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Fold recognition by scoring protein maps using the congruence coefficient.

Pietro Di Lena1, Pierre Baldi2,3

  • 1Department of Computer Science and Engineering, University of Bologna, Bologna 40126, Italy.

Bioinformatics (Oxford, England)
|September 25, 2020
PubMed
Summary
This summary is machine-generated.

We introduce the congruence coefficient, a novel metric for comparing protein contact and distance maps. This method significantly improves protein fold recognition, especially for distantly related proteins, outperforming existing techniques.

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Structure Prediction

Background:

  • Protein fold recognition is crucial for template-based protein structure prediction.
  • Identifying distantly related protein homologs is challenging using sequence homology alone.
  • Predicted residue-residue contact and distance maps offer potential for improved fold recognition.

Purpose of the Study:

  • To develop and evaluate a new metric, the congruence coefficient, for assessing similarity between protein contact and distance maps.
  • To improve the accuracy and efficiency of protein fold recognition, particularly for distantly related proteins.

Main Methods:

  • The congruence coefficient was proposed as a similarity metric for symmetric matrices (contact/distance maps).
  • Mathematical properties of the congruence coefficient were analyzed, enabling efficient computation of its mean, variance, and statistical significance.
  • Fold recognition tests were conducted using predicted maps from recent Critical Assessment of Structure Prediction (CASP) studies and the ECOD database.

Main Results:

  • The congruence coefficient demonstrated superior performance in fold recognition compared to existing alignment tools and their similarity scores.
  • This metric effectively assesses the statistical significance of map similarity over all possible alignments.
  • Performance was validated on a large benchmark of over 27,000 non-homologous structural templates.

Conclusions:

  • The congruence coefficient is an effective and mathematically robust metric for comparing protein maps.
  • It significantly enhances protein fold recognition, offering a valuable tool for structural bioinformatics.
  • The CCpro software is available as part of the SCRATCH suite.