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Computing the three-dimensional structure of a protein molecule from its amino acid sequence is a long-standing grand challenge problem. Results from the recent Critical Assessment of Structure Prediction (CASP14) experiment show that new deep-learning methods have now provided a dramatic solution, with many computed structures comparable, likely sometimes better, representations of in vivo protein structures to those obtained with state-of-the-art experimental techniques of crystallography and cryo-electron microscopy. These models have already demonstrated an ability to solve problematic crystal structures, and the results suggest the methods will be successfully applied to other areas of structural biology and more generally.

In this talk I’ll describe how the protein modeling field arrived at this point, what sort of methods were used, and some potential further applications.

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