Update Log

  • 2024.09.30 (V1.4.0)

    Update plan

      Data updates

    • 1. Keep an eye on the latest Cyclic peptide releases, incorporate them into Cyclicpepedia, and display them in the News module;
    • 2. Supplement cyclic peptide target information from databases such as Therapeutic Target Database.

    • Integration of artificial intelligence tools

    • 1. Use artificial intelligence models to predict high affinity binding targets, pharmacological properties, toxicity, and biological activities of cyclic peptides;
    • 2. Use AI tools, for example AlphaFold2 and AfCycDesign, to predict cyclic peptide 3D structures and protein-peptide complex structures;
    • 3. Integrate AI tools into CyclicPepedia.

    • Addressing user feedback and demands

      Add additional interfaces and cyclic peptide tools.

  • 2024.07.05 (V1.3.2)

    Data updates

    • 1. Complement the cyclic peptides from the CreativePeptides and the user feedback.
    • 2. Partial cyclic peptides deletion data and target data were supplemented.

  • 2024.07.05 (V1.3.2)

    Backend development

    • 1. Fixed some back-end bugs.

  • 2024.02.26 (V1.3.1)

    Data updates

    • 1. Added the relevant information (drug ID) of cyclic peptides from TTD, VARDIT, INTEDE, TheMarker and DrugMAP.

  • 2024.02.26 (V1.3.1)

    Backend development

    • 1. Fixed some back-end bugs.

  • 2024.02.26 (V1.3.1)

    Front-end development

    • 1. Added connections to TTD, VARDIT, INTEDE, TheMarker and DrugMAP;
    • 2. Fixed some display bugs.

  • 2024.01.25 (V1.3.0)

    Data updates

    • 1. 3416 cyclic peptide data (from CP05864 to CP09279) were obtained from ConoServer. ConoServer offers data on sequences, source organisms, classifications, and relevant references;
    • 2. Added detailed annotation information (Taxonomy ID and Wiki) of source organisms;
    • 3. Standardized the classifications of source, family, function, and target;
    • 4. Improved the structure-to-sequence, sequence-to-structure, structure/sequence format transformation, and peptide property calculation algorithms, and updated all codes on GitHub;
    • 5. Provided more detailed evidence for all information;
    • 6. Manually checked all collected data;
    • 7. Provided comprehensive download files;
    • 8. Recalculated data statistics;
    • 9. Other data optimization.

  • 2024.01.25 (V1.3.0)

    Backend development

    • 1. Added tools of sequence graph alignment, structure-to-sequence transformation, sequence-to-structure transformation, peptide property calculation, structure format transformation, sequence format transformation;
    • 2. Added advanced search function;
    • 3. Improved search and page loading speed;
    • 4. Optimization of other functions.

  • 2024.01.25 (V1.3.0)

    Front-end development

    • 1. Edited the homepage and simplified search logic;
    • 2. Added advanced search functions;
    • 3. Added and improved sequence retrieval, structure retrieval, sequence and structure calculation pages;
    • 4. Optimized the cyclic peptide details page;
    • 5. Edited the statistics page;
    • 6. Added the Browse section and search functions of Source;
    • 7. Used a new table plugin, providing sorting, search, and filtering functions in search results;
    • 8. Provided detailed information on the Datasource page;
    • 9. Updated Help Page;
    • 10. Edited other interfaces and fixed some issues.

  • 2023.06.15 (V1.2.0)

    Dataset

    • Add 1511 new cyclic peptide data from Cyber and Norine databases (from CP04345 to CP05863)
    • To supplement missing values in the database and correct incorrect values.

  • 2023.06.15 (V1.2.0)

    Back-end

    • Optimize the structure, sequence retrieval function, improve retrieval efficiency, add advanced retrieval function.

  • 2023.06.15 (V1.2.0)

    Front-end

      Add Classification Interface
    • 1. Based on the Family, Target, and Function fields, provide different classification interfaces.
    • 2. Users can choose a specific classification to view related lists of cyclic peptides.

    • Front-end interface optimization

  • 2023.03.15 (V1.1.0)

    Dataset

    The data of cyclic peptides were mainly from Pubchem, Drugbank, Uniprot, DRAMP3, APD3, DPL2, with a total of 3817, the data consisted of basic information of cyclic peptides (name, IUPAC name, formula, SMILES, Sequence, Family, Source, Target, Function, 3D structure and related literature) .

  • 2023.03.15 (V1.1.0)

    Back-end

      Data Model Design


      Database construction:
    • Establish multiple cyclic peptide data models, including basic information, structural information, sequence information, as well as classification tables for Family, Source, Target, and Function.

    • Data Import
    • Use scripts to import well-organized data into the database.

    • Index Creation
    • To improve retrieval speed, create indexes for certain fields (e.g., Sequence, Family) as needed.

    • Functional Logic Design Overview:

      Text Search
    • 1. User inputs keywords.
    • 2. The database performs fuzzy matching in all text fields (e.g., name, IUPAC name) and returns matching results.

    • Sequence Search
    • 1. User inputs or uploads a sequence.
    • 2. The database performs a comparison in the Sequence field and returns matching cyclic peptides.

    • Structure Search
    • 1. User uploads or specifies a structural formula.
    • 2. The database compares in the SMILES and 3D structure fields and returns matching cyclic peptides.

  • 2023.03.15 (V1.1.0)

    Front-end

    • This database home page provides 'Browse', 'Statistical Charts', 'Search', 'Help' and 'Download' and 'News' six sections, which browse provides a classified list of cyclic peptides and their targets, families, function, etc.

    • The relevant literature and DrugBank database can also be accessed by clicking“Browse-Reference/Drugbank”