Escape from Adaptive Conflict follows from weak functional trade-offs and mutational robustness

Frustration can Limit the Adaptation of Promiscuous Enzymes Through Gene Duplication and Specialisation

Virtually all enzymes catalyse more than one reaction, a phenomenon known as enzyme promiscuity. It is unclear whether promiscuous enzymes are more often generalists that catalyse multiple reactions at similar rates or specialists that catalyse one reaction much more efficiently than other reactions. In addition, the factors that shape whether an enzyme evolves to be a generalist or a specialist are poorly understood. To address these questions, we follow a three-pronged approach. First, we examine the distribution of promiscuity in empirical enzymes reported in the BRENDA database. We find that the promiscuity distribution of empirical enzymes is bimodal. In other words, a large fraction of promiscuous enzymes are either generalists or specialists, with few intermediates. Second, we demonstrate that enzyme biophysics is not sufficient to explain this bimodal distribution. Third, we devise a constraint-based model of promiscuous enzymes undergoing duplication and facing selection pressures favouring subfunctionalization. The model posits the existence of constraints between the catalytic efficiencies of an enzyme for different reactions and is inspired by empirical case studies. The promiscuity distribution predicted by our constraint-based model is consistent with the empirical bimodal distribution. Our results suggest that subfunctionalization is possible and beneficial only in certain enzymes. Furthermore, the model predicts that conflicting constraints and selection pressures can cause promiscuous enzymes to enter a 'frustrated' state, in which competing interactions limit the specialisation of enzymes. We find that frustration can be both a driver and an inhibitor of enzyme evolution by duplication and subfunctionalization. In addition, our model predicts that frustration becomes more likely as enzymes catalyse more reactions, implying that natural selection may prefer catalytically simple enzymes. In sum, our results suggest that frustration may play an important role in enzyme evolution.

Computing Free Energies of Fold-Switching Proteins Using MELD x MD

Some proteins are conformational switches, able to transition between relatively different conformations. To understand what drives them requires computing the free-energy difference ΔGAB between their stable states, A and B. Molecular dynamics (MD) simulations alone are often slow because they require a reaction coordinate and must sample many transitions in between. Here, we show that modeling employing limited data (MELD) x MD on known endstates A and B is accurate and efficient because it does not require passing over barriers or knowing reaction coordinates. We validate this method on two problems: (1) it gives correct relative populations of α and β conformers for small designed chameleon sequences of protein G; and (2) it correctly predicts the conformations of the C-terminal domain (CTD) of RfaH. Free-energy methods like MELD x MD can often resolve structures that confuse machine-learning (ML) methods.

Identification of a covert evolutionary pathway between two protein folds

Although homologous protein sequences are expected to adopt similar structures, some amino acid substitutions can interconvert α-helices and β-sheets. Such fold switching may have occurred over evolutionary history, but supporting evidence has been limited by the: (1) abundance and diversity of sequenced genes, (2) quantity of experimentally determined protein structures, and (3) assumptions underlying the statistical methods used to infer homology. Here, we overcome these barriers by applying multiple statistical methods to a family of ~600,000 bacterial response regulator proteins. We find that their homologous DNA-binding subunits assume divergent structures: helix-turn-helix versus α-helix + β-sheet (winged helix). Phylogenetic analyses, ancestral sequence reconstruction, and AlphaFold2 models indicate that amino acid substitutions facilitated a switch from helix-turn-helix into winged helix. This structural transformation likely expanded DNA-binding specificity. Our approach uncovers an evolutionary pathway between two protein folds and provides a methodology to identify secondary structure switching in other protein families.

Design and characterization of a protein fold switching network

To better understand how amino acid sequence encodes protein structure, we engineered mutational pathways that connect three common folds (3α, β-grasp, and α/β-plait). The structures of proteins at high sequence-identity intersections in the pathways (nodes) were determined using NMR spectroscopy and analyzed for stability and function. To generate nodes, the amino acid sequence encoding a smaller fold is embedded in the structure of an ~50% larger fold and a new sequence compatible with two sets of native interactions is designed. This generates protein pairs with a 3α or β-grasp fold in the smaller form but an α/β-plait fold in the larger form. Further, embedding smaller antagonistic folds creates critical states in the larger folds such that single amino acid substitutions can switch both their fold and function. The results help explain the underlying ambiguity in the protein folding code and show that new protein structures can evolve via abrupt fold switching.

Mechanisms of protein evolution

How do proteins evolve? How do changes in sequence mediate changes in protein structure, and in turn in function? This question has multiple angles, ranging from biochemistry and biophysics to evolutionary biology. This review provides a brief integrated view of some key mechanistic aspects of protein evolution. First, we explain how protein evolution is primarily driven by randomly acquired genetic mutations and selection for function, and how these mutations can even give rise to completely new folds. Then, we also comment on how phenotypic protein variability, including promiscuity, transcriptional and translational errors, may also accelerate this process, possibly via "plasticity-first" mechanisms. Finally, we highlight open questions in the field of protein evolution, with respect to the emergence of more sophisticated protein systems such as protein complexes, pathways, and the emergence of pre-LUCA enzymes.

Gene duplication and rate variation in the evolution of plastid ACCase and Clp genes in angiosperms

While the chloroplast (plastid) is known for its role in photosynthesis, it is also involved in many other metabolic pathways essential for plant survival. As such, plastids contain an extensive suite of enzymes required for non-photosynthetic processes. The evolution of the associated genes has been especially dynamic in flowering plants (angiosperms), including examples of gene duplication and extensive rate variation. We examined the role of ongoing gene duplication in two key plastid enzymes, the acetyl-CoA carboxylase (ACCase) and the caseinolytic protease (Clp), responsible for fatty acid biosynthesis and protein turnover, respectively. In plants, there are two ACCase complexes-a homomeric version present in the cytosol and a heteromeric version present in the plastid. Duplications of the nuclear-encoded homomeric ACCase gene and retargeting of one resultant protein to the plastid have been previously reported in multiple species. We find that these retargeted homomeric ACCase proteins exhibit elevated rates of sequence evolution, consistent with neofunctionalization and/or relaxation of selection. The plastid Clp complex catalytic core is composed of nine paralogous proteins that arose via ancient gene duplication in the cyanobacterial/plastid lineage. We show that further gene duplication occurred more recently in the nuclear-encoded core subunits of this complex, yielding additional paralogs in many species of angiosperms. Moreover, in six of eight cases, subunits that have undergone recent duplication display increased rates of sequence evolution relative to those that have remained single copy. We also compared substitution patterns between pairs of Clp core paralogs to gain insight into post-duplication evolutionary routes. These results show that gene duplication and rate variation continue to shape the plastid proteome.

