Predicting the structure of proteins from amino acid sequences is a hard problem. Convolutional neural networks can learn to predict a map of distances between amino acid residues that can be turned into a three-dimensional structure. With a combination of approaches, including an evolutionary technique to find the best neural network architecture and a tool to find the atom coordinates in the folded structure, a pipeline for rapid prediction of three-dimensional protein structures is demonstrated.
- Wenzhi Mao
- Wenze Ding
- Haipeng Gong
