Accurate prediction of protein structures and interactions using a three-track neural network.

ABSTRACT: DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo-electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate prote

SUBMITTER: Baek M 

PROVIDER: S-EPMC7612213 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature