title: PCHM: A bioinformatic resource for high-throughput human mitochondrial proteome searching and comparison.
abstract: Mitochondrial proteins associated with a wide spectrum of human diseases and currently large amounts of tissue or organ specific human mitochondrial proteome datasets are generated. However, high-throughput comparative proteomic methods have yet to be applied to extract subtle differences among mitochondria from different tissues or muscle types. The aim of this work was to provide an integrated way to identify and compare huge mitochondrial protein or peptide mass spectral data sets acquired from expert mitochondrial proteome or biomarker discovery community. Proteome comparison of human mitochondria (PCHM) is a web-based analysis environment for manual or automatic analysis of individual peptide mass fingerprints alongside a database of proteins and peptides identified in various organs for human mitochondrial proteins. PCHM provides a suite of graphical tools that allow the virtual plot of peptide mass fingerprinting (PMF) spectra and a fully automatic protein function classification based on gene ontology (GO) annotation system. The new virtual PMF plot is very useful to validate fragmented ion loses of any identical proteins and to remove unwanted foreign ion peaks. Fully automatic protein function classifier provides an easier way to compare the subtle differences of compositionally biased mitochondrial protein functions. PCHM also provides a variety of query algorithms aid in browsing, searching, and accessing complete annotations of data relevant to each mitochondrial protein of interest, which link external databases and users. PCHM will be a useful tool for the systematic and functional characterization of the mitochondrial proteins in relation to human diseases or biological research applications. PCHM can be accessed freely via a web interface http://pchm.inje.ac.kr.
authors.affiliation: Department of Physiology and Integrated Biosystems, College of Medicine, Inje University, Busan 614-735, Republic of Korea. taehok@gurum.inje.ac.kr
authors.forename: Taeho
authors.initials: T
authors.lastname: Kim
authors.forename: Euiyong
authors.initials: E
authors.lastname: Kim
authors.forename: Seok-Ju
authors.initials: SJ
authors.lastname: Park
authors.forename: Hyun
authors.initials: H
authors.lastname: Joo
mesh_terms: D000465:Algorithms; D001331:Automation; D015415:Biomarkers / Q000378:metabolism; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D030562:Databases, Protein; D006801:Humans; D020407:Internet; D008928:Mitochondria / Q000378:metabolism / Q000502:physiology*; D024101:Mitochondrial Proteins / Q000737:chemistry*; D010455:Peptides / Q000737:chemistry; D020543:Proteome; D040901:Proteomics / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods; D012984:Software
chemical_list: D015415:Biomarkers; D024101:Mitochondrial Proteins; D010455:Peptides; D020543:Proteome