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Related Experiment Videos

Knowledge-based model building of proteins: concepts and examples

J Bajorath1, R Stenkamp, A Aruffo

  • 1Bristol-Myers Squibb, Pharmaceutical Research Institute, Seattle, Washington 98121.

Protein Science : a Publication of the Protein Society
|November 1, 1993
PubMed
Summary

Learn to build accurate protein models using structural templates, even with low sequence similarity. This guide emphasizes identifying and evaluating structural relationships for effective protein modeling and experimental applications.

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Area of Science:

  • Structural biology
  • Computational biology
  • Biophysics

Background:

  • Protein structure prediction is crucial for understanding protein function.
  • Comparative protein modeling relies on identifying homologous structures.
  • Challenges arise when sequence similarity is low or absent.

Purpose of the Study:

  • To outline methods for building protein models from structural templates.
  • To highlight the importance of detecting and evaluating structural relationships.
  • To present computational techniques for comparative protein modeling.

Main Methods:

  • Reviewing methods for identifying structural similarities across varying sequence identities.
  • Discussing computational approaches for generating and refining comparative models.

Related Experiment Videos

  • Illustrating model derivation using P-selectin and gp39 examples.

    • Main Results:

    • Demonstrated successful protein model construction from templates.
    • Showcased techniques applicable to diverse sequence similarity levels.
    • Provided practical examples of model application in experimental studies.

    Conclusions:

    • Structural relationship evaluation is key to successful protein modeling.
    • Comparative modeling is feasible even without significant sequence similarity.
    • Derived protein models aid in experimental design and interpretation.