New machine-learning algorithms may revolutionize drug discovery -- and our understanding of life

A new set of machine-learning algorithms can generate 3D structures of complex nanoscale protein molecules like this complex proteasome map refined to 2.8 Angstroms (.28 nanometer) in 70 min with 49,954 particle images (credit: Structura Biotechnology Inc.) A new set of machine-learning algorithms developed by researchers at the University of Toronto Scarborough can generate 3D structures of nanoscale protein molecules that could not be achieved in the past. The algorithms may revolutionize the development of new drug therapies for a range of diseases and may even lead to better understand how life works at the atomic level, the researchers say. Drugs work by binding to a specific protein molecule and changing the protein's 3D shape, which alters the way the drug works once inside the body. The ideal drug is designed in a shape that will only bind to a specific protein or group of proteins that are involved in a disease, while eliminating side effects that occur when drugs bind to other proteins in the body.