Baek et al. |
RoseTTAFold2NA
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RoseTTAFold2NA is an advanced computational tool developed to predict the structures of protein/nucleic acid complexes with high accuracy. Building on the RoseTTAFold framework, which utilizes state-of-the-art deep learning techniques for protein structure prediction, RoseTTAFold2NA integrates the modeling of nucleic acids, thereby extending its capabilities to include complex biomolecular interactions.
Example use case: Predict the structure of viral RNA-protein complexes to identify targets for designing inhibitors.
Technology: Neural Network
Citation:
Baek, M., McHugh, R., Anishchenko, I. et al. Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA. Nat Methods 21, 117–121 (2024). https://doi.org/10.1038/s41592-023-02086-5
Released:
Jul-08-2024
Jul-08-2024
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