QMEAN

Regarding protein structure prediction, model quality estimation is an essential step. It is crucial to have accurate models to ensure their usefulness for specific applications. During the protein structure prediction process, alternative models are usually produced, and then the most accurate model is chosen. The QMEAN server provides access to two scoring functions that have been successfully tested at the eighth round of the community-wide blind test experiment CASP.

The QMEAN server offers two scoring functions, the composite scoring function QMEAN and the clustering-based scoring function QMEANclust. The QMEAN function derives a quality estimate based on the geometrical analysis of single models. On the other hand, the QMEANclust function calculates a global and local quality estimate based on a weighted all-against-all comparison of the models from the ensemble provided by the user.

The QMEAN server also allows ranking input models and highlighting problematic regions for each model. This feature can be extremely helpful in identifying areas that require further analysis and improvement.

Topic

Microarray experiment;Biobank;Human biology;Transcription factors and regulatory sites;Sample collections

Detail

  • Operation: Protein modelling;Protein modelling (mutation);Functional clustering;Protein model validation

  • Software interface: Web application

  • Language: -

  • License: Attribution-ShareAlike 4.0 International

  • Cost: Free

  • Version name: -

  • Credit: -

  • Input: PDB format or tar.gz-archives

  • Output: -

  • Contact: Gabriel Studer gabriel.studer@unibas.ch

  • Collection: -

  • Maturity: Mature

Publications

  • QMEAN: A comprehensive scoring function for model quality assessment.
  • Benkert P, et al. QMEAN: A comprehensive scoring function for model quality assessment. QMEAN: A comprehensive scoring function for model quality assessment. 2008; 71:261-77. doi: 10.1002/prot.21715
  • https://doi.org/10.1002/prot.21715
  • PMID: 17932912
  • PMC: -
  • Global and local model quality estimation at CASP8 using the scoring functions QMEAN and QMEANclust.
  • Benkert P, et al. Global and local model quality estimation at CASP8 using the scoring functions QMEAN and QMEANclust. Global and local model quality estimation at CASP8 using the scoring functions QMEAN and QMEANclust. 2009; 77 Suppl 9:173-80. doi: 10.1002/prot.22532
  • https://doi.org/10.1002/prot.22532
  • PMID: 19705484
  • PMC: -
  • Toward the estimation of the absolute quality of individual protein structure models.
  • Benkert P, et al. Toward the estimation of the absolute quality of individual protein structure models. Toward the estimation of the absolute quality of individual protein structure models. 2011; 27:343-50. doi: 10.1093/bioinformatics/btq662
  • https://doi.org/10.1093/bioinformatics/btq662
  • PMID: 21134891
  • PMC: PMC3031035
  • Assessing the local structural quality of transmembrane protein models using statistical potentials (QMEANBrane).
  • Studer G, et al. Assessing the local structural quality of transmembrane protein models using statistical potentials (QMEANBrane). Assessing the local structural quality of transmembrane protein models using statistical potentials (QMEANBrane). 2014; 30:i505-11. doi: 10.1093/bioinformatics/btu457
  • https://doi.org/10.1093/bioinformatics/btu457
  • PMID: 25161240
  • PMC: PMC4147910
  • QMEANDisCo-distance constraints applied on model quality estimation.
  • Studer G, et al. QMEANDisCo-distance constraints applied on model quality estimation. QMEANDisCo-distance constraints applied on model quality estimation. 2020; 36:1765-1771. doi: 10.1093/bioinformatics/btz828
  • https://doi.org/10.1093/bioinformatics/btz828
  • PMID: 31697312
  • PMC: PMC7075525
  • QMEAN server for protein model quality estimation.
  • Benkert P, et al. QMEAN server for protein model quality estimation. QMEAN server for protein model quality estimation. 2009; 37:W510-4. doi: 10.1093/nar/gkp322
  • https://doi.org/10.1093/nar/gkp322
  • PMID: 19429685
  • PMC: PMC2703985

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