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Summary
This summary is machine-generated.

New protein evolution models (SSCPE) incorporate structural changes, improving evolutionary variability predictions and phylogenetic inference accuracy compared to previous stability-only models.

Keywords:
SSCPE modelSubstitution modelphylogenetic inferenceprotein folding stabilityprotein structure evolutionstructure and stability constrained protein evolution

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Area of Science:

  • Computational Biology
  • Protein Evolution
  • Bioinformatics

Background:

  • Previous Stability Constrained substitution models of Protein Evolution (Stab-CPE) defined protein fitness by native state probability but ignored structural changes.
  • Stab-CPE models showed limitations, differing qualitatively from observed data and being too tolerant to mutations.

Purpose of the Study:

  • To develop novel Structure and Stability Constrained substitution models of Protein Evolution (SSCPE) that incorporate structural deformation into fitness definitions.
  • To evaluate the performance of SSCPE models in predicting protein evolutionary variability and inferring phylogenies.

Main Methods:

  • Developed structurally constrained substitution models (Str-CPE) using an extension of a linearly forced elastic network model to predict fitness based on structural deformation.
  • Combined Str-CPE with previous Stab-CPE models to create the comprehensive SSCPE models.
  • Implemented SSCPE models in a PERL-based program (SSCPE.pl) utilizing RAxML-NG for phylogenetic inference.

Main Results:

  • SSCPE models are more stringent than Stab-CPE, predicting lower sequence entropy and substitution rates.
  • SSCPE models provide higher likelihood to multiple sequence alignments (MSAs) with known structures and better predict observed site conservation.
  • SSCPE models yielded phylogenies more similar to reference phylogenies inferred from structural distances for distantly-related proteins.

Conclusions:

  • SSCPE models offer a more accurate and stringent approach to modeling protein evolution by integrating structural and stability constraints.
  • These models significantly improve the fit to empirical data and enhance the accuracy of deep phylogeny inference.
  • The SSCPE models and associated software provide a valuable tool for researchers studying protein evolution and phylogenetics.