Relative tolerance of mesostable and thermostable protein homologs to extensive mutation

Distribution and molecular evolution of the anti-CRISPR family AcrIF7

Anti-clustered regularly interspaced short palindromic repeats (CRISPRs) are proteins capable of blocking CRISPR-Cas systems and typically their genes are located on mobile genetic elements. Since their discovery, numerous anti-CRISPR families have been identified. However, little is known about the distribution and sequence diversity of members within a family, nor how these traits influence the anti-CRISPR's function and evolution. Here, we use AcrIF7 to explore the dissemination and molecular evolution of an anti-CRISPR family. We uncovered 5 subclusters and prevalent anti-CRISPR variants within the group. Remarkably, AcrIF7 homologs display high similarity despite their broad geographical, ecological, and temporal distribution. Although mainly associated with Pseudomonas aeruginosa, AcrIF7 was identified in distinct genetic backgrounds indicating horizontal dissemination, primarily by phages. Using mutagenesis, we recreated variation observed in databases but also extended the sequence diversity of the group. Characterisation of the variants identified residues key for the anti-CRISPR function and other contributing to its mutational tolerance. Moreover, molecular docking revealed that variants with affected function lose key interactions with its CRISPR-Cas target. Analysis of publicly available data and the generated variants suggests that the dominant AcrIF7 variant corresponds to the minimal and optimal anti-CRISPR selected in the family. Our study provides a blueprint to investigate the molecular evolution of anti-CRISPR families.

A Trait-Based Approach to Predicting Viral Host-Range Evolvability

Predicting the evolution of virus host range has proven to be extremely difficult, in part because of the sheer diversity of viruses, each with unique biology and ecological interactions. We have not solved this problem, but to make the problem more tractable, we narrowed our focus to three traits intrinsic to all viruses that may play a role in host-range evolvability: mutation rate, recombination rate, and phenotypic heterogeneity. Although each trait should increase evolvability, they cannot do so unbounded because fitness trade-offs limit the ability of all three traits to maximize evolvability. By examining these constraints, we can begin to identify groups of viruses with suites of traits that make them especially concerning, as well as ecological and environmental conditions that might push evolution toward accelerating host-range expansion.

Viral protein instability enhances host-range evolvability

Viruses are highly evolvable, but what traits endow this property? The high mutation rates of viruses certainly play a role, but factors that act above the genetic code, like protein thermostability, are also expected to contribute. We studied how the thermostability of a model virus, bacteriophage λ, affects its ability to evolve to use a new receptor, a key evolutionary transition that can cause host-range evolution. Using directed evolution and synthetic biology techniques we generated a library of host-recognition protein variants with altered stabilities and then tested their capacity to evolve to use a new receptor. Variants fell within three stability classes: stable, unstable, and catastrophically unstable. The most evolvable were the two unstable variants, whereas seven of eight stable variants were significantly less evolvable, and the two catastrophically unstable variants could not grow. The slowly evolving stable variants were delayed because they required an additional destabilizing mutation. These results are particularly noteworthy because they contradict a widely supported contention that thermostabilizing mutations enhance evolvability of proteins by increasing mutational robustness. Our work suggests that the relationship between thermostability and evolvability is more complex than previously thought, provides evidence for a new molecular model of host-range expansion evolution, and identifies instability as a potential predictor of viral host-range evolution.

Understanding how viruses evolve to infect new hosts is critical for predicting host shifts as well as tuning host-range in phage therapy applications. Yet a mechanistic understanding of the molecular steps required to shift hosts has not been achieved. For this study we examined the evolutionary potential of different strains of a model virus, bacteriophage λ, to gain the ability to use a new receptor, a key step in host shifts. We discovered that λ variants with destabilized host-recognition proteins were more likely to evolve the necessary mutations to use the new receptor than stabilized variants. However, destabilization was only beneficial to a certain point and variants with overly unstable proteins lost all function. These results led us to propose a new molecular model for receptor use evolution in λ; 1) destabilizing mutations evolve that provide protein structural flexibility that allows new protein conformations to form that are able to interact with the new receptors, and 2) mutations evolve that alter the binding surface chemical properties to assist interactions with the new receptor. Our work with a model virus-host system, points to the potential use of viral stability as a phenotypic indicator of the capacity for virus host-range evolution.

