1. Accurate prediction of protein structures and interactions using a three-track neural network.
- Author
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Baek M, DiMaio F, Anishchenko I, Dauparas J, Ovchinnikov S, Lee GR, Wang J, Cong Q, Kinch LN, Schaeffer RD, Millán C, Park H, Adams C, Glassman CR, DeGiovanni A, Pereira JH, Rodrigues AV, van Dijk AA, Ebrecht AC, Opperman DJ, Sagmeister T, Buhlheller C, Pavkov-Keller T, Rathinaswamy MK, Dalwadi U, Yip CK, Burke JE, Garcia KC, Grishin NV, Adams PD, Read RJ, and Baker D
- Subjects
- ADAM Proteins chemistry, Amino Acid Sequence, Computer Simulation, Cryoelectron Microscopy, Crystallography, X-Ray, Databases, Protein, Membrane Proteins chemistry, Models, Molecular, Multiprotein Complexes chemistry, Neural Networks, Computer, Protein Subunits chemistry, Proteins physiology, Receptors, G-Protein-Coupled chemistry, Sphingosine N-Acyltransferase chemistry, Deep Learning, Protein Conformation, Protein Folding, Proteins chemistry
- 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 protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
- Published
- 2021
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