4.7 Article

PolarProtDb: A Database of Transmembrane and Secreted Proteins showing Apical-Basal Polarity

期刊

JOURNAL OF MOLECULAR BIOLOGY
卷 433, 期 11, 页码 -

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jmb.2020.11.004

关键词

epithelial polarity; protein sorting; apical membrane; basolateral membrane; sorting signals

资金

  1. Hungarian Research and Developments Fund [OTKA K119287, K125607, 132522]
  2. Hungarian Academy of Sciences [LP2012-35]
  3. EMBO [STF-8784]

向作者/读者索取更多资源

The article introduces a comprehensive database containing experimentally verified mammalian proteins displaying polarized sorting or secretion, with a focus on epithelial cells. This database provides various information relevant to cell secretion and sorting, which can be valuable for researchers in conducting related studies or comparative analyses.
Most cells in multicellular organisms are somehow asymmetric, polarized: maintaining separate membrane domains. Typical examples are the epithelial cells (apical-basal polarization), neurons (dendriticaxonal domains), or migratory cells (with a leading and a trailing edge). Here we present the most comprehensive database containing experimentally verified mammalian proteins that display polarized sorting or secretion, focusing on epithelial polarity. In addition to the source cells or tissues, homology-based inferences and transmembrane topology (if applicable) are all provided. PolarProtDb also offers a detailed interface displaying all information that may be relevant for trafficking: including post-translational modifications (glycosylations and phosphorylations), known or predicted short linear motifs conserved across orthologs, as well as potential interaction partners. Data on polarized sorting has so far been scattered across myriads of publications, hence difficult to access. This information can help researchers in several areas, such as scanning for potential entry points of viral agents like COVID-19. PolarProtDb shall be a useful resource to design future experiments as well as for comparative analyses. (C) 2020 The Authors. Published by Elsevier Ltd.

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