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Related Experiment Videos

Modeling protein structures: construction and their applications

C S Ring1, F E Cohen

  • 1Department of Pharmaceutical Chemistry, University of California, San Francisco 94143-0446.

FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology
|June 1, 1993
PubMed
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Protein structure prediction is advancing with experimental data and computational methods. This study successfully modeled proteases, leading to the discovery of potent small molecule enzyme inhibitors.

Area of Science:

  • Structural biology
  • Computational chemistry
  • Drug discovery

Background:

  • The protein folding problem remains a significant challenge in biology.
  • Experimental constraints and heuristic methods improve 3D structure prediction.
  • Interleukin-4 structure determination utilized mutagenesis and CD spectroscopy.

Purpose of the Study:

  • To accurately predict protein structures using experimental data and computational modeling.
  • To model proteases relevant to parasitic diseases.
  • To identify potential small molecule enzyme inhibitors.

Main Methods:

  • Utilizing mutagenesis data and circular dichroism (CD) spectroscopy for secondary structure assignment.
  • Employing modeling by homology with known protein structures as templates.

Related Experiment Videos

  • Computational identification of putative small molecule enzyme inhibitors.

    • Main Results:

    • Accurate assignment of secondary and tertiary structures for interleukin-4.
    • Successful modeling of serine and cysteine proteases involved in schistosome and malaria.
    • Identification of nonpeptidic compounds active at low micromolar concentrations.

    Conclusions:

    • Experimental constraints are crucial for accurate protein structure prediction.
    • Homology modeling is effective for predicting structures of related proteins.
    • Computational approaches can successfully identify novel enzyme inhibitors.