A deep learning model rapidly predicts the 3D shapes of drug-like molecules

In their quest to discover effective new medicines, scientists search for drug-like molecules that can attach to disease-causing proteins and change their functionality. It is crucial that they know the 3D shape of a molecule to understand how it will attach to specific surfaces of the protein. But a single molecule can fold in thousands of different ways, so solving that puzzle experimentally is a time consuming and expensive process akin to searching for a needle in a molecular haystack. MIT researchers are using machine learning to streamline this complex task. They have created a deep learning model that predicts the 3D shapes of a molecule solely based on a graph in 2D of its molecular structure.