Modeling-Assisted Design of Thermostable Benzaldehyde Lyases from Rhodococcus erythropolis for Continuous Production of α-Hydroxy Ketones

Enantiopure α-hydroxy ketones are important building blocks of active pharmaceutical ingredients (APIs), which can be produced by thiamine-diphosphate-dependent lyases, such as benzaldehyde lyase. Here we report the discovery of a novel thermostable benzaldehyde lyase from Rhodococcus erythropolis R138 (ReBAL). While the overall sequence identity to the only experimentally confirmed benzaldehyde lyase from Pseudomonas fluorescens Biovar I (PfBAL) was only 65 %, comparison of a structural model of ReBAL with the crystal structure of PfBAL revealed only four divergent amino acids in the substrate binding cavity. Based on rational design, we generated two ReBAL variants, which were characterized along with the wild-type enzyme in terms of their substrate spectrum, thermostability and biocatalytic performance in the presence of different co-solvents. We found that the new enzyme variants have a significantly higher thermostability (up to 22 °C increase in T₅₀ ) and a different co-solvent-dependent activity. Using the most stable variant immobilized in packed-bed reactors via the SpyCatcher/SpyTag system, (R)-benzoin was synthesized from benzaldehyde over a period of seven days with a stable space-time-yield of 9.3 mmol ⋅ L^-1  ⋅ d^-1 . Our work expands the important class of benzaldehyde lyases and therefore contributes to the development of continuous biocatalytic processes for the production of α-hydroxy ketones and APIs.

Mutational and biophysical robustness in a prestabilized monobody

The fibronectin type III (FN3) monobody domain is a promising non-antibody scaffold, which features a less complex architecture than an antibody while maintaining analogous binding loops. We previously developed FN3Con, a hyperstable monobody derivative with diagnostic and therapeutic potential. Prestabilization of the scaffold mitigates the stability–function trade-off commonly associated with evolving a protein domain toward biological activity. Here, we aimed to examine if the FN3Con monobody could take on antibody-like binding to therapeutic targets, while retaining its extreme stability. We targeted the first of the Adnectin derivative of monobodies to reach clinical trials, which was engineered by directed evolution for binding to the therapeutic target VEGFR2; however, this function was gained at the expense of large losses in thermostability and increased oligomerization. In order to mitigate these losses, we grafted the binding loops from Adnectin-anti-VEGFR2 (CT-322) onto the prestabilized FN3Con scaffold to produce a domain that successfully bound with high affinity to the therapeutic target VEGFR2. This FN3Con-anti-VEGFR2 construct also maintains high thermostability, including remarkable long-term stability, retaining binding activity after 2 years of storage at 36 °C. Further investigations into buffer excipients doubled the presence of monomeric monobody in accelerated stability trials. These data suggest that loop grafting onto a prestabilized scaffold is a viable strategy for the development of monobody domains with desirable biophysical characteristics and that FN3Con is therefore well-suited to applications such as the evolution of multiple paratopes or shelf-stable diagnostics and therapeutics.

Large-scale in silico mutagenesis experiments reveal optimization of genetic code and codon usage for protein mutational robustness

Background

How, and the extent to which, evolution acts on DNA and protein sequences to ensure mutational robustness and evolvability is a long-standing open question in the field of molecular evolution. We addressed this issue through the first structurome-scale computational investigation, in which we estimated the change in folding free energy upon all possible single-site mutations introduced in more than 20,000 protein structures, as well as through available experimental stability and fitness data.

Results

At the amino acid level, we found the protein surface to be more robust against random mutations than the core, this difference being stronger for small proteins. The destabilizing and neutral mutations are more numerous in the core and on the surface, respectively, whereas the stabilizing mutations are about 4% in both regions. At the genetic code level, we observed smallest destabilization for mutations that are due to substitutions of base III in the codon, followed by base I, bases I+III, base II, and other multiple base substitutions. This ranking highly anticorrelates with the codon-anticodon mispairing frequency in the translation process. This suggests that the standard genetic code is optimized to limit the impact of random mutations, but even more so to limit translation errors. At the codon level, both the codon usage and the usage bias appear to optimize mutational robustness and translation accuracy, especially for surface residues.

Conclusion

Our results highlight the non-universality of mutational robustness and its multiscale dependence on protein features, the structure of the genetic code, and the codon usage. Our analyses and approach are strongly supported by available experimental mutagenesis data.

