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The field of protein structure prediction has greatly advanced in recent years thanks to increasingly accurate deep-learning methods. More than protein structures have been predicted in this way and are now available in Pfam, with more to follow. And by exploring these protein structures, they can also start to gradually understand the protein functions. It uses the large, multiple sequence alignments available in Pfam and applies a deep learning model to predict the transformations and structure parameters for each protein. It then applies the Rosetta pipeline to predict the structure. An lDDT score of 0. The large majority of structural models obtained from rtRosetta are of good quality, with an lDDT score of over 0.
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