Brian Powell¹ , Vamshi Amerishetty² , John Meinken^2,3 , Geneva Knott⁴ , Feng Yu¹ , Chester Cooper^2,4 , Xiang Jia Min^2,4

1 Department of Computer Science & Information Systems, Youngstown State University, Youngstown, OH 44555, USA
2 Center for Applied Chemical Biology, Youngstown State University, Youngstown, OH 44555, USA
3 Center for Health Informatics, University of Cincinnati, Cincinnati, OH 45267-0840, USA
4 Department of Biological Sciences, Youngstown State University, Youngstown, OH 44555, USA
Author    Correspondence author
Computational Molecular Biology, 2016, Vol. 6, No. 4   doi: 10.5376/cmb.2016.06.0004
Received: 19 Sep., 2016    Accepted: 01 Nov., 2016    Published: 14 Dec., 2016

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.

Powell B., Amerishetty V., Meinken J., Knott G., Feng Y., Cooper C., and Min X.J., 2016, ProtSecKB: the protist secretome and subcellular proteome knowledgebase, Computational Molecular Biology, 6(4): 1-12

Kingdom Protista contains a large group of eukaryotic organisms with diverse lifestyles. We developed the Protist Secretome and Subcellular Proteome Knowledgebase (ProtSecKB) to host information of curated and predicted subcellular locations of all protist proteins. The protist protein sequences were retrieved from UniProtKB, consisting of 1.97 million entries generated from 7,024 species with 101 species including 127 organisms having complete proteomes. The protein subcellular locations were based on curated information and predictions using a set of well evaluated computational tools.  The database can be searched using several different types of identifiers, gene names or keyword(s). Secretomes and other subcellular proteomes can be searched or downloaded. BLAST searching against the complete set of protist proteins or secretomes is available.  Protein family analysis of secretomes from representing protist species, including Dictyostelium discoideum, Phytophthora infestans, and Trypanosoma cruzi, showed that species with different lifestyles had drastic differences of protein families in their secretomes, which may determine their lifestyles. The database provides an important resource for the protist and biomedical research community. The database is available at http://bioinformatics.ysu.edu/secretomes/protist/index.php.

Computational Prediction; Protest; Protista; Secreted Protein; Secretome; Signal Peptide; Subcellular Location; Subcellular Proteome; Lifestyle