Guda Chittibabu, Subramaniam Shankar
Gen*NY*sis Center for Excellence in Cancer Genomics, State University of New York, One Discovery Drive, Rensselaer, NY 12144-3456, USA.
Bioinformatics. 2005 Nov 1;21(21):3963-9. doi: 10.1093/bioinformatics/bti650. Epub 2005 Sep 6.
There is a scarcity of efficient computational methods for predicting protein subcellular localization in eukaryotes. Currently available methods are inadequate for genome-scale predictions with several limitations. Here, we present a new prediction method, pTARGET that can predict proteins targeted to nine different subcellular locations in the eukaryotic animal species.
The nine subcellular locations predicted by pTARGET include cytoplasm, endoplasmic reticulum, extracellular/secretory, golgi, lysosomes, mitochondria, nucleus, plasma membrane and peroxisomes. Predictions are based on the location-specific protein functional domains and the amino acid compositional differences across different subcellular locations. Overall, this method can predict 68-87% of the true positives at accuracy rates of 96-99%. Comparison of the prediction performance against PSORT showed that pTARGET prediction rates are higher by 11-60% in 6 of the 8 locations tested. Besides, the pTARGET method is robust enough for genome-scale prediction of protein subcellular localizations since, it does not rely on the presence of signal or target peptides.
A public web server based on the pTARGET method is accessible at the URL http://bioinformatics.albany.edu/~ptarget. Datasets used for developing pTARGET can be downloaded from this web server. Source code will be available on request from the corresponding author.
用于预测真核生物中蛋白质亚细胞定位的高效计算方法匮乏。目前可用的方法存在若干局限性，不足以进行全基因组规模的预测。在此，我们提出一种新的预测方法pTARGET，它能够预测真核动物物种中靶向九个不同亚细胞位置的蛋白质。
pTARGET预测的九个亚细胞位置包括细胞质、内质网、细胞外/分泌、高尔基体、溶酶体、线粒体、细胞核、质膜和过氧化物酶体。预测基于特定位置的蛋白质功能域以及不同亚细胞位置之间的氨基酸组成差异。总体而言，该方法能够以96% - 99%的准确率预测68% - 87%的真阳性。与PSORT的预测性能比较表明，在测试的8个位置中的6个位置，pTARGET的预测率高出11% - 60%。此外，pTARGET方法对于蛋白质亚细胞定位的全基因组规模预测足够稳健，因为它不依赖于信号肽或靶向肽的存在。
基于pTARGET方法的公共网络服务器可通过网址http://bioinformatics.albany.edu/~ptarget访问。用于开发pTARGET的数据集可从该网络服务器下载。源代码可根据相应作者的要求提供。
