• Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14

    13 days ago - By Wiley

    Abstract
    The trRosetta structure prediction method employs deep learning to generate predicted residue-residue distance and orientation distributions from which 3D models are built. We sought to improve the method by incorporating as inputs both language model embeddings and template information weighted by sequence similarity to the target. We also developed a refinement pipeline that recombines models generated by template-free and template utilizing versions of trRosetta guided by the DeepAccNet accuracy predictor. Both benchmark tests and CASP results show that the new pipeline is a...
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  • Continuous Automated Model EvaluatiOn -Perspectives on the future of fully automated evaluation of structure prediction methods

    13 days ago - By Wiley

    Abstract
    The Continuous Automated Model EvaluatiOn platform complements the biennial CASP experiment by conducting fully automated blind evaluations of three-dimensional protein prediction servers based on the weekly prerelease of sequences of those structures, which are going to be published in the upcoming release of the Protein Data Bank. While in CASP14, significant success was observed in predicting the structures of individual protein chains with high accuracy, significant challenges remain in correctly predicting the structures of complexes. By implementing fully automated...
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