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Related Experiment Videos

Protein structure prediction.

B Al-Lazikani1, J Jung, Z Xiang

  • 1Department of Biochemistry and Molecular Biophysics, Howard Hughes Medical Institute, Columbia University, 630 West 168th Street, New York, NY 10032, USA.

Current Opinion in Chemical Biology
|February 13, 2001
PubMed
Summary
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Protein structure prediction using homology modeling is improving due to increased sequence and structure data. Advances in analysis tools and understanding protein stability enhance model accuracy.

Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational chemistry

Background:

  • Protein structure prediction is crucial for understanding biological function.
  • Homology modeling relies on sequence and structural similarities between proteins.
  • Recent years have seen a surge in available protein sequence and structure data.

Purpose of the Study:

  • To review advancements in protein structure prediction, particularly homology modeling.
  • To highlight improvements in analysis tools and methodologies.
  • To discuss the role of physical chemistry in validating protein conformations.

Main Methods:

  • Utilizing sequence and structure homology for model building.
  • Employing profile methods for enhanced sequence searches.

Related Experiment Videos

  • Integrating 3D structure information into sequence alignment.
  • Developing novel tools for loop and side-chain conformation prediction.
  • Applying physical chemical potential functions to assess protein stability and folding accuracy.

    • Main Results:

    • Homology models have demonstrated increased accuracy and broader applicability.
    • Profile methods improve sequence search sensitivity.
    • New tools enhance the prediction of complex structural features like loops and side chains.
    • Understanding protein stability through physical chemistry aids in identifying correct protein folds.

    Conclusions:

    • Significant progress in protein structure prediction is driven by data availability and methodological improvements.
    • Enhanced computational tools and a deeper understanding of protein stability are key to accurate modeling.
    • These advancements facilitate a more comprehensive understanding of protein function and disease mechanisms.