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Improved protein structure prediction using predicted inter-residue orientations

View ORCID ProfileJianyi Yang, View ORCID ProfileIvan Anishchenko, View ORCID ProfileHahnbeom Park, View ORCID ProfileZhenling Peng, Sergey Ovchinnikov, View ORCID ProfileDavid Baker
doi: https://doi.org/10.1101/846279
Jianyi Yang
School of Mathematical Sciences, Nankai University, Tianjin 300071, China
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Ivan Anishchenko
Department of Biochemistry, University of Washington, Seattle, WA, USAInstitute for Protein Design, University of Washington, Seattle, WA, USA
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  • ORCID record for Ivan Anishchenko
Hahnbeom Park
Department of Biochemistry, University of Washington, Seattle, WA, USAInstitute for Protein Design, University of Washington, Seattle, WA, USA
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Zhenling Peng
Center for Applied Mathematics, Tianjin University, Tianjin, 300072, China
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Sergey Ovchinnikov
John Harvard Distinguished Science Fellowship Program, Harvard University, Cambridge, MA 02138, USA
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David Baker
Department of Biochemistry, University of Washington, Seattle, WA, USAInstitute for Protein Design, University of Washington, Seattle, WA, USAHoward Hughes Medical Institute, University of Washington, Seattle, WA, USA
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  • For correspondence: dabaker@uw.edu
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Abstract

The prediction of inter-residue contacts and distances from co-evolutionary data using deep learning has considerably advanced protein structure prediction. Here we build on these advances by developing a deep residual network for predicting inter-residue orientations in addition to distances, and a Rosetta constrained energy minimization protocol for rapidly and accurately generating structure models guided by these restraints. In benchmark tests on CASP13 and CAMEO derived sets, the method outperforms all previously described structure prediction methods. Although trained entirely on native proteins, the network consistently assigns higher probability to de novo designed proteins, identifying the key fold determining residues and providing an independent quantitative measure of the “ideality” of a protein structure. The method promises to be useful for a broad range of protein structure prediction and design problems.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 18, 2019.
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Improved protein structure prediction using predicted inter-residue orientations
Jianyi Yang, Ivan Anishchenko, Hahnbeom Park, Zhenling Peng, Sergey Ovchinnikov, David Baker
bioRxiv 846279; doi: https://doi.org/10.1101/846279
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Improved protein structure prediction using predicted inter-residue orientations
Jianyi Yang, Ivan Anishchenko, Hahnbeom Park, Zhenling Peng, Sergey Ovchinnikov, David Baker
bioRxiv 846279; doi: https://doi.org/10.1101/846279

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