TUPDB

TUPDB catalogs target-unrelated peptides (TUPs) to support interpretation and filtering of phage display selection (biopanning) results.


Key Features:

  • Curated TUP collection: Contains 73 experimentally confirmed TUPs and 1963 potential TUPs.
  • Data sources: Aggregates entries from TUPScan, the BDB database, and public research articles.
  • Manual curation: Entries are manually curated to enhance data accuracy and reliability.
  • Integration with TUPScan: Linked with TUPScan to facilitate detailed analysis and detection of TUPs.
  • TUP identification and removal: Provides data and functionality to identify and eliminate target-unrelated peptides from phage display datasets.

Scientific Applications:

  • Phage display analysis: Improves interpretation of biopanning results by distinguishing true binders from TUPs.
  • Epitope mapping: Enhances epitope mapping quality by removing confounding TUPs from datasets.
  • Vaccine development: Supports selection of genuine target-binding peptides for vaccine antigen discovery.
  • Diagnostics: Aids identification of specific peptide biomarkers by excluding nonspecific TUPs.
  • Therapeutics discovery: Assists therapeutic peptide discovery by filtering out target-unrelated sequences.

Methodology:

Entries were aggregated from TUPScan, the BDB database, and public research articles and manually curated; the database integrates with TUPScan to enable detailed analysis and identification/removal of TUPs.

Topics

Details

Tool Type:
web application
Added:
12/13/2021
Last Updated:
12/13/2021

Operations

Data Inputs & Outputs

Database search

Publications

He B, Yang S, Long J, Chen X, Zhang Q, Gao H, Chen H, Huang J. TUPDB: Target-Unrelated Peptide Data Bank. Interdisciplinary Sciences: Computational Life Sciences. 2021;13(3):426-432. doi:10.1007/s12539-021-00436-5. PMID:33993461.

PMID: 33993461
Funding: - National Natural Science Foundation of China: 61901129, 61901130, 62071099 - Guizhou University: (2018)54, (2018)55 - Guizhou Science and Technology Department: (2018)5781, [2020]1Y345, [2020]1Y407 - China Postdoctoral Science Foundation: 2019M653369, 2019M660236