Michael J. Harms

Evolutionary biochemistry: revealing the historical and physical causes of protein properties

The repertoire of proteins and nucleic acids in the living world is determined by evolution; their properties are determined by the laws of physics and chemistry. Explanations of these two kinds of causality — the purviews of evolutionary biology and biochemistry, respectively — are typically pursued in isolation, but many fundamental questions fall squarely at the interface of fields. Here we articulate the paradigm of evolutionary biochemistry, which aims to dissect the physical mechanisms and evolutionary processes by which biological molecules diversified and to reveal how their physical architecture facilitates and constrains their evolution. We show how an integration of evolution with biochemistry moves us towards a more complete understanding of why biological molecules have the properties that they do.

Protein Evolution by Molecular Tinkering: Diversification of the Nuclear Receptor Superfamily from a Ligand- Dependent Ancestor

Phylogenetic reconstruction of the structure and function of the ancestor of the nuclear receptor protein family reveals how functional diversity evolves by subtle tinkering with an ancestral template.

Analyzing protein structure and function using ancestral gene reconstruction

Protein families with functionally diverse members can illuminate the structural determinants of protein function and the process by which protein structure and function evolve. To identify the key amino acid changes that differentiate one family member from another, most studies have taken a horizontal approach, swapping candidate residues between present-day family members. This approach has often been stymied, however, by the fact that shifts in function often require multiple interacting mutations; chimeric proteins are often nonfunctional, either because one lineage has amassed mutations that are incompatible with key residues that conferred a new function on other lineages, or because it lacks mutations required to support those key residues. These difficulties can be overcome by using a vertical strategy, which reconstructs ancestral genes and uses them as the appropriate background in which to study the effects of historical mutations on functional diversification. In this review, we discuss the advantages of the vertical strategy and highlight several exemplary studies that have used ancestral gene reconstruction to reveal the molecular underpinnings of protein structure, function, and evolution.

Historical contingency and its biophysical basis in glucocorticoid receptor evolution

Understanding how chance historical events shape evolutionary processes is a central goal of evolutionary biology. Direct insights into the extent and causes of evolutionary contingency have been limited to experimental systems, because it is difficult to know what happened in the deep past and to characterize other paths that evolution could have followed. Here we combine ancestral protein reconstruction, directed evolution and biophysical analysis to explore alternative ‘might-have-been’ trajectories during the ancient evolution of a novel protein function. We previously found that the evolution of cortisol specificity in the ancestral glucocorticoid receptor (GR) was contingent on permissive substitutions, which had no apparent effect on receptor function but were necessary for GR to tolerate the large-effect mutations that caused the shift in specificity. Here we show that alternative mutations that could have permitted the historical function-switching substitutions are extremely rare in the ensemble of genotypes accessible to the ancestral GR. In a library of thousands of variants of the ancestral protein, we recovered historical permissive substitutions but no alternative permissive genotypes. Using biophysical analysis, we found that permissive mutations must satisfy at least three physical requirements—they must stabilize specific local elements of the protein structure, maintain the correct energetic balance between functional conformations, and be compatible with the ancestral and derived structures—thus revealing why permissive mutations are rare. These findings demonstrate that GR evolution depended strongly on improbable, non-deterministic events, and this contingency arose from intrinsic biophysical properties of the protein.

Arginine residues at internal positions in a protein are always charged.

Many functionally essential ionizable groups are buried in the hydrophobic interior of proteins. A systematic study of Lys, Asp, and Glu residues at 25 internal positions in staphylococcal nuclease showed that their pKa values can be highly anomalous, some shifted by as many as 5.7 pH units relative to normal pKa values in water. Here we show that, in contrast, Arg residues at the same internal positions exhibit no detectable shifts in pKa; they are all charged at pH ≤ 10. Twenty-three of these 25 variants with Arg are folded at both pH 7 and 10. The mean decrease in thermodynamic stability from substitution with Arg was 6.2 kcal/mol at this pH, comparable to that for substitution with Lys, Asp, or Glu at pH 7. The physical basis behind the remarkable ability of Arg residues to remain protonated in environments otherwise incompatible with charges is suggested by crystal structures of three variants showing how the guanidinium moiety of the Arg side chain is effectively neutralized through multiple hydrogen bonds to protein polar atoms and to site-bound water molecules. The length of the Arg side chain, and slight deformations of the protein, facilitate placement of the guanidinium moieties near polar groups or bulk water. This unique capacity of Arg side chains to retain their charge in dehydrated environments likely contributes toward the important functional roles of internal Arg residues in situations where a charge is needed in the interior of a protein, in a lipid bilayer, or in similarly hydrophobic environments.

