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Related Experiment Videos

Calmodulin target database.

K L Yap1, J Kim, K Truong

  • 1Division of Molecular and Structural Biology, Ontario Cancer Institute and Department of Medical Biophysics, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada.

Journal of Structural and Functional Genomics
|July 3, 2003
PubMed
Summary

Researchers created a database for calmodulin (CaM) binding sites, called CaM recruitment signaling (CRS) motifs. This tool classifies these motifs into four subclasses, aiding in understanding CaM-protein interactions.

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Area of Science:

  • Molecular Biology
  • Biochemistry
  • Structural Biology

Background:

  • Calmodulin (CaM) is a crucial intracellular calcium sensor protein.
  • CaM regulates diverse protein functions through calcium-dependent interactions.
  • CaM-protein recognition mechanisms are varied but can be classified structurally.

Purpose of the Study:

  • To develop a comprehensive web-based database for CaM binding sites, termed CaM recruitment signaling (CRS) motifs.
  • To classify known CRS motifs into distinct subclasses based on structural and sequence information.
  • To provide a tool for predicting CRS motif location and subclass within novel protein sequences.

Main Methods:

  • Development of a web-based database (http://calcium.uhnres.utoronto.ca/ctdb).

Related Experiment Videos

  • Analysis of approximately 180 protein sequences containing CRS motifs.
  • Classification of CRS motifs into four subclasses representing different recognition modes.
  • Implementation of predictive algorithms for CRS location and subclass identification.
  • Inclusion of structural and biophysical parameters (hydrophobicity, hydrophobic moment, alpha-helix propensity).

    • Main Results:

    • The database currently contains information on approximately 180 protein sequences with CRS motifs.
    • CRS motifs are categorized into four distinct subclasses, each reflecting a unique CaM molecular recognition strategy.
    • The database enables prediction of potential CRS motif locations and their corresponding subclasses.
    • Key biophysical parameters associated with CRS motifs are provided for further analysis.

    Conclusions:

    • The developed database serves as a valuable resource for studying CaM-protein interactions.
    • Classification of CRS motifs provides insights into the diverse mechanisms of CaM molecular recognition.
    • The predictive capabilities of the database facilitate the identification and characterization of novel CaM-binding proteins.