TECHNICAL BRIEF Proteopathogen, a protein database for studying Candida albicans – host interaction Vital Viala ´s 1 , Rube ´n Nogales-Cadenas 2 , Ce ´sar Nombela 1 , Alberto Pascual-Montano 2 and Concha Gil 1,3 1 Departamento de Microbiologı´a II, Facultad de Farmacia, Universidad Complutense de Madrid, Madrid, Spain 2 Departamento de Arquitectura de Computadores y Automa ´tica, Facultad de Ciencias Fı´sicas, Universidad Complutense de Madrid, Madrid, Spain 3 Unidad de Proteo ´mica UCM-Parque Cientı´fico de Madrid, Facultad de Farmacia, Universidad, Complutense de Madrid, Madrid, Spain Received: January 13, 2009 Revised: June 25, 2009 Accepted: July 2, 2009 There exist, at present, public web repositories for management and storage of proteomic data and also fungi-specific databases. None of them, however, is focused to the specific research area of fungal pathogens and their interactions with the host, and contains proteomics experimental data. In this context, we present Proteopathogen, a database intended to compile proteomics experimental data and to facilitate storage and access to a range of data which spans proteomics workflows from description of the experimental approaches leading to sample preparation to MS settings and peptides supporting protein identification. Proteopathogen is currently focused on Candida albicans and its interaction with macrophages; however, data from experiments concerning different pathogenic fungi species and other mammalian cells may also be found suitable for inclusion into the data- base. Proteopathogen is publicly available at http://proteopathogen.dacya.ucm.es Keywords: Candida albicans / Database / Host / MS / Microbiology / Pathogen Candida albicans is an opportunistic pathogenic fungus, which can be found as a component of the usual flora in human mucoses. Although it does not normally cause disease in immunocompetent colonized hosts, in the case of immunosuppressed patients Candida cells can over- proliferate and become pathogenic. Cells in yeast form (oval cells) may produce hyphae, penetrate tissues and eventually cause invasive candidiasis. At present, the frequency of this fatal opportunistic mycosis continues to be distressing and, unfortunately, solution is hindered by the reduced effec- tiveness and serious side effects of the few available drugs, the appearance of antifungal-drug resistance, and the lack of accurate and prompt diagnostic procedures [1]. Addressing proteomic studies involving the way Candida interacts with immune cells is thus essential in order to improve our comprehension of the process of infection and represents the primary step of investigation that could lead to future development of diagnosis methods, vaccines and antifungal drugs [2–5]. Experimental techniques in proteomics have quickly evolved in such a way that nowadays we have to deal with vast amounts of complex data originated by the combination of multi-dimensional separation techniques and MS analy- sis together with the bioinformatics software reports [6]. Existing public repositories for management and storage of proteomic data such as World 2-D PAGE [7], the Proteome Database System for Microbial Research 2-D PAGE [8], or PRIDE [9]; and fungi-specific databases such as BioBase MycoPathPD [10], Candida Genome Database (CGD) [11] or Candida DB [12] are very popular and useful tools. However, none of them deals with proteomic experimental Abbreviations: CGD, Candida Genome Database; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; PDB, Protein Data Bank Correspondence: Dr. Concha Gil, Departamento de Micro- biologı´a II, Facultad, de Farmacia, Universidad Complutense, Plaza de Ramo ´ n y Cajal s/n, 28040 Madrid, Spain E-mail: conchagil@farm.ucm.es Fax:134-913941745 & 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com Proteomics 2009, 9, 1–5 1 DOI 10.1002/pmic.200900023