Evolution of a cytoplasmic determinant: evidence for the biochemical basis of functional evolution of the novel germ line regulator oskar

Germ line specification is essential in sexually reproducing organisms. Despite their critical role, the evolutionary history of the genes that specify animal germ cells is heterogeneous and dynamic. In many insects, the gene oskar is required for the specification of the germ line. However, the germ line role of oskar is thought to be a derived role resulting from co-option from an ancestral somatic role. To address how evolutionary changes in protein sequence could have led to changes in the function of Oskar protein that enabled it to regulate germ line specification, we searched for oskar orthologs in 1,565 publicly available insect genomic and transcriptomic data sets. The earliest-diverging lineage in which we identified an oskar ortholog was the order Zygentoma (silverfish and firebrats), suggesting that oskar originated before the origin of winged insects. We noted some order-specific trends in oskar sequence evolution, including whole gene duplications, clade-specific losses, and rapid divergence. An alignment of all known 379 Oskar sequences revealed new highly conserved residues as candidates that promote dimerization of the LOTUS domain. Moreover, we identified regions of the OSK domain with conserved predicted RNA binding potential. Furthermore, we show that despite a low overall amino acid conservation, the LOTUS domain shows higher conservation of predicted secondary structure than the OSK domain. Finally, we suggest new key amino acids in the LOTUS domain that may be involved in the previously reported Oskar−Vasa physical interaction that is required for its germ line role.

Navigating the amino acid sequence space between functional proteins using a deep learning framework

MOTIVATION

Shedding light on the relationships between protein sequences and functions is a challenging task with many implications in protein evolution, diseases understanding, and protein design. The protein sequence space mapping to specific functions is however hard to comprehend due to its complexity. Generative models help to decipher complex systems thanks to their abilities to learn and recreate data specificity. Applied to proteins, they can capture the sequence patterns associated with functions and point out important relationships between sequence positions. By learning these dependencies between sequences and functions, they can ultimately be used to generate new sequences and navigate through uncharted area of molecular evolution.

RESULTS

This study presents an Adversarial Auto-Encoder (AAE) approached, an unsupervised generative model, to generate new protein sequences. AAEs are tested on three protein families known for their multiple functions the sulfatase, the HUP and the TPP families. Clustering results on the encoded sequences from the latent space computed by AAEs display high level of homogeneity regarding the protein sequence functions. The study also reports and analyzes for the first time two sampling strategies based on latent space interpolation and latent space arithmetic to generate intermediate protein sequences sharing sequential properties of original sequences linked to known functional properties issued from different families and functions. Generated sequences by interpolation between latent space data points demonstrate the ability of the AAE to generalize and produce meaningful biological sequences from an evolutionary uncharted area of the biological sequence space. Finally, 3D structure models computed by comparative modelling using generated sequences and templates of different sub-families point out to the ability of the latent space arithmetic to successfully transfer protein sequence properties linked to function between different sub-families. All in all this study confirms the ability of deep learning frameworks to model biological complexity and bring new tools to explore amino acid sequence and functional spaces.

Exploring the sequence fitness landscape of a bridge between protein folds

Most foldable protein sequences adopt only a single native fold. Recent protein design studies have, however, created protein sequences which fold into different structures apon changes of environment, or single point mutation, the best characterized example being the switch between the folds of the GA and GB binding domains of streptococcal protein G. To obtain further insight into the design of sequences which can switch folds, we have used a computational model for the fitness landscape of a single fold, built from the observed sequence variation of protein homologues. We have recently shown that such coevolutionary models can be used to design novel foldable sequences. By appropriately combining two of these models to describe the joint fitness landscape of GA and GB, we are able to describe the propensity of a given sequence for each of the two folds. We have successfully tested the combined model against the known series of designed GA/GB hybrids. Using Monte Carlo simulations on this landscape, we are able to identify pathways of mutations connecting the two folds. In the absence of a requirement for domain stability, the most frequent paths go via sequences in which neither domain is stably folded, reminiscent of the propensity for certain intrinsically disordered proteins to fold into different structures according to context. Even if the folded state is required to be stable, we find that there is nonetheless still a wide range of sequences which are close to the transition region and therefore likely fold switches, consistent with recent estimates that fold switching may be more widespread than had been thought.

Amalgamated cross-species transcriptomes reveal organ-specific propensity in gene expression evolution

The origins of multicellular physiology are tied to evolution of gene expression. Genes can shift expression as organisms evolve, but how ancestral expression influences altered descendant expression is not well understood. To examine this, we amalgamate 1,903 RNA-seq datasets from 182 research projects, including 6 organs in 21 vertebrate species. Quality control eliminates project-specific biases, and expression shifts are reconstructed using gene-family-wise phylogenetic Ornstein-Uhlenbeck models. Expression shifts following gene duplication result in more drastic changes in expression properties than shifts without gene duplication. The expression properties are tightly coupled with protein evolutionary rate, depending on whether and how gene duplication occurred. Fluxes in expression patterns among organs are nonrandom, forming modular connections that are reshaped by gene duplication. Thus, if expression shifts, ancestral expression in some organs induces a strong propensity for expression in particular organs in descendants. Regardless of whether the shifts are adaptive or not, this supports a major role for what might be termed preadaptive pathways of gene expression evolution.

