Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors
Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors
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DOI：
10.1371/journal.pone.0004681
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发表时间：
2009-03-05
期刊：
影响因子：
3.7
通讯作者：
Chow, Carson C.
中科院分区：
文献类型：
--
作者：
Fatakia, Sarosh N.;Costanzi, Stefano;Chow, Carson C.
G蛋白偶联受体（GPCR）是一个由七种跨膜蛋白组成的超家族，参与广泛的生理功能，是药物最常见的靶点。本研究的目的是确定一个队列或集团的立场，共享高互信息。使用跨膜（TM）结构域的多序列比对，我们计算了所有TM间比对位置对之间的互信息，并通过互信息对这些对进行排名。构建了一个互信息图，其顶点对应于TM位置，如果互信息超过统计显著性阈值，则绘制顶点之间的边。发现具有高程度的位置（即与大量其他位置具有显著的互信息）与A类以及C类GPCR的明确的TM间配体结合腔对齐。虽然C类受体的天然配体结合到它们的细胞外N-末端结构域，但是已经报道了通过结合到它们的螺旋束的配体来调节它们的活性的可能性。对于B类GPCR未发现这样的位置，这与不存在结合在其TM螺旋束内的已知配体的观察结果一致。所有识别的关键位置在感兴趣的MI图内形成一个集团。对于A类受体的一个子集，我们还考虑了第二胞外环的一部分的对齐，并发现与保守的Cys相邻的两个位置作为关键位置，所述保守的Cys将环与TM 3桥接。我们的算法可能是有用的定位在其他蛋白质家族的拓扑保守区域。
G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families.