Biophysical mechanisms for large-effect mutations in the evolution of steroid hormone receptors

The genetic and biophysical mechanisms by which new protein functions evolve is a central question in evolutionary biology, biochemistry, and biophysics. Of particular interest is whether major shifts in protein function are caused by a few mutations of large effect and, if they are, the mechanisms that mediate these changes. Here we combine ancestral protein reconstruction with genetic manipulation and explicit studies of protein structure and dynamics to dissect an ancient and discrete shift in ligand specificity in the steroid receptors, a family of biologically essential hormone-controlled transcription factors. We previously found that the ancestor of the entire steroid receptor family was highly specific for estrogens, but its immediate phylogenetic descendant was sensitive only to androgens, progestogens, and corticosteroids. Here we show that this shift in function was driven primarily by two historical amino acid changes, which caused a ∼70,000-fold change in the ancestral protein’s specificity. These replacements subtly changed the chemistry of two amino acids, but they dramatically reduced estrogen sensitivity by introducing an excess of interaction partners into the receptor/estrogen complex, inducing a frustrated ensemble of suboptimal hydrogen bond networks unique to estrogens. This work shows how the protein’s architecture and dynamics shaped its evolution, amplifying a few biochemically subtle mutations into major shifts in the energetics and function of the protein.

Thermodynamic System Drift in Protein Evolution

Tracking the evolution of thermostability in resurrected ancestors of a heat-tolerant extremophile protein and its less heat tolerant Escherichia coli homologue shows how thermostability has probably explored different mechanisms of protein stabilization over evolutionary time.

Detecting High-Order Epistasis in Nonlinear Genotype-Phenotype Maps

High-order epistasis has been observed in many genotype-phenotype maps. These multi-way interactions between mutations may be useful for dissecting complex traits and could have profound implications for evolution. Alternatively, they could be a statistical artifact. High-order epistasis models assume the effects of mutations should add, when they could in fact multiply or combine in some other nonlinear way. A mismatch in the “scale” of the epistasis model and the scale of the underlying map would lead to spurious epistasis. In this article, we develop an approach to estimate the nonlinear scales of arbitrary genotype-phenotype maps. We can then linearize these maps and extract high-order epistasis. We investigated seven experimental genotype-phenotype maps for which high-order epistasis had been reported previously. We find that five of the seven maps exhibited nonlinear scales. Interestingly, even after accounting for nonlinearity, we found statistically significant high-order epistasis in all seven maps. The contributions of high-order epistasis to the total variation ranged from 2.2 to 31.0%, with an average across maps of 12.7%. Our results provide strong evidence for extensive high-order epistasis, even after nonlinear scale is taken into account. Further, we describe a simple method to estimate and account for nonlinearity in genotype-phenotype maps.

The thermostability and specificity of ancient proteins.

Were ancient proteins systematically different than modern proteins? The answer to this question is profoundly important, shaping how we understand the origins of protein biochemical, biophysical, and functional properties. Ancestral sequence reconstruction (ASR), a phylogenetic approach to infer the sequences of ancestral proteins, may reveal such trends. We discuss two proposed trends: a transition from higher to lower thermostability and a tendency for proteins to acquire higher specificity over time. We review the evidence for elevated ancestral thermostability and discuss its possible origins in a changing environmental temperature and/or reconstruction bias. We also conclude that there is, as yet, insufficient data to support a trend from promiscuity to specificity. Finally, we propose future work to understand these proposed evolutionary trends.

Robustness of reconstructed ancestral protein functions to statistical uncertainty

Hypotheses about the functions of ancient proteins and the effects of historical mutations on them are often tested using ancestral protein reconstruction (APR)—phylogenetic inference of ancestral sequences followed by synthesis and experimental characterization. Usually, some sequence sites are ambiguously reconstructed, with two or more statistically plausible states. The extent to which the inferred functions and mutational effects are robust to uncertainty about the ancestral sequence has not been studied systematically. To address this issue, we reconstructed ancestral proteins in three domain families that have different functions, architectures, and degrees of uncertainty; we then experimentally characterized the functional robustness of these proteins when uncertainty was incorporated using several approaches, including sampling amino acid states from the posterior distribution at each site and incorporating the alternative amino acid state at every ambiguous site in the sequence into a single “worst plausible case” protein. In every case, qualitative conclusions about the ancestral proteins’ functions and the effects of key historical mutations were robust to sequence uncertainty, with similar functions observed even when scores of alternate amino acids were incorporated. There was some variation in quantitative descriptors of function among plausible sequences, suggesting that experimentally characterizing robustness is particularly important when quantitative estimates of ancient biochemical parameters are desired. The worst plausible case method appears to provide an efficient strategy for characterizing the functional robustness of ancestral proteins to large amounts of sequence uncertainty. Sampling from the posterior distribution sometimes produced artifactually nonfunctional proteins for sequences reconstructed with substantial ambiguity.