New deep-learning approach predicts protein structure from amino acid sequence

Composed of long chains of amino acids, proteins perform these myriad tasks by folding themselves into precise 3D structures that govern how they interact with other molecules. Because a protein's shape determines its function and the extent of its dysfunction in disease, efforts to illuminate protein structures are central to all of molecular biology -- and in particular, therapeutic science and the development of lifesaving and life-altering medicines. In recent years, computational methods have made significant strides in predicting how proteins fold based on knowledge of their amino acid sequence. If fully realized, these methods have the potential to transform virtually all facets of biomedical research. Current approaches, however, are limited in the scale and scope of the proteins that can be determined.