![]() ![]() Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures 3. Considerable progress has recently been made by leveraging genetic information. This problem is of fundamental importance as the structure of a protein largely determines its function 2 however, protein structures can be difficult to determine experimentally. Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence 1.
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