Combining N-grams and Alignment in G-protein Coupling Specificity Prediction

B. Cheng, J. Carbonell
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引用次数: 2

Abstract

G-protein coupled receptors (GPCR) interact with G-proteins to regulate much of the cell’s response to external stimuli; abnormalities in which cause numerous diseases. We developed a new method to predict the families of G-proteins with which it interacts, given its residue sequence. We combine both alignment and n-gram features. The former captures long-range interactions but assumes the linear ordering of conserved segments is preserved. The latter makes no such assumption but cannot capture long-range interactions. By combining alignment and n-gram features, and using the entire GPCR sequence (instead of intracellular regions alone, as was done by others), our method outperformed the current state-of-the-art in precision, recall and F1, attaining 0.753 in F1 and 0.796 in accuracy on the PTbase 2004 dataset. Moreover, analysis of our results shows that the majority of coupling specificity information lies in the beginning of the 2nd intracellular loop and over the length of the 3rd.
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结合N-grams和比对技术预测g蛋白偶联特异性
g蛋白偶联受体(GPCR)与g蛋白相互作用,调节细胞对外界刺激的反应;引起许多疾病的异常。我们开发了一种新的方法来预测与它相互作用的g蛋白家族,给定它的残基序列。我们结合了对齐和n-gram特征。前者捕获远程相互作用,但假设保留了保守片段的线性顺序。后者没有这样的假设,但无法捕捉远程相互作用。通过结合比对和n-gram特征,并使用整个GPCR序列(而不是像其他人那样单独使用细胞内区域),我们的方法在精度,召回率和F1方面优于当前最先进的技术,在PTbase 2004数据集上F1达到0.753,准确性为0.796。此外,我们的结果分析表明,大多数偶联特异性信息位于细胞内第2环的开始和第3环的长度。
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