Repurposing a bacterial prolidase for organophosphorus hydrolysis: Reshaped catalytic cavity switches substrate selectivity

Enzyme promiscuity is critical to the acquisition of evolutionary plasticity in cells and can be recruited for high-value chemical synthesis or xenobiotic degradation. The molecular determinants of substrate ambiguity are essential to this activity; however, these details remain unknown. Here, we performed the directed evolution of a prolidase to enhance its initially weak paraoxonase activity. The in vitro evolution led to an unexpected 1,000,000-fold switch in substrate selectivity, with a 30-fold increase in paraoxon hydrolysis and 40,000-fold decrease in peptide hydrolysis. Structural and in silico analyses revealed enlarged catalytic cavities and substrate repositioning as responsible for rapid catalytic transitions between distinct chemical reactions.

Gene and genome duplications in the evolution of chemodiversity: perspectives from studies of Lamiaceae

Plants are reservoirs of extreme chemical diversity, yet biosynthetic pathways remain underexplored in the majority of taxa. Access to improved, inexpensive genomic and computational technologies has recently enhanced our understanding of plant specialized metabolism at the biochemical and evolutionary levels including the elucidation of pathways leading to key metabolites. Furthermore, these approaches have provided insights into the mechanisms of chemical evolution, including neofunctionalization and subfunctionalization, structural variation, and modulation of gene expression. The broader utilization of genomic tools across the plant tree of life, and an expansion of genomic resources from multiple accessions within species or populations, will improve our overall understanding of chemodiversity. These data and knowledge will also lead to greater insight into the selective pressures contributing to and maintaining this diversity, which in turn will enable the development of more accurate predictive models of specialized metabolism in plants.

The evolution of metabolism: How to test evolutionary hypotheses at the genomic level

The origin of primordial metabolism and its expansion to form the metabolic networks extant today represent excellent systems to study the impact of natural selection and the potential adaptive role of novel compounds. Here we present the current hypotheses made on the origin of life and ancestral metabolism and present the theories and mechanisms by which the large chemical diversity of plants might have emerged along evolution. In particular, we provide a survey of statistical methods that can be used to detect signatures of selection at the gene and population level, and discuss potential and limits of these methods for investigating patterns of molecular adaptation in plant metabolism.

Opposing Pressures of Speed and Efficiency Guide the Evolution of Molecular Machines

Many biomolecular machines need to be both fast and efficient. How has evolution optimized these machines along the tradeoff between speed and efficiency? We explore this question using optimizable dynamical models along coordinates that are plausible evolutionary degrees of freedom. Data on 11 motors and ion pumps are consistent with the hypothesis that evolution seeks an optimal balance of speed and efficiency, where any further small increase in one of these quantities would come at great expense to the other. For F_oF₁-ATPases in different species, we also find apparent optimization of the number of subunits in the c-ring, which determines the number of protons pumped per ATP synthesized. Interestingly, these ATPases appear to more optimized for efficiency than for speed, which can be rationalized through their key role as energy transducers in biology. The present modeling shows how the dynamical performance properties of biomolecular motors and pumps may have evolved to suit their corresponding biological actions.

Evolutionary dynamics of natural product biosynthesis in bacteria

Covering: 2008 up to 2019The forces of biochemical adaptive evolution operate at the level of genes, manifesting in complex phenotypes and the global biodiversity of proteins and metabolites. While evolutionary histories have been deciphered for some other complex traits, the origins of natural product biosynthesis largely remain a mystery. This fundamental knowledge gap is surprising given the many decades of research probing the genetic, chemical, and biophysical mechanisms of bacterial natural product biosynthesis. Recently, evolutionary thinking has begun to permeate this otherwise mechanistically dominated field. Natural products are now sometimes referred to as 'specialized' rather than 'secondary' metabolites, reinforcing the importance of their biological and ecological functions. Here, we review known evolutionary mechanisms underlying the overwhelming chemical diversity of bacterial secondary metabolism, focusing on enzyme promiscuity and the evolution of enzymatic domains that enable metabolic traits. We discuss the mechanisms that drive the assembly of natural product biosynthetic gene clusters and propose formal definitions for 'specialized' and 'secondary' metabolism. We further explore how biosynthetic gene clusters evolve to synthesize related molecular species, and in turn how the biological and ecological roles that emerge from metabolic diversity are acted on by selection. Finally, we reconcile chemical, functional, and genetic data into an evolutionary model, the dynamic chemical matrix evolutionary hypothesis, in which the relationships between chemical distance, biomolecular activity, and relative fitness shape adaptive landscapes.

Evolutionary Potential of Cis-Regulatory Mutations to Cause Rapid Changes in Transcription Factor Binding

Transcriptional regulation is crucial for all biological processes and well investigated at the molecular level for a wide range of organisms. However, it is quite unclear how innovations, such as the activity of a novel regulatory element, evolve. In the case of transcription factor (TF) binding, both a novel TF and a novel-binding site would need to evolve concertedly. Since promiscuous functions have recently been identified as important intermediate steps in creating novel specific functions in many areas such as enzyme evolution and protein-protein interactions, we ask here how promiscuous binding of TFs to TF-binding sites (TFBSs) affects the robustness and evolvability of this tightly regulated system. Specifically, we investigate the binding behavior of several hundred TFs from different species at unprecedented breadth. Our results illustrate multiple aspects of TF-binding interactions, ranging from correlations between the strength of the interaction bond and specificity, to preferences regarding TFBS nucleotide composition in relation to both domains and binding specificity. We identified a subset of high A/T binding motifs. Motifs in this subset had many functionally neutral one-error mutants, and were bound by multiple different binding domains. Our results indicate that, especially for some TF-TFBS associations, low binding specificity confers high degrees of evolvability, that is that few mutations facilitate rapid changes in transcriptional regulation, in particular for large and old TF families. In this study we identify binding motifs exhibiting behavior indicating high evolutionary potential for innovations in transcriptional regulation.

