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Related Experiment Videos

Practical evaluation of comparative modelling and threading methods

M J Schoonman1, R M Knegtel, P D Grootenhuis

  • 1Department of Molecular Design & Informatics, N.V. Organon, Oss, The Netherlands.

Computers & Chemistry
|October 27, 1998
PubMed
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Protein structure prediction tools were evaluated. Threading methods outperform comparative modeling for low sequence identity, but a gap remains. Including ligands improves active site accuracy in models.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Modeling

Background:

  • Accurate protein structure prediction is crucial for understanding biological function.
  • Evaluating the performance of different computational methods is essential for advancing the field.

Purpose of the Study:

  • To assess the accuracy of various protein structure prediction tools.
  • To compare threading and comparative modeling approaches.
  • To investigate the impact of ligands on active site model accuracy.

Main Methods:

  • Utilized six protein pairs with known 3D structures.
  • Generated sequence alignments using QUANTA, THREADER, 123D, and PHD Topits.
  • Built protein structure models with MODELLER.

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  • Assessed model accuracy using root mean square deviation (RMSD) and 3D profile scores.

    • Main Results:

    • Threading methods yielded more accurate models than comparative modeling for sequence identities below 30%.
    • A persistent 2 Å RMSD gap exists between theoretical best models and those from threading.
    • Comparative modeling with MODELLER produced accurate models for high sequence identities (>30%).
    • The 3D profile score was not consistently reliable in distinguishing correct folds.
    • Including ligands during model building prevented unrealistic active site filling.

    Conclusions:

    • Threading is superior for low sequence identity protein structure prediction.
    • Comparative modeling is effective for high sequence identity cases.
    • Ligand inclusion is vital for accurate active site modeling.