Improved protein structure prediction using predicted interresidue orientations

Yang, Jianyi; Anishchenko, Ivan; Park, Hahnbeom; Peng, Zhenling; Ovchinnikov, Sergey; Baker, David

doi:10.1073/pnas.1914677117

articleProceedings of the National Academy of SciencesJan 2, 2020BRONZE OA

Improved protein structure prediction using predicted interresidue orientations

JYJianyi Yang IAIvan Anishchenko HPHahnbeom Park ZPZhenling Peng SOSergey Ovchinnikov

Nankai University · University of Washington · +3 more institutions

PubMed

Indexed incrossrefpubmed

Abstract

The prediction of interresidue contacts and distances from coevolutionary data using deep learning has considerably advanced protein structure prediction. Here, we build on these advances by developing a deep residual network for predicting interresidue 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 13th Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP13)- and Continuous Automated Model Evaluation (CAMEO)-derived sets, the method outperforms all previously described structure-prediction methods. Although…

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Topics & keywords

Topics

Keywords

Benchmark (surveying)
Protein structure prediction
Computer science
Residual
Artificial intelligence
Network structure
Range (aeronautics)
Measure (data warehouse)

UN Sustainable Development Goals

Affordable and clean energy

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