Bioinformatics Advance Access originally published online on January 25, 2005
Bioinformatics 2005 21(9):1825-1830; doi:10.1093/bioinformatics/bti280
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Computational identification of human mitochondrial proteins based on homology to yeast mitochondrially targeted proteins
Metabolism Programme, Research Institute, The Hospital for Sick Children 555 University Avenue, Toronto, ON Canada, M5G1X8
*To whom correspondence should be addressed.
Motivation: Patients with defects of the mitochondrial respiratory chain due to mutations in nuclear genes are often undiagnosable due to the lack of information about the role of these genes. We therefore sought to produce a novel dataset of human nuclear-encoded mitochondrial proteins.
Results: We have used the web-based computer program Mitoprot to predict which proteins in the Saccharomyces cerevisiae genome are targeted to mitochondria. We then used this protein dataset to identify the homologous human proteins in the Unigene database using TBLASTN from NCBI. Human proteins with an Expectation value <10–5 and an Identity >30% were accepted as true homologues of the yeast proteins. These human proteins were then reanalyzed with Mitoprot. The final set of proteins comprises a dataset of 361 human mitochondrially targeted proteins with homology to all S.cerevisiae mitochondrially targeted proteins. One hundred twenty eight of these proteins are novel and are of unknown function.
Contact: bhr{at}sickkids.ca
Supplementary information: Supplementary tables will be available from http://www.sickkids.ca/Robinsonlab/
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  M. Kumar, R. Verma, and G. P. S. Raghava Prediction of Mitochondrial Proteins Using Support Vector Machine and Hidden Markov Model J. Biol. Chem., March 3, 2006; 281(9): 5357 - 5363. [Abstract] [Full Text] [PDF]
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