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Related Experiment Videos

Development of KiBank, a database supporting structure-based drug design.

Junwei Zhang1, Masahiro Aizawa, Shinji Amari

  • 1Collaborative Research Center of Frontier Simulation Software for Industrial Science, Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan. cho@fsis.iis.u-tokyo.ac.jp

Computational Biology and Chemistry
|November 24, 2004
PubMed
Summary

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KiBank is a freely accessible database containing inhibition constant (Ki) values and 3D structures for drug design. It supports structure-based drug design, virtual screening, and quantitative structure-activity relationship (QSAR) analysis.

Area of Science:

  • Biochemistry
  • Medicinal Chemistry
  • Structural Biology

Background:

  • Drug discovery relies on understanding molecular interactions.
  • Databases integrating chemical and protein data are crucial for structure-based drug design.
  • Existing resources may lack comprehensive, optimized 3D structures and associated bioactivity data.

Purpose of the Study:

  • To create KiBank, a curated database of inhibition constant (Ki) values and 3D structures.
  • To provide optimized protein and chemical structures for computational drug design.
  • To facilitate structure-based drug design, virtual screening, and QSAR studies.

Main Methods:

  • Ki values were collected from peer-reviewed literature via PubMed.
  • Protein 3D structures were sourced from the Protein Data Bank (PDB).

Related Experiment Videos

  • Chemical 2D structures were converted to 3D, and all structures were energy-minimized.

    • Main Results:

    • KiBank contains over 8000 Ki values, 6000+ chemicals, and 166 proteins (as of August 2004).
    • Protein and chemical structures are provided in PDB and MDL MOL formats, respectively.
    • The database is updated daily and is freely available online.

    Conclusions:

    • KiBank serves as a valuable resource for structure-based drug design.
    • The integrated data supports virtual screening, docking studies, and QSAR analysis.
    • The database facilitates lead optimization and accelerates the drug discovery process.