Balancing Specificity and Promiscuity in Enzyme Evolution: Multidimensional Activity Transitions in the Alkaline Phosphatase Superfamily

Highly proficient, promiscuous enzymes can be springboards for functional evolution, able to avoid loss of function during adaptation by their capacity to promote multiple reactions. We employ a systematic comparative study of structure, sequence, and substrate specificity to track the evolution of specificity and reactivity between promiscuous members of clades of the alkaline phosphatase (AP) superfamily. Construction of a phylogenetic tree of protein sequences maps out the likely transition zone between arylsulfatases (ASs) and phosphonate monoester hydrolases (PMHs). Kinetic analysis shows that all enzymes characterized have four chemically distinct phospho- and sulfoesterase activities, with rate accelerations ranging from 10¹¹- to 10¹⁷-fold for their primary and 10⁹- to 10¹²-fold for their promiscuous reactions, suggesting that catalytic promiscuity is widespread in the AP-superfamily. This functional characterization and crystallography reveal a novel class of ASs that is so similar in sequence to known PMHs that it had not been recognized as having diverged in function. Based on analysis of snapshots of catalytic promiscuity "in transition", we develop possible models that would allow functional evolution and determine scenarios for trade-off between multiple activities. For the new ASs, we observe largely invariant substrate specificity that would facilitate the transition from ASs to PMHs via trade-off-free molecular exaptation, that is, evolution without initial loss of primary activity and specificity toward the original substrate. This ability to bypass low activity generalists provides a molecular solution to avoid adaptive conflict.

Widespread signatures of selection for secreted peptidases in a fungal plant pathogen

BACKGROUND

Fungal plant pathogens secrete a large arsenal of hydrolytic enzymes during the course of infection, including peptidases. Secreted peptidases have been extensively studied for their role as effectors. In this study, we combined transcriptomics, comparative genomics and evolutionary analyses to investigate all 39 secreted peptidases in the fungal wheat pathogen Zymoseptoria tritici and its close relatives Z. pseudotritici and Z. ardabiliae.

RESULTS

RNA-seq data revealed that a majority of the secreted peptidases displayed differential transcription during the course of Z. tritici infection, indicative of specialization for different stages in the life cycle. Evolutionary analyses detected widespread evidence of adaptive evolution acting on at least 28 of the peptidases. A few peptidases displayed lineage-specific rates of molecular evolution, suggesting altered selection pressure in Z. tritici following host specialization on domesticated wheat. The peptidases belonging to MEROPS families A1 and G1 emerged as a particularly interesting group that may play key roles in host-pathogen co-evolution, host adaptation and pathogenicity. Sister genes in the A1 and G1 families showed accelerated substitution rates after gene duplications.

CONCLUSIONS

These results suggest widespread evolution of secreted peptidases leading to novel gene functions, consistent with predicted models of "escape from adaptive conflict" and "neo-functionalization". Our analyses identified candidate genes worthy of functional analyses that may encode effector functions, for example by suppressing plant defenses during the biotrophic phase of infection.

Evolution of intrinsic disorder in eukaryotic proteins

Conformational flexibility conferred though regions of intrinsic structural disorder allows proteins to behave as dynamic molecules. While it is well-known that intrinsically disordered regions can undergo disorder-to-order transitions in real-time as part of their function, we also are beginning to learn more about the dynamics of disorder-to-order transitions along evolutionary time-scales. Intrinsically disordered regions endow proteins with functional promiscuity, which is further enhanced by the ability of some of these regions to undergo real-time disorder-to-order transitions. Disorder content affects gene retention after whole genome duplication, but it is not necessarily conserved. Altered patterns of disorder resulting from evolutionary disorder-to-order transitions indicate that disorder evolves to modify function through refining stability, regulation, and interactions. Here, we review the evolution of intrinsically disordered regions in eukaryotic proteins. We discuss the interplay between secondary structure and disorder on evolutionary time-scales, the importance of disorder for eukaryotic proteome expansion and functional divergence, and the evolutionary dynamics of disorder.

Foldamer hypothesis for the growth and sequence differentiation of prebiotic polymers

It is not known how life originated. It is thought that prebiotic processes were able to synthesize short random polymers. However, then, how do short-chain molecules spontaneously grow longer? Also, how would random chains grow more informational and become autocatalytic (i.e., increasing their own concentrations)? We study the folding and binding of random sequences of hydrophobic ([Formula: see text]) and polar ([Formula: see text]) monomers in a computational model. We find that even short hydrophobic polar (HP) chains can collapse into relatively compact structures, exposing hydrophobic surfaces. In this way, they act as primitive versions of today's protein catalysts, elongating other such HP polymers as ribosomes would now do. Such foldamer catalysts are shown to form an autocatalytic set, through which short chains grow into longer chains that have particular sequences. An attractive feature of this model is that it does not overconverge to a single solution; it gives ensembles that could further evolve under selection. This mechanism describes how specific sequences and conformations could contribute to the chemistry-to-biology (CTB) transition.

Evolutionary Diversification of Alanine Transaminases in Yeast: Catabolic Specialization and Biosynthetic Redundancy

Gene duplication is one of the major evolutionary mechanisms providing raw material for the generation of genes with new or modified functions. The yeast Saccharomyces cerevisiae originated after an allopolyploidization event, which involved mating between two different ancestral yeast species. ScALT1 and ScALT2 codify proteins with 65% identity, which were proposed to be paralogous alanine transaminases. Further analysis of their physiological role showed that while ScALT1 encodes an alanine transaminase which constitutes the main pathway for alanine biosynthesis and the sole pathway for alanine catabolism, ScAlt2 does not display alanine transaminase activity and is not involved in alanine metabolism. Moreover, phylogenetic studies have suggested that ScALT1 and ScALT2 come from each one of the two parental strains which gave rise to the ancestral hybrid. The present work has been aimed to the understanding of the properties of the ancestral type Lacchancea kluyveri LkALT1 and Kluyveromyces lactis KlALT1, alanine transaminases in order to better understand the ScALT1 and ScALT2 evolutionary history. These ancestral -type species were chosen since they harbor ALT1 genes, which are related to ScALT2. Presented results show that, although LkALT1 and KlALT1 constitute ScALT1 orthologous genes, encoding alanine transaminases, both yeasts display LkAlt1 and KlAlt1 independent alanine transaminase activity and additional unidentified alanine biosynthetic and catabolic pathway(s). Furthermore, phenotypic analysis of null mutants uncovered the fact that KlAlt1 and LkAlt1 have an additional role, not related to alanine metabolism but is necessary to achieve wild type growth rate. Our study shows that the ancestral alanine transaminase function has been retained by the ScALT1 encoded enzyme, which has specialized its catabolic character, while losing the alanine independent role observed in the ancestral type enzymes. The fact that ScAlt2 conserves 64% identity with LkAlt1 and 66% with KlAlt1, suggests that ScAlt2 diversified after the ancestral hybrid was formed. ScALT2 functional diversification resulted in loss of both alanine transaminase activity and the additional alanine-independent LkAlt1 function, since ScALT2 did not complement the Lkalt1Δ phenotype. It can be concluded that LkALT1 and KlLALT1 functional role as alanine transaminases was delegated to ScALT1, while ScALT2 lost this role during diversification.

