Predicting protein cellular localization using a domain projection method
Predicting protein cellular localization using a domain projection method
复制标题
DOI：
10.1101/gr.96802
复制
发表时间：
2002-08-01
期刊：
影响因子：
7
通讯作者：
Ponting, CP
中科院分区：
文献类型：
--
作者：
Mott, R;Schultz, J;Ponting, CP
我们研究了结构域家族在真核蛋白质中的共存，以预测蛋白质的细胞定位。大约一半(300)的智能域形成了一个“小世界网络”，它们之间的距离不超过7度。将结构域投影到二维空间显示了三个簇，它们对应于包含分泌蛋白、细胞质蛋白和核蛋白的细胞室。投影法考虑了“桥接”域的存在，即两个域可能不会彼此出现但经常与第三个域共存的情况；在这种情况下，这两个域是投影中的邻居。虽然大多数结构域是特定于一个区段(“区域”)的，因此可以用来定位任何包含这种区域的蛋白质，但一小部分区域要么存在于多个区域，要么存在于跨膜蛋白中。与以前标注的蛋白质的比较表明，该方法使用的智能域数据可以预测23%的真核蛋白质的定位，准确率为92%。随着领域数据库覆盖率的提高，覆盖率和准确率将会提高。这种方法是对使用氨基酸组成或识别排序序列的方法的补充；这些方法可以组合在一起以进一步提高预测精度。
We investigate the co-occurrence of domain families in eukaryotic proteins to predict protein cellular localization. Approximately half (300) of SMART domains form a "small-world network", linked by no more than seven degrees of separation. Projection of the domains onto two-dimensional space reveals three clusters that correspond to cellular compartments containing secreted, cytoplasmic, and nuclear proteins. The projection method takes into account the existence of "bridging" domains, that is, instances where two domains might not occur with each other but frequently co-occur with a third domain; in such circumstances the domains are neighbors in the projection. While the majority of domains are specific to a compartment ("locale"), and hence may be used to localize any protein that contains such a domain, a small subset of domains either are present in multiple locales or occur in transmembrane proteins. Comparison with previously annotated proteins shows that SMART domain data used with this approach can predict, with 92% accuracy, the localizations of 23% of eukaryotic proteins. The coverage and accuracy will increase with improvements in domain database coverage. This method is complementary to approaches that use amino-acid composition or identify sorting sequences; these methods may be combined to further enhance prediction accuracy.