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Updated: Jun 10, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

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Published on: November 3, 2011

Recognizing protein substructure similarity using segmental threading.

Sitao Wu1, Yang Zhang

  • 1Center for Bioinformatics and Department of Molecular Bioscience, University of Kansas, 2030 Becker Drive, Lawrence, KS 66047, USA.

Structure (London, England : 1993)
|July 20, 2010
PubMed
Summary
This summary is machine-generated.

SEGMER identifies protein substructure similarities using segmental threading, improving protein structure prediction accuracy. This method enhances template identification for better protein structure and function inference.

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Area of Science:

  • Computational Biology
  • Structural Biology
  • Bioinformatics

Background:

  • Protein template identification is crucial for predicting protein structure and function.
  • Conventional whole-chain threading methods struggle with identifying conserved substructures when protein folds differ.

Purpose of the Study:

  • To introduce SEGMER, a novel segmental threading approach for identifying protein substructure similarities.
  • To evaluate SEGMER's effectiveness in improving protein structure modeling and functional inference.

Main Methods:

  • SEGMER splits target sequences into segments of secondary structural elements.
  • These segments are threaded through the Protein Data Bank (PDB) to find matching substructure motifs.
  • The approach was tested on 144 nonredundant hard proteins and 12 CASP8 free modeling targets.

Main Results:

  • Combining SEGMER with whole-chain threading improved alignment TM-scores by 16% and spatial restraint accuracy by 25%.
  • For free modeling targets, SEGMER increased TM-score by 28% and contact accuracy by 48%.
  • SEGMER significantly enhances the accuracy of protein structure modeling and functional inference.

Conclusions:

  • SEGMER offers a significant advancement in identifying protein substructure similarities.
  • The segmental threading approach improves upon traditional whole-chain methods, especially for proteins with dissimilar folds.
  • This method has substantial implications for computational protein structure prediction and understanding protein function.