Diversity, expansion, and evolutionary novelty of plant DNA-binding transcription factor families

Plant transcription factors (TFs) that interact with specific sequences via DNA-binding domains are crucial for regulating transcriptional initiation and are fundamental to plant development and environmental response. In addition, expansion of TF families has allowed functional divergence of duplicate copies, which has contributed to novel, and in some cases adaptive, traits in plants. Thus, TFs are central to the generation of the diverse plant species that we see today. Major plant agronomic traits, including those relevant to domestication, have also frequently arisen through changes in TF coding sequence or expression patterns. Here our goal is to provide an overview of plant TF evolution by first comparing the diversity of DNA-binding domains and the sizes of these domain families in plants and other eukaryotes. Because TFs are among the most highly expanded gene families in plants, the birth and death process of TFs as well as the mechanisms contributing to their retention are discussed. We also provide recent examples of how TFs have contributed to novel traits that are important in plant evolution and in agriculture.This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

Evolution of Gene Duplication in Plants

Ancient duplication events and a high rate of retention of extant pairs of duplicate genes have contributed to an abundance of duplicate genes in plant genomes. These duplicates have contributed to the evolution of novel functions, such as the production of floral structures, induction of disease resistance, and adaptation to stress. Additionally, recent whole-genome duplications that have occurred in the lineages of several domesticated crop species, including wheat (Triticum aestivum), cotton (Gossypium hirsutum), and soybean (Glycine max), have contributed to important agronomic traits, such as grain quality, fruit shape, and flowering time. Therefore, understanding the mechanisms and impacts of gene duplication will be important to future studies of plants in general and of agronomically important crops in particular. In this review, we survey the current knowledge about gene duplication, including gene duplication mechanisms, the potential fates of duplicate genes, models explaining duplicate gene retention, the properties that distinguish duplicate from singleton genes, and the evolutionary impact of gene duplication.

Evolutionary dynamics of viral escape under antibodies stress: A biophysical model

Viruses constantly face the selection pressure of antibodies, either from innate immune response of the host or from administered antibodies for treatment. We explore the interplay between the biophysical properties of viral proteins and the population and demographic variables in the viral escape. The demographic and population genetics aspect of the viral escape have been explored before; however one important assumption was the a priori distribution of fitness effects (DFE). Here, we relax this assumption by instead considering a realistic biophysics-based genotype-phenotype relationship for RNA viruses escaping antibodies stress. In this model the DFE is itself an evolvable property that depends on the genetic background (epistasis) and the distribution of biophysical effects of mutations, which is informed by biochemical experiments and theoretical calculations in protein engineering. We quantitatively explore in silico the viability of viral populations under antibodies pressure and derive the phase diagram that defines the fate of the virus population (extinction or escape from stress) in a range of viral mutation rates and antibodies concentrations. We find that viruses are most resistant to stress at an optimal mutation rate (OMR) determined by the competition between supply of beneficial mutation to facilitate escape from stressors and lethal mutagenesis caused by excess of destabilizing mutations. We then show the quantitative dependence of the OMR on genome length and viral burst size. We also recapitulate the experimental observation that viruses with longer genomes have smaller mutation rate per nucleotide.

Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches

Deciphering the effects of nonsynonymous mutations on protein structure is central to many areas of biomedical research and is of fundamental importance to the study of molecular evolution. Much of the investigation of protein evolution has focused on mutations that leave a protein’s folded structure essentially unchanged. However, to evolve novel folds of proteins, mutations that lead to large conformational modifications have to be involved. Unraveling the basic biophysics of such mutations is a challenge to theory, especially when only one or two amino acid substitutions cause a large-scale conformational switch. Among the few such mutational switches identified experimentally, the one between the G_A all-α and G_B α+β folds is extensively characterized; but all-atom simulations using fully transferrable potentials have not been able to account for this striking switching behavior. Here we introduce an explicit-chain model that combines structure-based native biases for multiple alternative structures with a general physical atomic force field, and apply this construct to twelve mutants spanning the sequence variation between G_A and G_B. In agreement with experiment, we observe conformational switching from G_A to G_B upon a single L45Y substitution in the GA98 mutant. In line with the latent evolutionary potential concept, our model shows a gradual sequence-dependent change in fold preference in the mutants before this switch. Our analysis also indicates that a sharp G_A/G_B switch may arise from the orientation dependence of aromatic π-interactions. These findings provide physical insights toward rationalizing, predicting and designing evolutionary conformational switches.

The biological functions of globular proteins are intimately related to their folded structures and their associated conformational fluctuations. Evolution of new structures is an important avenue to new functions. Although many mutations do not change the folded state, experiments indicate that a single amino acid substitution can lead to a drastic change in the folded structure. The physics of this switch-like behavior remains to be elucidated. Here we develop a computational model for the relevant physical forces, showing that mutations can lead to new folds by passing through intermediate sequences where the old and new folds occur with varying probabilities. Our approach helps provide a general physical account of conformational switching in evolution and mutational effects on conformational dynamics.

