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Causes of evolutionary rate variation among protein sites

Nature Reviews Genetics volume 17, pages 109–121 (2016)Cite this article

Subjects

Key Points

  • The rate of evolution varies among sites within proteins owing to structural and functional constraints.

  • The main pattern of variation is due to structural constraints: evolutionary rates increase from the slowly evolving, solvent-inaccessible, tightly packed and rigid protein interior, to the rapidly evolving, solvent-exposed and loosely packed protein surface.

  • Functional constraints result in the slow evolution of sites that are directly involved in protein function and their neighbours. There may also be longer range effects on distant sites.

  • According to mechanistic biophysical models, site-specific evolutionary rates are related to mutational changes of thermodynamic stability. Structural predictors, such as solvent accessibility and local packing, would be proxies of mutational stability changes.

  • Our understanding of rate variation among sites remains limited: at best, current models explain approximately 60% of the observed variance in site-specific rates, and in many cases these models explain considerably less.

  • To make further progress, we need to develop better rate inference methods, complete the list of structural and functional molecular features that correlate with rates, and undertake further research on theoretical models derived from first principles.

Abstract

It has long been recognized that certain sites within a protein, such as sites in the protein core or catalytic residues in enzymes, are evolutionarily more conserved than other sites. However, our understanding of rate variation among sites remains surprisingly limited. Recent progress to address this includes the development of a wide array of reliable methods to estimate site-specific substitution rates from sequence alignments. In addition, several molecular traits have been identified that correlate with site-specific mutation rates, and novel mechanistic biophysical models have been proposed to explain the observed correlations. Nonetheless, current models explain, at best, approximately 60% of the observed variance, highlighting the limitations of current methods and models and the need for new research directions.

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Figure 1: Structural and functional constraints shape site-specific evolutionary divergence.
Figure 2: WCN correlates more strongly than RSA with site-specific rate.
Figure 3: Predictors of evolutionary variation can help to identify important sites in a protein.
Figure 4: The trade-off between native stability and active stability.

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Acknowledgements

J.E. is Principal Investigator of CONICET. This work was also supported in part by US National Institutes of Health (NIH) grant F31 GM113622-01 to S.J.S. and by NIH grant R01 GM088344, NSF Cooperative agreement DBI-0939454 (BEACON Center), and ARO grant W911NF-12-1-0390 to C.O.W.

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Authors and Affiliations

  1. Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, San Martín, 1650, Buenos Aires, Argentina

    Julian Echave

  2. Department of Integrative Biology, Center for Computational Biology and Bioinformatics, and Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, 78712, Texas, USA

    Stephanie J. Spielman & Claus O. Wilke

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  1. Julian Echave
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Correspondence to Julian Echave or Claus O. Wilke.

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Glossary

Evolutionary rates

Number of substitutions (fixed mutations) per unit of evolutionary time.

Structural constraints

Structural features that correlate with sequence conservation (for example, solvent accessibility).

Functional constraints

Functional features that correlate with sequence conservation (for example, involvement in the active site).

Substitutions

Mutations that have spread to all members of the population (that is, have fixed), substituting the ancestral variant.

dN/dS

Ratio of non-synonymous to synonymous evolutionary rates.

dN

Non-synonymous evolutionary rate: that is, the rate at which non-synonymous substitutions (fixed mutations) occur per unit of evolutionary time.

Non-synonymous substitutions

DNA substitutions that change from a codon that codes for one amino acid to a codon that codes for a different amino acid.

dS

Synonymous evolutionary rate: that is, the rate at which synonymous substitutions (fixed mutations) occur per unit of evolutionary time.

Synonymous substitutions

DNA substitutions that change from a codon that codes for one amino acid to a codon that codes for the same amino acid.

Purifying selection

Loss of mutations that decrease fitness (deleterious).

Positive selection

Fixation of mutations that increase fitness (adaptive).

Rate4Site

Popular software to estimate relative site-specific rates from amino acid sequence data.

Accessible surface area

(ASA). Same as solvent accessible surface area.

Solvent accessible surface area

(SASA). Surface area of a given residue that is accessible to water.

Relative solvent accessibility

(RSA). Measures the proportion of the surface of an amino acid that is accessible to solvent (that is, water) in the folded protein structure, from 0 (completely inaccessible) to 1 (completely accessible). Calculated as the ratio of the solvent accessible surface area (SASA) of a given residue in the protein structure and the maximum SASA of that residue in a fully solvent-accessible conformation.

Contact number

(CN). Number of neighbouring residues present in a protein structure within a given distance (for example, 10 Å) from a focal residue.

Weighted contact number

(WCN). Similar to the contact number, but the neighbouring residues are weighted by their inverse square distance to the focal residue, and all residues in a structure are considered to be neighbouring residues.

Mean square fluctuations

(MSFs). Time-average of the square norm of the vector that connects the instantaneous coordinates of a site to its equilibrium coordinates; measures the amount of movement a residue undergoes over time.

B-factors

(Also known as temperature factors). Quantity that measures the amount of thermal motion of an atom in a protein crystal structure.

ΔΔG

Mutational change of stability; the folding free energy difference between mutant and wild type when each is in its own native conformation.

ΔΔG*

Mutational change of stability of the active conformation; free energy difference between the active conformation of the mutant and the active conformation of the wild type.

ΔΔG‡

Mutational change of the activation free energy; difference between mutant and wild type of the free energy needed to deform the protein from the native into the active conformation.

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Echave, J., Spielman, S. & Wilke, C. Causes of evolutionary rate variation among protein sites. Nat Rev Genet 17, 109–121 (2016). https://doi.org/10.1038/nrg.2015.18

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