, the application of machine learning techniques, such as regression models, for BRAF-targeted drug discovery poses an interesting challenge. Specifically, regression models will be employed to predict the bioactivity of different molecules against BRAF. The utilization of PubChem fingerprints and IC50 values will serve as the basis for developing the predictive model.

The code for this project can be found here.