Evidence that Environmental Heterogeneity Maintains a Detoxifying Enzyme Polymorphism in Drosophila melanogaster

Environmental heterogeneity is thought to be an important process maintaining genetic variation in populations [1-4]: if alternative alleles are favored in different environments, a stable polymorphism can be maintained [1, 5, 6]. This situation has been hypothesized to occur in genes encoding multi-substrate enzymes [7], in which changes that increase activity with one substrate typically decrease activity with others [8-10], but examples of polymorphisms maintained by this mechanism are rare. Here, we present evidence that a polymorphism in an enzyme gene in Drosophila melanogaster is maintained by such a trade-off. The mitochondrially localized aldehyde dehydrogenase in D. melanogaster has two important functions: detoxifying acetaldehyde derived from dietary ethanol [11] and detoxifying larger aldehydes produced as byproducts of oxidative phosphorylation [12]. A derived variant of the enzyme, Leu479Phe, is present in moderate frequencies in most temperate populations but is rare in more ethanol-averse tropical populations. Using purified recombinant protein, we show that the Leu-Phe substitution increases turnover rate of acetaldehyde but decreases turnover rate of larger aldehydes. Furthermore, using transgenic fly lines, we show that the substitution increases lifetime fitness on medium supplemented with an ecologically relevant ethanol concentration but decreases fitness on medium lacking ethanol. The strong, opposing selection pressures, coupled with documented highly variable ethanol concentrations in breeding sites of temperate populations, implicate an essential role for environmental heterogeneity in maintaining the polymorphism.

Handicap-Recover Evolution Leads to a Chemically Versatile, Nucleophile-Permissive Protease

Mutation of the tobacco etch virus (TEV) protease nucleophile from cysteine to serine causes an approximately ∼104 -fold loss in activity. Ten rounds of directed evolution of the mutant, TEVSer , overcame the detrimental effects of nucleophile exchange to recover near-wild-type activity in the mutant TEVSer X. Rather than respecialising TEV to the new nucleophile, all the enzymes along the evolutionary trajectory also retained the ability to use the original cysteine nucleophile. Therefore the adaptive evolution of TEVSer is paralleled by a neutral trajectory for TEVCys , in which mutations that increase serine nucleophile reactivity hardly affect the reactivity of cysteine. This apparent nucleophile permissiveness explains how nucleophile switches can occur in the phylogeny of the chymotrypsin-like protease PA superfamily. Despite the changed key component of their chemical mechanisms, the evolved variants TEVSer X and TEVCys X have similar activities; this could potentially facilitate escape from adaptive conflict to enable active-site evolution.

Smooth functional transition along a mutational pathway with an abrupt protein fold switch

Recent protein design experiments have demonstrated that proteins can migrate between folds through the accumulation of substitution mutations without visiting disordered or nonfunctional points in sequence space. To explore the biophysical mechanism underlying such transitions we use a three-letter continuous protein model with seven atoms per amino acid to provide realistic sequence-structure and sequence-function mappings through explicit simulation of the folding and interaction of model sequences. We start from two 16-amino-acid sequences folding into an α-helix and a β-hairpin, respectively, each of which has a preferred binding partner with 35 amino acids. We identify a mutational pathway between the two folds, which features a sharp fold switch. By contrast, we find that the transition in function is smooth. Moreover, the switch in preferred binding partner does not coincide with the fold switch. Discovery of new folds in evolution might therefore be facilitated by following fitness slopes in sequence space underpinned by binding-induced conformational switching.

Gene duplication and the evolution of moonlighting proteins

Gene duplication is a recurring phenomenon in genome evolution and a major driving force in the gain of biological functions. Here, we examine the role of gene duplication in the origin and maintenance of moonlighting proteins, with special focus on functional redundancy and innovation, molecular tradeoffs, and genetic robustness. An overview of specific examples-mainly from yeast-suggests a widespread conservation of moonlighting behavior in duplicate genes after long evolutionary times. Dosage amplification and incomplete subfunctionalization appear to be prevalent in the maintenance of multifunctionality. We discuss the role of gene-expression divergence and paralog responsiveness in moonlighting proteins with overlapping biochemical properties. Future studies analyzing multifunctional genes in a more systematic and comprehensive manner will not only enable a better understanding of how this emerging class of protein behavior originates and is maintained, but also provide new insights on the mechanisms of evolution by gene duplication.

Biophysics of protein evolution and evolutionary protein biophysics

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence-structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by 'hidden' conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

Ancient Origin and Recent Innovations of RNA Polymerase IV and V

Small RNA-mediated chromatin modification is a conserved feature of eukaryotes. In flowering plants, the short interfering (si)RNAs that direct transcriptional silencing are abundant and subfunctionalization has led to specialized machinery responsible for synthesis and action of these small RNAs. In particular, plants possess polymerase (Pol) IV and Pol V, multi-subunit homologs of the canonical DNA-dependent RNA Pol II, as well as specialized members of the RNA-dependent RNA Polymerase (RDR), Dicer-like (DCL), and Argonaute (AGO) families. Together these enzymes are required for production and activity of Pol IV-dependent (p4-)siRNAs, which trigger RNA-directed DNA methylation (RdDM) at homologous sequences. p4-siRNAs accumulate highly in developing endosperm, a specialized tissue found only in flowering plants, and are rare in nonflowering plants, suggesting that the evolution of flowers might coincide with the emergence of specialized RdDM machinery. Through comprehensive identification of RdDM genes from species representing the breadth of the land plant phylogeny, we describe the ancient origin of Pol IV and Pol V, suggesting that a nearly complete and functional RdDM pathway could have existed in the earliest land plants. We also uncover innovations in these enzymes that are coincident with the emergence of seed plants and flowering plants, and recent duplications that might indicate additional subfunctionalization. Phylogenetic analysis reveals rapid evolution of Pol IV and Pol V subunits relative to their Pol II counterparts and suggests that duplicates were retained and subfunctionalized through Escape from Adaptive Conflict. Evolution within the carboxy-terminal domain of the Pol V largest subunit is particularly striking, where illegitimate recombination facilitated extreme sequence divergence.

