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Protein threading by recursive dynamic programming.

R Thiele1, R Zimmer, T Lengauer

  • 1German National Research Center for Information Technology (GMD), Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Sankt Augustin, D-53754, Germany.

Journal of Molecular Biology
|July 9, 1999
PubMed
Summary
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The recursive dynamic programming (RDP) method accurately predicts three-dimensional protein structures by mapping target sequences onto template structures. This efficient threading approach outperforms existing methods, aiding in modeling protein active sites.

Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Biochemistry

Background:

  • Protein structure prediction is crucial for understanding protein function.
  • Existing methods for three-dimensional protein structure prediction have limitations.
  • Threading approaches offer a promising avenue for structure prediction.

Purpose of the Study:

  • To introduce and evaluate the recursive dynamic programming (RDP) method for protein structure prediction.
  • To demonstrate the efficiency and effectiveness of RDP in threading protein sequences onto known structures.
  • To highlight RDP's utility in modeling protein active sites.

Main Methods:

  • The RDP method employs a divide-and-conquer strategy for stepwise mapping of target sequences onto template structures.

Related Experiment Videos

  • It utilizes cost functions similar to local alignments but adapted for structural mapping.
  • The process recursively identifies and maps similar segments, modifying the template and interpreting unmapped regions as gaps.

    • Main Results:

    • RDP efficiently threads protein sequences against large databases (e.g., 887 domains in ~12 hours on a low-cost workstation).
    • Statistical evaluations show RDP significantly outperforms competing protein threading methods.
    • The method provides accurate alignments, particularly valuable for modeling protein active sites.

    Conclusions:

    • The RDP method is an efficient and effective tool for three-dimensional protein structure prediction.
    • Its robustness allows for flexibility in alignment methods, mapping strategies, and cost function adaptation.
    • RDP, integrated into the ToPLign system, is accessible online and valuable for structural bioinformatics research.