Computational Design of Enantiocomplementary Epoxide Hydrolases for Asymmetric Synthesis of Aliphatic and Aromatic Diols

The use of enzymes in preparative biocatalysis often requires tailoring enzyme selectivity by protein engineering. Herein we explore the use of computational library design and molecular dynamics simulations to create variants of limonene epoxide hydrolase that produce enantiomeric diols from meso‐epoxides. Three substrates of different sizes were targeted: cis‐2,3‐butene oxide, cyclopentene oxide, and cis‐stilbene oxide. Most of the 28 designs tested were active and showed the predicted enantioselectivity. Excellent enantioselectivities were obtained for the bulky substrate cis‐stilbene oxide, and enantiocomplementary mutants produced (S,S)‐ and (R,R)‐stilbene diol with >97 % enantiomeric excess. An (R,R)‐selective mutant was used to prepare (R,R)‐stilbene diol with high enantiopurity (98 % conversion into diol, >99 % ee). Some variants displayed higher catalytic rates (k_cat) than the original enzyme, but in most cases K_M values increased as well. The results demonstrate the feasibility of computational design and screening to engineer enantioselective epoxide hydrolase variants with very limited laboratory screening.

Artificial Metalloenzymes on the Verge of New-to-Nature Metabolism

Residing at the interface of chemistry and biotechnology, artificial metalloenzymes (ArMs) offer an attractive technology to combine the versatile reaction repertoire of transition metal catalysts with the exquisite catalytic features of enzymes. While earlier efforts in this field predominantly comprised studies in well-defined test-tube environments, a trend towards exploiting ArMs in more complex environments has recently emerged. Integration of these artificial biocatalysts in enzymatic cascades and using them in whole-cell biotransformations and in vivo opens up entirely novel prospects for both preparative chemistry and synthetic biology. We highlight selected recent developments with a particular focus on challenges and opportunities in the in vivo application of ArMs.

Enzyme Efficiency but Not Thermostability Drives Cefotaxime Resistance Evolution in TEM-1 β-Lactamase

A leading intellectual challenge in evolutionary genetics is to identify the specific phenotypes that drive adaptation. Enzymes offer a particularly promising opportunity to pursue this question, because many enzymes' contributions to organismal fitness depend on a comparatively small number of experimentally accessible properties. Moreover, on first principles the demands of enzyme thermostability stand in opposition to the demands of catalytic activity. This observation, coupled with the fact that enzymes are only marginally thermostable, motivates the widely held hypothesis that mutations conferring functional improvement require compensatory mutations to restore thermostability. Here, we explicitly test this hypothesis for the first time, using four missense mutations in TEM-1 β-lactamase that jointly increase cefotaxime Minimum Inhibitory Concentration (MIC) ∼1500-fold. First, we report enzymatic efficiency (kcat/KM) and thermostability (Tm, and thence ΔG of folding) for all combinations of these mutations. Next, we fit a quantitative model that predicts MIC as a function of kcat/KM and ΔG. While kcat/KM explains ∼54% of the variance in cefotaxime MIC (∼92% after log transformation), ΔG does not improve explanatory power of the model. We also find that cefotaxime MIC rises more slowly in kcat/KM than predicted. Several explanations for these discrepancies are suggested. Finally, we demonstrate substantial sign epistasis in MIC and kcat/KM, and antagonistic pleiotropy between phenotypes, in spite of near numerical additivity in the system. Thus constraints on selectively accessible trajectories, as well as limitations in our ability to explain such constraints in terms of underlying mechanisms are observed in a comparatively "well-behaved" system.

A robust cosolvent-compatible halohydrin dehalogenase by computational library design

To improve the applicability of halohydrin dehalogenase as a catalyst for reactions in the presence of organic cosolvents, we explored a computational library design strategy (Framework for Rapid Enzyme Stabilization by Computational libraries) that involves discovery and in silico evaluation of stabilizing mutations. Energy calculations, disulfide bond predictions and molecular dynamics simulations identified 218 point mutations and 35 disulfide bonds with predicted stabilizing effects. Experiments confirmed 29 stabilizing point mutations, most of which were located in two distinct regions, whereas introduction of disulfide bonds was not effective. Combining the best mutations resulted in a 12-fold mutant (HheC-H12) with a 28°C higher apparent melting temperature and a remarkable increase in resistance to cosolvents. This variant also showed a higher optimum temperature for catalysis while activity at low temperature was preserved. Mutant H12 was used as a template for the introduction of mutations that enhance enantioselectivity or activity. Crystal structures showed that the structural changes in the H12 mutant mostly agreed with the computational predictions and that the enhanced stability was mainly due to mutations that redistributed surface charges and improved interactions between subunits, the latter including better interactions of water molecules at the subunit interfaces.

