SEPDB: a database of secreted proteins

Database (Oxford). 2024 Feb 12:2024:baae007. doi: 10.1093/database/baae007.

Abstract

Detecting changes in the dynamics of secreted proteins in serum has been a challenge for proteomics. Enter secreted protein database (SEPDB), an integrated secretory proteomics database offering human, mouse and rat secretory proteomics datasets collected from serum, exosomes and cell culture media. SEPDB compiles secreted protein information from secreted protein database, UniProt and Human Protein Atlas databases to annotate secreted proteomics data based on protein subcellular localization and disease markers. SEPDB integrates the latest predictive modeling techniques to measure deviations in the distribution of signal peptide structures of secreted proteins, extends signal peptide sequence prediction by excluding transmembrane structural domain proteins and updates the validation analysis pipeline for secreted proteins. To establish tissue-specific profiles, we have also created secreted proteomics datasets associated with different human tissues. In addition, we provide information on heterogeneous receptor network organizational relationships, reflective of the complex functional information inherent in the molecular structures of secreted proteins that serve as ligands. Users can take advantage of the Refreshed Search, Analyze, Browse and Download functions of SEPDB, which is available online at https://sysomics.com/SEPDB/. Database URL: https://sysomics.com/SEPDB/.

MeSH terms

  • Animals
  • Databases, Protein
  • Humans
  • Mice
  • Protein Sorting Signals
  • Proteins* / chemistry
  • Proteomics* / methods
  • Rats

Substances

  • Proteins
  • Protein Sorting Signals