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A Protocol for Computer-Based Protein Structure and Function Prediction
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Protein model discrimination attempts using mutational sensitivity, predicted secondary structure, and model quality

Shruti Khare1, Munmun Bhasin1, Anusmita Sahoo1

  • 1Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.

Proteins
|January 8, 2019
PubMed
Summary

Distinguishing correct protein structures from decoys is challenging. This study shows that combining experimental mutational sensitivity data with computational scores like DOPE improves protein model discrimination.

Keywords:
CASPDOPEdeep sequencingmodel rankingprotein foldingsaturation mutagenesis

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Area of Science:

  • Computational Biology
  • Structural Biology
  • Protein Science

Background:

  • Protein structure prediction methods generate numerous models, making it difficult to identify the correct fold among decoys.
  • Previous work showed a correlation between residue depth and mutational sensitivity for CcdB protein.

Purpose of the Study:

  • To assess if mutational sensitivity, predicted secondary structure, and DOPE score improve protein model discrimination.
  • To extend the correlation of residue depth with mutational sensitivity to other proteins.

Main Methods:

  • Applied a combination of experimental mutational sensitivity data, predicted secondary structure, and DOPE score.
  • Utilized a decoy dataset of 163 targets from the Critical Assessment of protein Structure Prediction (CASP).
  • Validated the approach on CcdB and four other proteins with available experimental mutational data.

Main Results:

  • The correlation between residue depth and mutational sensitivity was extended to four additional proteins.
  • Incorporating DOPE score and predicted secondary structure significantly improved model discrimination accuracy.
  • Experimental mutational data provided a small qualitative improvement over DOPE score alone.

Conclusions:

  • A combination of computational and experimental data enhances protein model discrimination.
  • The DOPE score is a substantial contributor to improved model accuracy.
  • Further methodological advancements are needed for better utilization of single mutant data in protein structure prediction.