Effect of Mutation and Substrate Binding on the Stability of Cytochrome P450BM3 Variants

Cytochrome P450BM3 is a heme-containing enzyme from Bacillus megaterium that exhibits high monooxygenase activity and has a self-sufficient electron transfer system in the full-length enzyme. Its potential synthetic applications drive protein engineering efforts to produce variants capable of oxidizing nonnative substrates such as pharmaceuticals and aromatic pollutants. However, promiscuous P450BM3 mutants often exhibit lower stability, thereby hindering their industrial application. This study demonstrated that the heme domain R47L/F87V/L188Q/E267V/F81I pentuple mutant (PM) is destabilized because of the disruption of hydrophobic contacts and salt bridge interactions. This was directly observed from crystal structures of PM in the presence and absence of ligands (palmitic acid and metyrapone). The instability of the tertiary structure and heme environment of substrate-free PM was confirmed by pulse proteolysis and circular dichroism, respectively. Binding of the inhibitor, metyrapone, significantly stabilized PM, but the presence of the native substrate, palmitic acid, had no effect. On the basis of high-temperature molecular dynamics simulations, the lid domain, β-sheet 1, and Cys ligand loop (a β-bulge segment connected to the heme) are the most labile regions and, thus, potential sites for stabilizing mutations. Possible approaches to stabilization include improvement of hydrophobic packing interactions in the lid domain and introduction of new salt bridges into β-sheet 1 and the heme region. An understanding of the molecular factors behind the loss of stability of P450BM3 variants therefore expedites site-directed mutagenesis studies aimed at developing thermostability.

The Structure of a Thermophilic Kinase Shapes Fitness upon Random Circular Permutation

Proteins can be engineered for synthetic biology through circular permutation, a sequence rearrangement in which native protein termini become linked and new termini are created elsewhere through backbone fission. However, it remains challenging to anticipate a protein's functional tolerance to circular permutation. Here, we describe new transposons for creating libraries of randomly circularly permuted proteins that minimize peptide additions at their termini, and we use transposase mutagenesis to study the tolerance of a thermophilic adenylate kinase (AK) to circular permutation. We find that libraries expressing permuted AKs with either short or long peptides amended to their N-terminus yield distinct sets of active variants and present evidence that this trend arises because permuted protein expression varies across libraries. Mapping all sites that tolerate backbone cleavage onto AK structure reveals that the largest contiguous regions of sequence that lack cleavage sites are proximal to the phosphotransfer site. A comparison of our results with a range of structure-derived parameters further showed that retention of function correlates to the strongest extent with the distance to the phosphotransfer site, amino acid variability in an AK family sequence alignment, and residue-level deviations in superimposed AK structures. Our work illustrates how permuted protein libraries can be created with minimal peptide additions using transposase mutagenesis, and it reveals a challenge of maintaining consistent expression across permuted variants in a library that minimizes peptide additions. Furthermore, these findings provide a basis for interpreting responses of thermophilic phosphotransferases to circular permutation by calibrating how different structure-derived parameters relate to retention of function in a cellular selection.

Archaeal Nucleic Acid Ligases and Their Potential in Biotechnology

With their ability to catalyse the formation of phosphodiester linkages, DNA ligases and RNA ligases are essential tools for many protocols in molecular biology and biotechnology. Currently, the nucleic acid ligases from bacteriophage T4 are used extensively in these protocols. In this review, we argue that the nucleic acid ligases from Archaea represent a largely untapped pool of enzymes with diverse and potentially favourable properties for new and emerging biotechnological applications. We summarise the current state of knowledge on archaeal DNA and RNA ligases, which makes apparent the relative scarcity of information on in vitro activities that are of most relevance to biotechnologists (such as the ability to join blunt- or cohesive-ended, double-stranded DNA fragments). We highlight the existing biotechnological applications of archaeal DNA ligases and RNA ligases. Finally, we draw attention to recent experiments in which protein engineering was used to modify the activities of the DNA ligase from Pyrococcus furiosus and the RNA ligase from Methanothermobacter thermautotrophicus, thus demonstrating the potential for further work in this area.

