Understanding protein interactions is key to innumerable fields — including, notably, drug design. Now, researchers from the Georgia Institute of Technology have developed a machine learning tool to predict interactions between multiple proteins, paving the way for easier identification of drug targets for antibiotics and therapeutics. The open-source, publicly available tool is called AF2Complex — short for AlphaFold 2 Complex, since the tool is built on top of London-based artificial intelligence lab DeepMind’s AlphaFold 2 protein structure prediction program. Jeffrey Skolnick, Regents' Professor and Mary and Maisie Gibson Chair in the School of Biological Sciences, and Mu Gao, senior research scientist, are co-authors of the study.
Summit Supercomputer, Deep Learning Power Protein Interaction Prediction