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Related Experiment Video

Updated: Jun 23, 2026

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

QMEAN server for protein model quality estimation.

Pascal Benkert¹, Michael Künzli, Torsten Schwede

¹Biozentrum, University of Basel, Switzerland.

Nucleic Acids Research

|May 12, 2009

Summary

This summary is machine-generated.

Model quality estimation is crucial for protein structure prediction. The QMEAN server offers two scoring functions, QMEAN and QMEANclust, to assess model accuracy and identify problematic regions.

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Area of Science:

Computational biology
Structural bioinformatics

Background:

Accurate protein structure prediction is vital for understanding biological function and disease mechanisms.
Selecting the most accurate model from a set of predictions is a critical step in the protein structure prediction pipeline.

Purpose of the Study:

To provide a web server (QMEAN) offering two validated scoring functions for protein model quality estimation.
To enable users to assess the global and local accuracy of protein models and identify potentially erroneous regions.

Main Methods:

Implementation of the QMEAN composite scoring function based on geometrical analysis of single models.
Development of the QMEANclust clustering-based scoring function utilizing all-against-all model comparisons.
Integration of these functions into a user-friendly web server for model ranking and analysis.

Main Results:

The QMEAN and QMEANclust scoring functions were successfully tested in the CASP8 experiment.
The QMEAN server provides a ranking of input protein models.
The server highlights regions with potential inaccuracies within each model.

Conclusions:

The QMEAN server offers reliable tools for assessing protein model quality.
Accurate model quality estimation aids in selecting the most useful protein structure predictions for downstream applications.
The QMEAN server facilitates the identification of potentially problematic regions, guiding further refinement or interpretation.