Muhamed Amin

This study uses machine learning to screen FDA-approved compounds for KRAS G12C and G12D inhibition, identifying potential drug candidates for further experimental validation.

This paper develops a hybrid deep learning model combining graph neural networks and molecular descriptors to predict drug targets with high accuracy and interpretability.

This study calculates polarizability tensors for drug-like molecules and uses machine learning to predict IC50s, showing induced polarizability's importance in binding.