Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 73, 14195 Berlin, Germany.
J Mol Histol. 2009 Oct;40(5-6):343-52. doi: 10.1007/s10735-009-9247-9. Epub 2009 Dec 22.
The subcellular localization of a protein can provide important information about its function within the cell. As eukaryotic cells and particularly mammalian cells are characterized by a high degree of compartmentalization, most protein activities can be assigned to particular cellular compartments. The categorization of proteins by their subcellular localization is therefore one of the essential goals of the functional annotation of the human genome. We previously performed a subcellular localization screen of 52 proteins encoded on human chromosome 21. In the current study, we compared the experimental localization data to the in silico results generated by nine leading software packages with different prediction resolutions. The comparison revealed striking differences between the programs in the accuracy of their subcellular protein localization predictions. Our results strongly suggest that the recently developed predictors utilizing multiple prediction methods tend to provide significantly better performance over purely sequence-based or homology-based predictions.
蛋白质的亚细胞定位可以提供有关其在细胞内功能的重要信息。由于真核细胞,特别是哺乳动物细胞具有高度的区隔化特征,因此大多数蛋白质的活性都可以分配到特定的细胞区室中。因此,根据亚细胞定位对蛋白质进行分类是人类基因组功能注释的重要目标之一。我们之前对人类 21 号染色体上编码的 52 种蛋白质进行了亚细胞定位筛选。在本研究中,我们将实验定位数据与由 9 个具有不同预测分辨率的领先软件包生成的计算结果进行了比较。比较结果表明,这些程序在亚细胞蛋白定位预测的准确性方面存在显著差异。我们的结果强烈表明,最近开发的利用多种预测方法的预测器在性能上明显优于纯基于序列或基于同源性的预测器。