Mutational robustness accelerates the origin of novel RNA phenotypes through phenotypic plasticity

Novel phenotypes can originate either through mutations in existing genotypes or through phenotypic plasticity, the ability of one genotype to form multiple phenotypes. From molecules to organisms, plasticity is a ubiquitous feature of life, and a potential source of exaptations, adaptive traits that originated for nonadaptive reasons. Another ubiquitous feature is robustness to mutations, although it is unknown whether such robustness helps or hinders the origin of new phenotypes through plasticity. RNA is ideal to address this question, because it shows extensive plasticity in its secondary structure phenotypes, a consequence of their continual folding and unfolding, and these phenotypes have important biological functions. Moreover, RNA is to some extent robust to mutations. This robustness structures RNA genotype space into myriad connected networks of genotypes with the same phenotype, and it influences the dynamics of evolving populations on a genotype network. In this study I show that both effects help accelerate the exploration of novel phenotypes through plasticity. My observations are based on many RNA molecules sampled at random from RNA sequence space, and on 30 biological RNA molecules. They are thus not only a generic feature of RNA sequence space but are relevant for the molecular evolution of biological RNA.

Whole-genome duplication in teleost fishes and its evolutionary consequences

Whole-genome duplication (WGD) events have shaped the history of many evolutionary lineages. One such duplication has been implicated in the evolution of teleost fishes, by far the most species-rich vertebrate clade. After initial controversy, there is now solid evidence that such event took place in the common ancestor of all extant teleosts. It is termed teleost-specific (TS) WGD. After WGD, duplicate genes have different fates. The most likely outcome is non-functionalization of one duplicate gene due to the lack of selective constraint on preserving both. Mechanisms that act on preservation of duplicates are subfunctionalization (partitioning of ancestral gene functions on the duplicates), neofunctionalization (assigning a novel function to one of the duplicates) and dosage selection (preserving genes to maintain dosage balance between interconnected components). Since the frequency of these mechanisms is influenced by the genes' properties, there are over-retained classes of genes, such as highly expressed ones and genes involved in neural function. The consequences of the TS-WGD, especially its impact on the massive radiation of teleosts, have been matter of controversial debate. It is evident that gene duplications are crucial for generating complexity and that WGDs provide large amounts of raw material for evolutionary adaptation and innovation. However, it is less clear whether the TS-WGD is directly linked to the evolutionary success of teleosts and their radiation. Recent studies let us conclude that TS-WGD has been important in generating teleost complexity, but that more recent ecological adaptations only marginally related to TS-WGD might have even contributed more to diversification. It is likely, however, that TS-WGD provided teleosts with diversification potential that can become effective much later, such as during phases of environmental change.

Interplay between chaperones and protein disorder promotes the evolution of protein networks

Evolution is driven by mutations, which lead to new protein functions but come at a cost to protein stability. Non-conservative substitutions are of interest in this regard because they may most profoundly affect both function and stability. Accordingly, organisms must balance the benefit of accepting advantageous substitutions with the possible cost of deleterious effects on protein folding and stability. We here examine factors that systematically promote non-conservative mutations at the proteome level. Intrinsically disordered regions in proteins play pivotal roles in protein interactions, but many questions regarding their evolution remain unanswered. Similarly, whether and how molecular chaperones, which have been shown to buffer destabilizing mutations in individual proteins, generally provide robustness during proteome evolution remains unclear. To this end, we introduce an evolutionary parameter λ that directly estimates the rate of non-conservative substitutions. Our analysis of λ in Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens sequences reveals how co- and post-translationally acting chaperones differentially promote non-conservative substitutions in their substrates, likely through buffering of their destabilizing effects. We further find that λ serves well to quantify the evolution of intrinsically disordered proteins even though the unstructured, thus generally variable regions in proteins are often flanked by very conserved sequences. Crucially, we show that both intrinsically disordered proteins and highly re-wired proteins in protein interaction networks, which have evolved new interactions and functions, exhibit a higher λ at the expense of enhanced chaperone assistance. Our findings thus highlight an intricate interplay of molecular chaperones and protein disorder in the evolvability of protein networks. Our results illuminate the role of chaperones in enabling protein evolution, and underline the importance of the cellular context and integrated approaches for understanding proteome evolution. We feel that the development of λ may be a valuable addition to the toolbox applied to understand the molecular basis of evolution.

Discriminating binding mechanisms of an intrinsically disordered protein via a multi-state coarse-grained model

Many proteins undergo a conformational transition upon binding to their cognate binding partner, with intrinsically disordered proteins (IDPs) providing an extreme example in which a folding transition occurs. However, it is often not clear whether this occurs via an "induced fit" or "conformational selection" mechanism, or via some intermediate scenario. In the first case, transient encounters with the binding partner favour transitions to the bound structure before the two proteins dissociate, while in the second the bound structure must be selected from a subset of unbound structures which are in the correct state for binding, because transient encounters of the incorrect conformation with the binding partner are most likely to result in dissociation. A particularly interesting situation involves those intrinsically disordered proteins which can bind to different binding partners in different conformations. We have devised a multi-state coarse-grained simulation model which is able to capture the binding of IDPs in alternate conformations, and by applying it to the binding of nuclear coactivator binding domain (NCBD) to either ACTR or IRF-3 we are able to determine the binding mechanism. By all measures, the binding of NCBD to either binding partner appears to occur via an induced fit mechanism. Nonetheless, we also show how a scenario closer to conformational selection could arise by choosing an alternative non-binding structure for NCBD.

Modeling the evolution of molecular systems from a mechanistic perspective

Systems biology-inspired genotype-phenotype mapping models are increasingly being used to study the evolutionary properties of molecular biological systems, in particular the general emergent properties of evolving systems, such as modularity, robustness, and evolvability. However, the level of abstraction at which many of these models operate might not be sufficient to capture all relevant intricacies of biological evolution in sufficient detail. Here, we argue that in particular gene and genome duplications, both evolutionary mechanisms of potentially major importance for the evolution of molecular systems and of special relevance to plant evolution, are not adequately accounted for in most GPM modeling frameworks, and that more fine-grained mechanistic models may significantly advance understanding of how gen(om)e duplication impacts molecular systems evolution.

