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Bioinformatics Advance Access originally published online on September 6, 2005
Bioinformatics 2005 21(21):3963-3969; doi:10.1093/bioinformatics/bti650
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oxfordjournals.org

TARGET: a new method for predicting protein subcellular localization in eukaryotes

Chittibabu Guda 1,2,* and Shankar Subramaniam 3,4,5

1Gen*NY*sis Center for Excellence in Cancer Genomics, State University of New York One Discovery Drive, Rensselaer, NY 12144-3456, USA
2Department of Epidemiology and Biostatistics, University at Albany, State University of New York One Discovery Drive, Rensselaer, NY 12144-3456, USA
3San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
4Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
5Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA

*To whom correspondence should be addressed.

Motivation: 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.

Results: 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.

Availability: 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.

Contact: cguda{at}albany.edu

Supplementary data: Accessible as online-only from the publisher.

Received on May 3, 2005; revised on August 26, 2005; accepted on August 26, 2005

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