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ArchPRED: a template based loop structure prediction server.

Narcis Fernandez-Fuentes1, Jun Zhai, András Fiser

  • 1Department of Biochemistry and Seaver Foundation Center for Bioinformatics, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.

Nucleic Acids Research
|July 18, 2006
PubMed
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ArchPRED server predicts protein loop conformations using a novel fragment-search method. This approach accurately models protein structures, outperforming previous methods in loop prediction accuracy.

Area of Science:

  • Structural Bioinformatics
  • Computational Biology
  • Protein Structure Prediction

Background:

  • Protein loops are crucial for protein function and stability.
  • Accurate prediction of loop conformations is essential for understanding protein dynamics and designing novel proteins.

Purpose of the Study:

  • To introduce the ArchPRED server, a novel tool for predicting protein loop conformations.
  • To evaluate the performance of the ArchPRED method using benchmark datasets and compare it with existing approaches.

Main Methods:

  • Fragment-search based algorithm utilizing a loop library.
  • Incorporation of secondary structure matching and geometric restraints.
  • Side chain rebuilding, clash detection, and Z-score ranking for loop selection.

Related Experiment Videos

  • Final loop conformation refinement using conjugate gradient minimization.

    • Main Results:

    • ArchPRED achieved high prediction coverage for loops of varying lengths (98% for length 4, 78% for length 8, 28% for length 12).
    • Accurate root mean square deviation (r.m.s.d.) values were obtained (0.22 Å for length 4, 1.38 Å for length 8, 2.47 Å for length 12).
    • The method demonstrated superior performance compared to an earlier database search method, outperforming it approximately 5:1.

    Conclusions:

    • The ArchPRED server provides an effective and accurate method for predicting protein loop conformations.
    • The fragment-search approach offers significant improvements in loop modeling accuracy and coverage.
    • ArchPRED is a valuable tool for structural bioinformatics and computational biology research.