Predicting subcellular localization of proteins based on their N-terminal amino acid sequence

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/. (C) 2000 Academic Press.