PSORTdb--an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea

Nucleic Acids Res. 2011 Jan;39(Database issue):D241-4. doi: 10.1093/nar/gkq1093. Epub 2010 Nov 10.

Abstract

The subcellular localization (SCL) of a microbial protein provides clues about its function, its suitability as a drug, vaccine or diagnostic target and aids experimental design. The first version of PSORTdb provided a valuable resource comprising a data set of proteins of known SCL (ePSORTdb) as well as pre-computed SCL predictions for proteomes derived from complete bacterial genomes (cPSORTdb). PSORTdb 2.0 (http://db.psort.org) extends user-friendly functionalities, significantly expands ePSORTdb and now contains pre-computed SCL predictions for all prokaryotes--including Archaea and Bacteria with atypical cell wall/membrane structures. cPSORTdb uses the latest version of the SCL predictor PSORTb (version 3.0), with higher genome prediction coverage and functional improvements over PSORTb 2.0, which has been the most precise bacterial SCL predictor available. PSORTdb 2.0 is the first microbial protein SCL database reported to have an automatic updating mechanism to regularly generate SCL predictions for deduced proteomes of newly sequenced prokaryotic organisms. This updating approach uses a novel sequence analysis we developed that detects whether the microbe being analyzed has an outer membrane. This identification of membrane structure permits appropriate SCL prediction in an auto-updated fashion and allows PSORTdb to serve as a practical resource for genome annotation and prokaryotic research.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Archaeal Proteins / analysis*
  • Bacterial Proteins / analysis*
  • Computational Biology
  • Databases, Protein*
  • Intracellular Space / chemistry
  • Membrane Proteins / analysis
  • Proteome / analysis
  • User-Computer Interface

Substances

  • Archaeal Proteins
  • Bacterial Proteins
  • Membrane Proteins
  • Proteome