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Related Experiment Video

Updated: Apr 16, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

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Published on: July 14, 2015

Nonadaptive Amino Acid Convergence Rates Decrease over Time.

Richard A Goldstein¹, Stephen T Pollard², Seena D Shah²

¹Division of Infection & Immunity, University College London, London, United Kingdom.

Molecular Biology and Evolution

|March 5, 2015

Summary

This summary is machine-generated.

Nonadaptive convergence is surprisingly common in closely related organisms, decreasing as they diverge. This finding challenges assumptions about adaptive evolution and improves evolutionary models.

Keywords:

Stokes shift Stokes–Fisher model adaptation amino acid propensities coevolution convergence epistasis epistatic interactions evolutionary process molecular evolution phylogenetics selection thermodynamics

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Published on: January 26, 2024

Area of Science:

Evolutionary biology
Molecular evolution
Phylogenetics

Background:

Convergence is key evidence for adaptation in evolutionary studies.
Understanding nonadaptive convergence is crucial for interpreting adaptive convergence.
Convergence can impact phylogenetic inference.

Purpose of the Study:

To investigate the patterns of nonadaptive convergence in mitochondrial and model proteins.
To compare nonadaptive convergence with divergence in closely related organisms.
To evaluate the predictive power of different evolutionary models for convergence.

Main Methods:

Analysis of nonadaptive convergence and divergence in mitochondrial and model proteins.
Application of "evolutionary Stokes shift" models and conventional evolutionary models.
Examination of convergence probabilities based on ancestral amino acid divergence and evolutionary rate.

Main Results:

Nonadaptive convergence is more frequent than expected in closely related organisms, diminishing with divergence.
Epistatic or coevolutionary effects better predict convergence drop-off in mitochondrial proteins than conventional models.
Convergence probabilities decrease significantly with ancestral amino acid divergence and evolutionary time, especially for rapidly evolving sites.

Conclusions:

Early convergence does not necessarily indicate adaptation.
The study provides insights into discriminating adaptive from nonadaptive convergence.
Improved evolutionary models with better phylogenetic inference validity can be developed.