Origin and functional diversification of an amphibian defense peptide arsenal

The skin secretion of many amphibians contains an arsenal of bioactive molecules, including hormone-like peptides (HLPs) acting as defense toxins against predators, and antimicrobial peptides (AMPs) providing protection against infectious microorganisms. Several amphibian taxa seem to have independently acquired the genes to produce skin-secreted peptide arsenals, but it remains unknown how these originated from a non-defensive ancestral gene and evolved diverse defense functions against predators and pathogens. We conducted transcriptome, genome, peptidome and phylogenetic analyses to chart the full gene repertoire underlying the defense peptide arsenal of the frog Silurana tropicalis and reconstruct its evolutionary history. Our study uncovers a cluster of 13 transcriptionally active genes, together encoding up to 19 peptides, including diverse HLP homologues and AMPs. This gene cluster arose from a duplicated gastrointestinal hormone gene that attained a HLP-like defense function after major remodeling of its promoter region. Instead, new defense functions, including antimicrobial activity, arose by mutation of the precursor proteins, resulting in the proteolytic processing of secondary peptides alongside the original ones. Although gene duplication did not trigger functional innovation, it may have subsequently facilitated the convergent loss of the original function in multiple gene lineages (subfunctionalization), completing their transformation from HLP gene to AMP gene. The processing of multiple peptides from a single precursor entails a mechanism through which peptide-encoding genes may establish new functions without the need for gene duplication to avoid adaptive conflicts with older ones.

Tracing the evolution of angucyclinone monooxygenases: structural determinants for C-12b hydroxylation and substrate inhibition in PgaE

Two functionally distinct homologous flavoprotein hydroxylases, PgaE and JadH, have been identified as branching points in the biosynthesis of the polyketide antibiotics gaudimycin C and jadomycin A, respectively. These evolutionarily related enzymes are both bifunctional and able to catalyze the same initial reaction, C-12 hydroxylation of the common angucyclinone intermediate prejadomycin. The enzymes diverge in their secondary activities, which include hydroxylation at C-12b by PgaE and dehydration at C-4a/C-12b by JadH. A further difference is that the C-12 hydroxylation is subject to substrate inhibition only in PgaE. Here we have identified regions associated with the C-12b hydroxylation in PgaE by extensive chimeragenesis, focusing on regions surrounding the active site. The results highlight the importance of a hairpin-β motif near the dimer interface, with two nonconserved residues, P78 and I79 (corresponding to Q89 and F90, respectively, in JadH), and invariant residue H73 playing key roles. Kinetic characterization of PgaE variants demonstrates that the secondary C-12b hydroxylation and substrate inhibition by prejadomycin are likely to be interlinked. The crystal structure of the PgaE P78Q/I79F variant at 2.4 Å resolution confirms that the changes do not alter the conformation of the β-strand secondary structure and that the side chains of these residues in effect point away from the active site toward the dimer interface. The results support a catalytic model for PgaE containing two binding modes for C-12 and C-12b hydroxylations, where binding of prejadomycin in the orientation for C-12b hydroxylation leads to substrate inhibition. The presence of an allosteric network is evident based on enzyme kinetics.

Helical ambivalency induced by point mutations

Background

Mutation of amino acid sequences in a protein may have diverse effects on its structure and function. Point mutations of even a single amino acid residue in the helices of the non-redundant database may lead to sequentially identical peptides which adopt different secondary structures in different proteins. However, various physico-chemical factors which govern the formation of these ambivalent helices generated by point mutations of a sequence are not clearly known.

Results

Sequences generated by point mutations of helices are mapped on to their non-helical counterparts in the SCOP database. The results show that short helices are prone to transform into non-helical conformations upon point mutations. Mutation of amino acid residues by helix breakers preferentially yield non-helical conformations, while mutation with residues of intermediate helix propensity display least preferences for non-helical conformations. Differences in the solvent accessibility of the mutating/mutated residues are found to be a major criteria for these sequences to conform to non-helical conformations. Even with minimal differences in the amino acid distributions of the sequences flanking the helical and non-helical conformations, helix-flanking sequences are found be more solvent accessible.

Conclusions

All types of mutations from helical to non-helical conformations are investigated. The primary factors attributing such changes in conformation can be: i) type/propensity of the mutating and mutant residues ii) solvent accessibility of the residue at the mutation site iii) context/environment dependence of the flanking sequences. The results from the present study may be used to design de novo proteins via point mutations.

A polymetamorphic protein

Arc repressor is a homodimeric protein with a ribbon-helix-helix fold. A single polar-to-hydrophobic substitution (N11L) at a solvent-exposed position leads to population of an alternate dimeric fold in which 3₁₀ helices replace a β-sheet. Here we find that the variant Q9V/N11L/R13V (S-VLV), with two additional polar-to-hydrophobic surface mutations in the same β-sheet, forms a highly stable, reversibly folded octamer with approximately half the α-helical content of wild-type Arc. At low protein concentration and low ionic strength, S-VLV also populates both dimeric topologies previously observed for N11L, as judged by NMR chemical shift comparisons. Thus, accumulation of simple hydrophobic mutations in Arc progressively reduces fold specificity, leading first to a sequence with two folds and then to a manifold bridge sequence with at least three different topologies. Residues 9-14 of S-VLV form a highly hydrophobic stretch that is predicted to be amyloidogenic, but we do not observe aggregates of higher order than octamer. Increases in sequence hydrophobicity can promote amyloid aggregation but also exert broader and more complex effects on fold specificity. Altered native folds, changes in fold coupled to oligomerization, toxic pre-amyloid oligomers, and amyloid fibrils may represent a near continuum of accessible alternatives in protein structure space.

Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed.

Proteins are essential molecules for performing a majority of functions in all biological systems. These functions often depend on the three-dimensional structures of proteins. Here, we investigate a fundamental question in molecular evolution: how can proteins acquire new advantageous structures via mutations while not sacrificing their existing structures that are still needed? Some authors have suggested that the same protein may adopt two or more alternative structures, switch between them and thus perform different functions with each of the alternative structures. Intuitively, such a protein could provide an evolutionary compromise between conflicting demands for existing and new protein structures. Yet no theoretical study has systematically tackled the biophysical basis of such compromises during evolutionary processes. Here we devise a model of evolution that specifically recognizes protein molecules that can exist in several different stable structures. Our model demonstrates that proteins can indeed utilize multiple structures to satisfy conflicting evolutionary requirements. In light of these results, we identify data from known protein structures that are consistent with our predictions and suggest novel directions for future investigation.