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HHfrag: HMM-based fragment detection using HHpred.

Ivan Kalev1, Michael Habeck

  • 1Department of Protein Evolution and Department of Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany.

Bioinformatics (Oxford, England)
|October 4, 2011
PubMed
Summary
This summary is machine-generated.

HHfrag is a new dynamic fragment search method for protein structure prediction. It improves fragment precision and detects variable-length, gapped fragments, aiding in more accurate protein modeling.

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Structure Prediction

Background:

  • Fragment libraries are crucial for protein structure prediction.
  • Static libraries extract universal structural alphabets.
  • Dynamic libraries provide query-specific local structural templates.

Purpose of the Study:

  • Introduce HHfrag, a novel dynamic fragment search method.
  • Enhance fragment assignment for improved protein structure prediction.
  • Leverage profile-profile comparisons for fragment detection.

Main Methods:

  • Developed HHfrag, a dynamic HMM-based fragment search tool.
  • Utilized HHpred for profile-profile comparisons.
  • Evaluated fragment detection on recent CASP targets.

Main Results:

  • HHfrag improves fragment precision with minimal loss in sequence coverage.
  • Detected fragments range from 6 to 21 amino acid residues.
  • HHfrag supports gapped fragments and avoids assignment in non-conserved regions.

Conclusions:

  • HHfrag offers significant advantages over existing fragment assignment methods.
  • The method enhances the accuracy of protein structure prediction.
  • HHfrag is a valuable tool for computational structural biology.