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ProQ3D: improved model quality assessments using deep learning.

Karolis Uziela1, David Menéndez Hurtado1, Nanjiang Shu1,2

  • 1Department of Biochemistry and Biophysics and Science for Life Laboratory, Stockholm University, Solna, Sweden.

Bioinformatics (Oxford, England)
|January 6, 2017
PubMed
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This study enhances protein quality assessment using deep neural networks, achieving a Pearson correlation of 0.90. This bioinformatics advancement significantly improves prediction accuracy over previous machine learning methods.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Machine Learning

Background:

  • Protein quality assessment is a critical challenge in bioinformatics.
  • Previous methods like ProQ, ProQ2, and ProQ3 have incrementally improved prediction accuracy using machine learning.
  • These improvements were mainly driven by incorporating a larger set of finely-tuned protein descriptors.

Purpose of the Study:

  • To investigate the impact of replacing traditional machine learning algorithms with deep neural networks for protein quality assessment.
  • To evaluate if deep neural networks can further enhance prediction accuracy using existing protein features.

Main Methods:

  • Utilized the same input features as ProQ2 and ProQ3.
  • Replaced the support vector machine (SVM) with a deep neural network (DNN).

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  • Evaluated prediction performance using Pearson correlation coefficient.

    • Main Results:

    • Achieved a Pearson correlation of 0.90 with the deep neural network approach.
    • This represents a substantial improvement over ProQ3's correlation of 0.85.
    • Even with ProQ2 input features, the DNN achieved a correlation of 0.85.

    Conclusions:

    • Deep neural networks offer a significant advancement in protein quality assessment compared to traditional machine learning methods.
    • The findings demonstrate the potential of DNNs to improve bioinformatics predictions with existing data features.
    • ProQ3D, implementing this DNN approach, is available as a webserver and stand-alone program.