Considering AI in drug discovery, which algorithm is generally employed in predicting interaction between drug and target?

In drug discovery, one of the commonly employed AI techniques for predicting interactions between drugs and their target proteins is Molecular Docking. Molecular docking involves simulating the binding of a small molecule (the drug) to a target protein, and it's a crucial step in drug development. Other algorithms like Random Forest, Linear Regression, and Support Vector Machines may be used for different aspects of drug discovery, but they are not specifically used for predicting drug-target interactions.