Arrigo P, Fariselli P, Casadio R
Istituto Circuiti Elettronici, Consiglio Nazionale delle Richerche, Genova, Italy.
Gene. 1998 Oct 9;221(1):GC65-110. doi: 10.1016/s0378-1119(98)00220-0.
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.
一种基于采用胜者全得策略训练的一组无监督神经网络的过滤器,揭示了G蛋白偶联受体编码序列中的信号。通过与现有实验数据比较,这些信号似乎与蛋白质的推定功能域相关。在亚家族内进行蛋白质比对后,信号聚集在蛋白质区域中,根据目前可用的实验结果,这些区域被描述为折叠蛋白的可能功能域。映射过程揭示了受体亚型共有的和/或特有的编码序列中的特征区域。这在第三个细胞质环中尤为明显,它可能参与所有亚家族与G蛋白的分子偶联。结果表明,我们的映射可以突出编码序列的内在代表性特征,在G蛋白偶联受体的情况下,这些特征是蛋白质功能区域的特征,并提出了该过滤器从编码序列预测蛋白质功能决定因素的可能应用。