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Related Experiment Videos

Protein structure prediction by threading. Why it works and why it does not

L A Mirny1, E I Shakhnovich

  • 1Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA, 02138, USA.

Journal of Molecular Biology
|October 14, 1998
PubMed
Summary

A new Monte Carlo threading algorithm accurately aligns protein sequences and structures. Its success depends on template similarity, with robust results for close templates and variable outcomes for distant ones.

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Folding

Background:

  • Protein threading is crucial for predicting protein structure and function.
  • Accurate sequence-structure alignment is essential for reliable protein threading.

Purpose of the Study:

  • To develop a novel Monte Carlo threading algorithm capable of handling gaps and insertions.
  • To analyze the impact of template similarity and potential accuracy on threading alignment outcomes.

Main Methods:

  • Developed a Monte Carlo threading algorithm allowing gaps and insertions in sequences and structures.
  • Performed sequence-structure alignments using "ideal" and knowledge-based potentials for ubiquitin, immunoglobulin, and globin folds.
  • Analyzed alignment behavior based on root-mean-square deviation (RMSD) between template and native structures.

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Main Results:

  • For templates within 2 Å RMSD of native structures, optimal alignments were robust and cooperative transitions to optimal alignment were observed.
  • For templates >3.5 Å RMSD, optimal alignments varied significantly with potential type, and suboptimal alignments were unreliable.
  • Intermediate RMSD ranges (2-3.5 Å) showed potential quality significantly influencing threading success.

Conclusions:

  • The accuracy and reliability of protein threading depend heavily on the similarity between the template structure and the native protein structure.
  • The developed algorithm provides insights into the free energy landscape of threading, highlighting limitations and potential improvements.