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Predicting Subcellular Localization of Proteins Based on their N-terminal Amino Acid Sequence,☆☆

https://doi.org/10.1006/jmbi.2000.3903Get rights and content

Abstract

A neural network-based tool, TargetP, for large-scale subcellular location prediction of newly identified proteins has been developed. Using N-terminal sequence information only, it discriminates between proteins destined for the mitochondrion, the chloroplast, the secretory pathway, and “other” localizations with a success rate of 85 % (plant) or 90 % (non-plant) on redundancy-reduced test sets. From a TargetP analysis of the recently sequenced Arabidopsis thaliana chromosomes 2 and 4 and the Ensembl Homo sapiens protein set, we estimate that 10 % of all plant proteins are mitochondrial and 14 % chloroplastic, and that the abundance of secretory proteins, in both Arabidopsis and Homo, is around 10 %. TargetP also predicts cleavage sites with levels of correctly predicted sites ranging from approximately 40 % to 50 % (chloroplastic and mitochondrial presequences) to above 70 % (secretory signal peptides). TargetP is available as a web-server at http://www.cbs.dtu.dk/services/TargetP/.

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    Abbreviations used: SP, signal peptide; mTP, mitochondrial targeting peptide; MPP, mitochondrial processing peptidase; MIP, mitochondrial intermediate peptidase; IMS, intermembrane space; cTP, chloroplast transit peptide; SPP, stromal processing peptidase

    ☆☆

    Edited by F. E. Cohen

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    E-mail address of the corresponding author: [email protected]

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