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How is structural divergence related to evolutionary information?

Diego Javier Zea1, Alexander Miguel Monzon2, Gustavo Parisi2

  • 1Structural Bioinformatics Unit, Fundación Instituto Leloir, CONICET, C1405BWE, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina.

Molecular Phylogenetics and Evolution
|June 29, 2018
PubMed
Summary
This summary is machine-generated.

Integrating protein structural diversity improves evolutionary analysis. Considering multiple protein structures enhances the interpretation of sequence-based evolutionary data, leading to better insights into protein function and evolution.

Keywords:
CoevolutionConformational diversityConservationSolvent accessibilityStructural divergence

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Area of Science:

  • Protein bioinformatics
  • Structural biology
  • Evolutionary genomics

Background:

  • Evolutionary analysis of protein families often integrates sequence and structural data.
  • Existing methods frequently use single protein structures, overlooking family-wide structural variability.

Purpose of the Study:

  • To investigate the impact of structural divergence on integrating sequence-based evolutionary measures with structural information.
  • To determine if considering multiple protein structures enhances evolutionary analysis.

Main Methods:

  • Analysis of evolutionary variables (conservation, covariation) from multiple sequence alignments.
  • Assessment of structural properties like inter-residue contacts and solvent accessibility across protein families.
  • Comparison of evolutionary data interpretation using single versus multiple protein structures.

Main Results:

  • Inter-residue contacts and solvent accessibility exhibit significant variation within protein families.
  • High covariation scores correlate with family-conserved residue contacts.
  • Mean relative solvent accessibility across multiple structures better reflects conservation patterns than single-structure accessibility.

Conclusions:

  • Comprehensive structural information, including divergence, is crucial for accurate interpretation of sequence-based evolutionary data.
  • Incorporating structural variability improves understanding of protein function, dynamics, and evolution.