New algorithm for functional protein design outperforms traditional methods

Researchers from the University of Science and Technology of China (USTC), led by Prof. Liu Qi, in collaboration with Harvard Medical School's Marinka Zitnik lab, have developed a novel deep generative algorithm, PocketGen. This algorithm, based on graph representation learning and protein language models, efficiently generates protein pocket sequences and spatial structures for binding small molecules. The study was published in Nature Machine Intelligence.