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Can functional regions of proteins be predicted from their coding sequences? The case study of G-protein coupled receptors

Academic Article
Publication Date:
1998
abstract:
A filter based on a set of unsupervised neural networks trained with a winner-take-all strategy discloses signals along the coding sequences of G-protein coupled receptors. By comparing with the existing experimental data it appears that these signals correlate with putative functional domains of the proteins. After protein alignment within subfamilies, signals cluster in protein regions which, according to the presently available experimental results, are described as possible functional domains of the folded proteins. The mapping procedure reveals characteristic regions in the coding sequences common and/or characteristic of the receptor subtype. This is particularly noticeable for the third cytoplasmic loop, which is likely to be involved in the molecular coupling of all the subfamilies with G-proteins. The results indicate that our mapping can highlight intrinsic representative features of the coding sequences which, in the case of G-protein coupled receptors, are characteristic of protein functional regions and suggest a possible application of the filter for predicting functional determinants in proteins starting from the coding sequence.
Iris type:
01.01 Articolo in rivista
Keywords:
Neural Networks; Unsupervised Learning; Pattern Classification; G-protein coupled receptors; functional domains
List of contributors:
Arrigo, Patrizio
Handle:
https://iris.cnr.it/handle/20.500.14243/199474
Published in:
GENE
Journal
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