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

Minkyung Baek | Zendy; Frank DiMaio | Zendy; Ivan Anishchenko | Zendy; Justas Dauparas | Zendy; Sergey Ovchinnikov | Zendy; Gyu Rie Lee | Zendy; Jue Wang | Zendy; Qian Cong | Zendy; Lisa N. Kinch | Zendy; R. Dustin Schaeffer | Zendy; Claudia Millán | Zendy; Hahnbeom Park | Zendy; Carson Adams | Zendy; Caleb R. Glassman | Zendy; Andy DeGiovanni | Zendy; J.H. Pereira | Zendy; Andria V. Rodrigues | Zendy; Alberdina A. van Dijk | Zendy; Ana C. Ebrecht | Zendy; Diederik J. Opperman | Zendy; Theo Sagmeister | Zendy; Christoph Buhlheller | Zendy; Tea PavkovKeller | Zendy; Manoj Kumar Rathinaswamy | Zendy; Udit Dalwadi | Zendy; Calvin K. Yip | Zendy; John E. Burke | Zendy; K. Christopher García | Zendy; Nick V. Grishin | Zendy; Paul D. Adams | Zendy; Randy J. Read | Zendy; David Baker | Zendy

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

Author(s) -

Minkyung Baek,

Frank DiMaio,

Ivan Anishchenko,

Justas Dauparas,

Sergey Ovchinnikov,

Gyu Rie Lee,

Jue Wang,

Qian Cong,

Lisa N. Kinch,

R. Dustin Schaeffer,

Claudia Millán,

Hahnbeom Park,

Carson Adams,

Caleb R. Glassman,

Andy DeGiovanni,

J.H. Pereira,

Andria V. Rodrigues,

Alberdina A. van Dijk,

Ana C. Ebrecht,

Diederik J. Opperman,

Theo Sagmeister,

Christoph Buhlheller,

Tea PavkovKeller,

Manoj Kumar Rathinaswamy,

Udit Dalwadi,

Calvin K. Yip,

John E. Burke,

K. Christopher García,

Nick V. Grishin,

Paul D. Adams,

Randy J. Read,

David Baker

Publication year - 2021

Publication title -

science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 12.556

H-Index - 1186

eISSN - 1095-9203

pISSN - 0036-8075

DOI - 10.1126/science.abj8754

Subject(s) - casp , protein structure prediction , artificial neural network , computer science , folding (dsp implementation) , artificial intelligence , sequence (biology) , protein folding , deep learning , protein structure , computational biology , machine learning , chemistry , biology , engineering , biochemistry , electrical engineering

Deep learning takes on protein folding In 1972, Anfinsen won a Nobel prize for demonstrating a connection between a protein’s amino acid sequence and its three-dimensional structure. Since 1994, scientists have competed in the biannual Critical Assessment of Structure Prediction (CASP) protein-folding challenge. Deep learning methods took center stage at CASP14, with DeepMind’s Alphafold2 achieving remarkable accuracy. Baeket al . explored network architectures based on the DeepMind framework. They used a three-track network to process sequence, distance, and coordinate information simultaneously and achieved accuracies approaching those of DeepMind. The method, RoseTTA fold, can solve challenging x-ray crystallography and cryo–electron microscopy modeling problems and generate accurate models of protein-protein complexes. —VV

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