John Meinken^1,4 , David K. Asch^2,4 , Kofi A. Neizer-Ashun³ , Guang-Hwa Chang³ , Chester R.Cooper JR^2,4 , Xiang Jia Min^2,4

1. Department of Computer Science and Information Systems, Youngstown State University, OH 44555, USA
2. Department of Biological Sciences, Youngstown State University, Youngstown, OH 44555, USA
3. Department of Mathematics & Statistics, Youngstown State University, Youngstown, OH 44555, USA
4. Center for Applied Chemical Biology, Youngstown State University, Youngstown, OH 44555, USA
Author    Correspondence author
Computational Molecular Biology, 2014, Vol. 4, No. 7   doi: 10.5376/cmb.2014.04.0007
Received: 05 Aug., 2014    Accepted: 21 Sep., 2014    Published: 22 Oct., 2014

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Meinken et al., 2014, FunSecKB2: a fungal protein subcellular location knowledgebase, Computational Molecular Biology, Vol.4, No.6, 1-17 (doi: 10.5376/cmb.2014.04.0007)

FunSecKB2 is an improved and updated version of the fungal secretome and subcellular proteome, i. e. protein subcellular location, knowledgebase. The fungal protein sequence data were retrieved from UniProtKB, consisting of nearly 2 million entries with 167 species having a complete proteome. The assignments of protein subcellular locations were based on curated information and prediction using seven computational tools. The tools used for subcellular location prediction include SignalP, WoLF PSORT, Phobius, TargetP, TMHMM, FragAnchor, and PS-Scan. Secreted proteins, i.e. secretomes, along with 15 other subcellular proteomes were predicted. The database can be searched by users using several different types of identifiers, gene name or keyword(s). A subcellular proteome from a species can be searched or downloaded. BLAST searching whole fungal protein data or secretomes is available. Community annotation of subcelluar locations based on experimental evidence is also supported. A primary analysis revealed that the secretome size of a fungal species is one of the determining factors to its lifestyle. The Gene Ontology and protein domain analysis of fungal secretomes revealed that fungal secretomes contain a large number of hydrolases, peptidases, oxidoreductases, and lysases, which may have potential applications in bio-processing of chemical wastes or biofuel production. The database provides an important and rich resource for the fungal community looking for protein subcellular location information and performing comparative subcellular proteome analysis.
 

Computational prediction; Fungi; Secreted protein; Secretome; Signal peptide; Subcellular location; Subcellular proteome