Molecular ensembles make evolution unpredictable
| Autor: | Michael J. Harms, Zachary R. Sailer |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
epistasis Computational biology Biology Protein evolution Evolution Molecular 03 medical and health sciences thermodynamics predictability Feature (machine learning) Amino Acid Sequence Predictability protein evolution Peptide sequence Conformational ensembles Genetics Multidisciplinary ensemble Computational Biology Proteins Epistasis Genetic Biological Sciences Biophysics and Computational Biology 030104 developmental biology Mutation (genetic algorithm) Mutation Protein model Epistasis Forecasting |
| Zdroj: | Proceedings of the National Academy of Sciences of the United States of America |
| ISSN: | 1091-6490 0027-8424 |
| Popis: | Significance A long-standing goal in evolutionary biology is predicting evolution. Here, we show that the architecture of macromolecules fundamentally limits evolutionary predictability. Under physiological conditions, macromolecules, like proteins, flip between multiple structures, forming an ensemble of structures. A mutation affects all of these structures in slightly different ways, redistributing the relative probabilities of structures in the ensemble. As a result, mutations that follow the first mutation have a different effect than they would if introduced before. This implies that knowing the effects of every mutation in an ancestor would be insufficient to predict evolutionary trajectories past the first few steps, leading to profound unpredictability in evolution. We, therefore, conclude that detailed evolutionary predictions are not possible given the chemistry of macromolecules. Evolutionary prediction is of deep practical and philosophical importance. Here we show, using a simple computational protein model, that protein evolution remains unpredictable, even if one knows the effects of all mutations in an ancestral protein background. We performed a virtual deep mutational scan—revealing the individual and pairwise epistatic effects of every mutation to our model protein—and then used this information to predict evolutionary trajectories. Our predictions were poor. This is a consequence of statistical thermodynamics. Proteins exist as ensembles of similar conformations. The effect of a mutation depends on the relative probabilities of conformations in the ensemble, which in turn, depend on the exact amino acid sequence of the protein. Accumulating substitutions alter the relative probabilities of conformations, thereby changing the effects of future mutations. This manifests itself as subtle but pervasive high-order epistasis. Uncertainty in the effect of each mutation accumulates and undermines prediction. Because conformational ensembles are an inevitable feature of proteins, this is likely universal. |
| Databáze: | OpenAIRE |
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