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Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA

Nature Methods, ISSN: 1548-7105, Vol: 21, Issue: 1, Page: 117-121
2024
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Reports from University of Washington Describe Recent Advances in Proteomics (Accurate Prediction of Protein-nucleic Acid Complexes Using Rosettafoldna)

2024 JAN 15 (NewsRx) -- By a News Reporter-Staff News Editor at Proteomics Daily -- A new study on Proteomics is now available. According to

Article Description

Protein–RNA and protein–DNA complexes play critical roles in biology. Despite considerable recent advances in protein structure prediction, the prediction of the structures of protein–nucleic acid complexes without homology to known complexes is a largely unsolved problem. Here we extend the RoseTTAFold machine learning protein-structure-prediction approach to additionally predict nucleic acid and protein–nucleic acid complexes. We develop a single trained network, RoseTTAFoldNA, that rapidly produces three-dimensional structure models with confidence estimates for protein–DNA and protein–RNA complexes. Here we show that confident predictions have considerably higher accuracy than current state-of-the-art methods. RoseTTAFoldNA should be broadly useful for modeling the structure of naturally occurring protein–nucleic acid complexes, and for designing sequence-specific RNA and DNA-binding proteins.

Bibliographic Details

Baek, Minkyung; McHugh, Ryan; Anishchenko, Ivan; Jiang, Hanlun; Baker, David; DiMaio, Frank

Springer Science and Business Media LLC

Biochemistry, Genetics and Molecular Biology

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