Protein secondary structure and homology by neural networks. The alpha-helices in rhodopsin |
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Authors: | H Bohr J Bohr S Brunak R M Cotterill B Lautrup L N?rskov O H Olsen S B Petersen |
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Institution: | Technical University, Lyngby, Denmark. |
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Abstract: | Neural networks provide a basis for semiempirical studies of pattern matching between the primary and secondary structures of proteins. Networks of the perceptron class have been trained to classify the amino-acid residues into two categories for each of three types of secondary feature: alpha-helix or not, beta-sheet or not, and random coil or not. The explicit prediction for the helices in rhodopsin is compared with both electron microscopy results and those of the Chou-Fasman method. A new measure of homology between proteins is provided by the network approach, which thereby leads to quantification of the differences between the primary structures of proteins. |
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