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Related Experiment Video

Updated: Feb 20, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Molecular ensembles make evolution unpredictable.

Zachary R Sailer^1,2, Michael J Harms^3,2

¹Institute of Molecular Biology, University of Oregon, Eugene, OR 97403-1253.

Proceedings of the National Academy of Sciences of the United States of America

|October 29, 2017

Summary

This summary is machine-generated.

Protein evolution is unpredictable, even with complete mutation data. Conformational ensembles and high-order epistasis, arising from statistical thermodynamics, undermine evolutionary predictions for proteins.

Keywords:

ensemble epistasis predictability protein evolution thermodynamics

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Area of Science:

Computational biology
Protein evolution
Statistical thermodynamics

Background:

Evolutionary prediction is crucial for understanding biological systems.
Predicting protein evolution is challenging due to complex molecular interactions.

Purpose of the Study:

To investigate the predictability of protein evolution using a computational model.
To determine if knowing all mutation effects in an ancestral protein allows accurate evolutionary trajectory prediction.

Main Methods:

Developed a simple computational protein model.
Performed a virtual deep mutational scan to identify individual and pairwise epistatic effects.
Used mutation effect data to predict evolutionary trajectories.

Main Results:

Evolutionary predictions based on mutation data were poor.
High-order epistasis, stemming from conformational ensembles, was identified.
Uncertainty in mutation effects accumulates, hindering prediction accuracy.

Conclusions:

Protein evolution remains inherently unpredictable.
The conformational ensemble nature of proteins leads to pervasive epistasis.
These findings suggest a universal limitation in predicting protein evolutionary trajectories.