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Related Experiment Videos

Prediction of protein structural classes

K C Chou1, C T Zhang

  • 1Computer-Aided Drug Discovery, Upjohn Laboratories, Kalamazoo, MI 49007-4940, USA.

Critical Reviews in Biochemistry and Molecular Biology
|January 1, 1995
PubMed
Summary
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Predicting protein structural class from amino acid composition is possible. A novel algorithm and database show high success rates, suggesting composition dictates protein fold.

Area of Science:

  • Biochemistry
  • Structural Biology
  • Bioinformatics

Background:

  • Proteins are classified into five structural classes: alpha, beta, alpha + beta, alpha/beta, and zeta (irregular).
  • Protein structural class correlates with amino acid composition, but direct prediction remains a challenge.

Purpose of the Study:

  • To review advancements in predicting protein structural class from amino acid composition.
  • To highlight a novel prediction algorithm and a recently developed database.

Main Methods:

  • A new prediction algorithm utilizing a covariance matrix to account for amino acid coupling effects.
  • A curated database of nonhomologous, high-quality protein structures with distinguishable class features.

Main Results:

Related Experiment Videos

  • The novel algorithm and database achieved very high success rates on both training and testing datasets.
  • Validation through simulated and jackknife analyses confirmed the algorithm's predictive power.

Conclusions:

  • Protein structural class can be accurately predicted from amino acid composition with an ideal database.
  • Amino acid composition fundamentally determines a protein's overall fold.