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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

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HighDB: a structure-annotated cyclic peptide database for comparative analysis, template retrieval, and

Yiqi Xu1, Ning Zhu2, Tianfeng Shang3

  • 1College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, China.

Journal of Computer-Aided Molecular Design
|July 14, 2026
PubMed
Summary

HighDB is a new database featuring 2,504 experimentally resolved cyclic peptide structures. This resource offers comprehensive annotations and tools for exploring cyclic peptide space, aiding drug discovery efforts.

Keywords:
Benchmark constructionCyclic peptide databaseStructural bioinformaticsTemplate retrievalTopology annotation

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Area of Science:

  • Structural Biology
  • Computational Chemistry
  • Drug Discovery

Background:

  • Cyclic peptides are valuable modulators of challenging drug targets and protein-protein interactions.
  • Existing structure-centered resources for cyclic peptides lack standardized, computable annotations.
  • Limited databases hinder comparative structural analysis and design-oriented exploration of cyclic peptide chemical space.

Purpose of the Study:

  • To present HighDB, a curated database of experimentally resolved cyclic peptide structures.
  • To provide standardized, computable annotations for cyclic peptide structures.
  • To facilitate comparative structural analysis and exploration of cyclic peptide design space.

Main Methods:

  • Collected 2,504 experimentally resolved cyclic peptide structures from the Protein Data Bank and literature.
  • Annotated entries at the PDB-chain level, harmonizing cyclization type, ring number, secondary structure, naturalness, and complex context.
  • Integrated keyword retrieval, multidimensional filtering, sequence-similarity search, and interactive 3D visualization.

Main Results:

  • HighDB contains 2,504 entries with harmonized annotations.
  • The database offers tools for comparative structural analysis, dataset construction, and template retrieval.
  • HighDB provides a unified annotation framework for topological and conformational descriptors.
  • Compared to existing resources, HighDB shows broader annotation coverage and the largest collection of experimentally resolved structures.

Conclusions:

  • HighDB is a comprehensive, freely accessible resource for cyclic peptide structural data.
  • The database and its unified annotation framework advance the study and design of cyclic peptides.
  • HighDB supports structure-centered research on cyclic peptides for drug discovery and other applications.