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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Related Experiment Video

Updated: Jun 12, 2026

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

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles.

Morten Nielsen1, Claus Lundegaard, Ole Lund

  • 1Center for Biological Sequence Analysis, Department of systems Biology, The Technical University of Denmark, Denmark.

Nucleic Acids Research
|June 15, 2010
PubMed
Summary
This summary is machine-generated.

CPHmodels-3.0 predicts protein 3D structures using homology modeling. This fast and accurate web server, suitable for both close and remote homology modeling, achieved high reliability in the CASP8 competition.

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Last Updated: Jun 12, 2026

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein structure prediction

Background:

  • Homology modeling is crucial for determining protein 3D structures when experimental data is unavailable.
  • Existing methods often struggle with remote homology detection, limiting their accuracy for distantly related proteins.

Purpose of the Study:

  • To introduce CPHmodels-3.0, an enhanced web server for protein 3D structure prediction.
  • To improve upon previous homology modeling techniques by incorporating a novel remote homology-modeling algorithm.

Main Methods:

  • CPHmodels-3.0 utilizes a hybrid approach combining CPHmodels-2.0 scoring functions with a new remote homology algorithm.
  • A fast profile-profile scoring function is used for initial close homology modeling.
  • A computationally intensive remote homology algorithm is employed only when no close template is found.

Main Results:

  • CPHmodels-3.0 successfully modeled 94% of targets in the CASP8 competition.
  • 74% of predicted models were classified as high reliability with an average RMSD of 4.6 Å.
  • The server demonstrates high performance and speed, with most queries completed in under 20 minutes.

Conclusions:

  • CPHmodels-3.0 is a highly accurate and efficient tool for protein 3D structure prediction.
  • The server's hybrid approach effectively handles both close and remote homology modeling scenarios.
  • CPHmodels-3.0 represents a significant advancement in computational protein structure prediction tools.