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Related Experiment Videos

Knowledge-based protein modeling

M S Johnson1, N Srinivasan, R Sowdhamini

  • 1Imperial Cancer Research Fund, Department of Crystallography, Birkbeck College, London.

Critical Reviews in Biochemistry and Molecular Biology
|January 1, 1994
PubMed
Summary
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Protein structure modeling uses known homologous proteins and general structural analysis to predict unknown protein structures. Automated methods, including fragment assembly and restraint satisfaction, are increasingly employed alongside manual techniques.

Area of Science:

  • Structural biology
  • Computational biology
  • Biophysics

Background:

  • Protein structure prediction is crucial for understanding biological function.
  • Homologous protein structures and general structural principles provide valuable data.
  • Manual modeling methods are being supplemented by automated approaches.

Purpose of the Study:

  • To outline the value of existing structural knowledge in modeling proteins.
  • To highlight the increasing use of automated procedures in protein modeling.
  • To describe common automated protein modeling strategies.

Main Methods:

  • Utilizing three-dimensional structures of homologous proteins.
  • Applying general analysis of protein structure.
  • Employing automated procedures such as fragment assembly.

Related Experiment Videos

  • Deriving atomic coordinates through satisfaction of positional restraints.

    • Main Results:

    • Knowledge from homologous proteins aids in modeling proteins of unknown structure.
    • Automated procedures are becoming more prevalent in protein modeling.
    • Fragment assembly and restraint satisfaction are key automated techniques.

    Conclusions:

    • Leveraging existing structural data and computational methods enhances protein modeling.
    • Automated strategies offer efficient alternatives or complements to manual modeling.
    • Protein structure modeling benefits from integrating diverse knowledge sources and techniques.