Ai for drug discovery

This course introduces Ph.D. students to the integration of traditional and AI methods in drug discovery. The course begins with practical training on the INDACO platform, covering UNIX essentials and cluster job management for efficient resource utilization. It then provides an overview of essential molecular modeling concepts and traditional drug design techniques, including the use platforms like Maestro/Schrodinger for Molecular Docking, MD simulations. And ligand binding free energy estimation. The final focus is on the application of Machine Learning (ML) and Deep Learning (DL) in the drug discovery, exploring their use in virtual screening, ADMET prediction, and the design of novel drug targets and molecules. The goal is to equip participants with the theoretical and practical skills to apply these computational and AI tools for developing bioactive molecules. The registration deadline is end of March but the course will take place in the second half of June.