Predotar: A tool for rapidly screening proteomes for N‐terminal targeting sequences
Top Cited Papers
- 25 May 2004
- journal article
- research article
- Published by Wiley in Proteomics
- Vol. 4 (6) , 1581-1590
- https://doi.org/10.1002/pmic.200300776
Abstract
Probably more than 25% of the proteins encoded by the nuclear genomes of multicellular eukaryotes are targeted to membrane‐bound compartments by N‐terminal targeting signals. The major signals are those for the endoplasmic reticulum, the mitochondria, and in plants, plastids. The most abundant of these targeted proteins are well‐known and well‐studied, but a large proportion remain unknown, including most of those involved in regulation of organellar gene expression or regulation of biochemical pathways. The discovery and characterization of these proteins by biochemical means will be long and difficult. An alternative method is to identify candidate organellar proteins via their characteristic N‐terminal targeting sequences. We have developed a neural network‐based approach (Predotar – Prediction of Organelle Targeting sequences) for identifying genes encoding these proteins amongst eukaryotic genome sequences. The power of this approach for identifying and annotating novel gene families has been illustrated by the discovery of the pentatricopeptide repeat family.Keywords
This publication has 33 references indexed in Scilit:
- Hydrophobicity scales and computational techniques for detecting amphipathic structures in proteinsPublished by Elsevier ,2005
- Multiple sequence alignment with the Clustal series of programsNucleic Acids Research, 2003
- Evolutionary diversification of mitochondrial proteomes: implications for human diseaseTrends in Genetics, 2003
- The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003Nucleic Acids Research, 2003
- Predicting Subcellular Localization of Proteins Based on their N-terminal Amino Acid SequenceJournal of Molecular Biology, 2000
- The PPR motif – a TPR-related motif prevalent in plant organellar proteinsTrends in Biochemical Sciences, 2000
- ChloroP, a neural network‐based method for predicting chloroplast transit peptides and their cleavage sitesProtein Science, 1999
- Basic local alignment search toolJournal of Molecular Biology, 1990
- Chloroplast transit peptides from the green alga Chlamydomonas reinhardtii share features with both mitochondrial and higher plant chloroplast presequencesFEBS Letters, 1990
- Conformational parameters for amino acids in helical, β-sheet, and random coil regions calculated from proteinsBiochemistry, 1974