Univ. Politècnica de Catalunya, UPC BarcelonaTech, 08034, Barcelona, Spain.
Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain.
Interdiscip Sci. 2018 Mar;10(1):43-52. doi: 10.1007/s12539-018-0286-3. Epub 2018 Feb 19.
G-protein-coupled receptors (GPCRs) are a large and diverse super-family of eukaryotic cell membrane proteins that play an important physiological role as transmitters of extracellular signal. In this paper, we investigate Class C, a member of this super-family that has attracted much attention in pharmacology. The limited knowledge about the complete 3D crystal structure of Class C receptors makes necessary the use of their primary amino acid sequences for analytical purposes. Here, we provide a systematic analysis of distinct receptor sequence segments with regard to their ability to differentiate between seven class C GPCR subtypes according to their topological location in the extracellular, transmembrane, or intracellular domains. We build on the results from the previous research that provided preliminary evidence of the potential use of separated domains of complete class C GPCR sequences as the basis for subtype classification. The use of the extracellular N-terminus domain alone was shown to result in a minor decrease in subtype discrimination in comparison with the complete sequence, despite discarding much of the sequence information. In this paper, we describe the use of Support Vector Machine-based classification models to evaluate the subtype-discriminating capacity of the specific topological sequence segments.
G 蛋白偶联受体(GPCRs)是一大类多样化的真核细胞膜蛋白,作为细胞外信号的传递者,在生理上发挥着重要作用。在本文中,我们研究了该超家族的成员 C 类,它在药理学中引起了广泛关注。由于对 C 类受体完整 3D 晶体结构的了解有限,因此有必要使用其原始氨基酸序列进行分析。在这里,我们对不同的受体序列片段进行了系统分析,以研究它们根据细胞外、跨膜或细胞内结构域的拓扑位置,区分七种 C 类 GPCR 亚型的能力。我们基于先前的研究结果,该研究初步证明了使用完整 C 类 GPCR 序列的分离结构域作为亚型分类的基础具有潜在用途。尽管丢弃了大部分序列信息,但仅使用细胞外 N 端结构域,与完整序列相比,在区分亚型方面的能力略有下降。本文描述了使用基于支持向量机的分类模型来评估特定拓扑序列片段的亚型区分能力。