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CHE1147-Project

Project for the course Data Mining in Engineering CHE1147 in the University of Toronto

Affinity Prediction of Chemical Inhibitors of Cathepsin S, a Therapeutic Target in Cancer Treatment.

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Cathepsin_Prediction

Implemented ML models (LR, SVM, K-Nearest Neighbours, Random Forest) in Python to predict binding affinities of chemical inhibitors of Cathepsin S enzyme from their 2D structural data (SMILES). A max model accuracy of 46% concluded that 2D structural data is insufficient to predict the complex kinetics of binding.

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