Natural Variants of the KPC-2 Carbapenemase have Evolved Increased Catalytic Efficiency for Ceftazidime Hydrolysis at the Cost of Enzyme Stability

The spread of β-lactamases that hydrolyze penicillins, cephalosporins and carbapenems among Gram-negative bacteria has limited options for treating bacterial infections. Initially, Klebsiella pneumoniae carbapenemase-2 (KPC-2) emerged as a widespread carbapenem hydrolyzing β-lactamase that also hydrolyzes penicillins and cephalosporins but not cephamycins and ceftazidime. In recent years, single and double amino acid substitution variants of KPC-2 have emerged among clinical isolates that show increased resistance to ceftazidime. Because it confers multi-drug resistance, KPC β-lactamase is a threat to public health. In this study, the evolution of KPC-2 function was determined in nine clinically isolated variants by examining the effects of the substitutions on enzyme kinetic parameters, protein stability and antibiotic resistance profile. The results indicate that the amino acid substitutions associated with KPC-2 natural variants lead to increased catalytic efficiency for ceftazidime hydrolysis and a consequent increase in ceftazidime resistance. Single substitutions lead to modest increases in catalytic activity while the double mutants exhibit significantly increased ceftazidime hydrolysis and resistance levels. The P104R, V240G and H274Y substitutions in single and double mutant combinations lead to the largest increases in ceftazidime hydrolysis and resistance. Molecular modeling suggests that the P104R and H274Y mutations could facilitate ceftazidime hydrolysis through increased hydrogen bonding interactions with the substrate while the V240G substitution may enhance backbone flexibility so that larger substrates might be accommodated in the active site. Additionally, we observed a strong correlation between gain of catalytic function for ceftazidime hydrolysis and loss of enzyme stability, which is in agreement with the ‘stability-function tradeoff’ phenomenon. The high T_m of KPC-2 (66.5°C) provides an evolutionary advantage as compared to other class A enzymes such as TEM (51.5°C) and CTX-M (51°C) in that it can acquire multiple destabilizing substitutions without losing the ability to fold into a functional enzyme.

The absence of new antibiotics combined with the emergence of antibiotic-resistance enzymes like KPC-2 that can inactivate most β-lactam antibiotics has resulted in a longer duration of medical treatment, higher costs of medical care, and increased mortality. In recent years, a number of amino acid sequence variants of KPC-2 have been identified in clinical isolates worldwide suggesting continued evolution of resistance in KPC-2. In this study we have characterized nine clinically isolated variants of KPC-2 (KPC-3 to -11) that differ from the initial KPC-2 isolate by one to two amino acids. The KPC variants confer increased resistance to the antibiotic ceftazidime as compared to KPC-2. This increase in resistance is correlated with improved ability of the variant enzymes to hydrolyze the antibiotic. Additionally, the changes associated with increased ceftazidime hydrolysis also reduce the thermal stability of the enzyme, indicating the mutations that assist catalysis come with a cost on the overall stability of the enzyme. The high thermal stability of KPC-2 allows destabilizing mutations that enhance catalysis to accumulate while the enzyme retains a folded, functional structure. Thus, the high stability of KPC-2 provides an evolutionary advantage to acquire multiple mutations and retain function as compared to other β-lactamase enzymes.

Comparative laboratory evolution of ordered and disordered enzymes

Intrinsically disordered proteins are ubiquitous in nature. To assess potential evolutionary advantages and disadvantages of structural disorder under controlled laboratory conditions, we directly compared the evolvability of weakly active ordered and disordered variants of dihydrofolate reductase by genetic selection. The circularly permuted Escherichia coli enzyme, which exists as a molten globule in the absence of ligands, and a well folded deletion mutant of the Bacillus stearothermophilus enzyme served as starting points. Both scaffolds evolved at similar rates and to similar extents, reaching near-native activity after three rounds of mutagenesis and selection. Surprisingly, however, the starting structural properties of the two scaffolds changed only marginally during optimization. Although the ordered and disordered proteins accumulated distinct sets of mutations, the changes introduced likely improved catalytic efficiency indirectly in both cases by bolstering the network of dynamic conformational fluctuations that productively couple into the reaction coordinate.

Robust enzyme design: bioinformatic tools for improved protein stability

The ability of proteins and enzymes to maintain a functionally active conformation under adverse environmental conditions is an important feature of biocatalysts, vaccines, and biopharmaceutical proteins. From an evolutionary perspective, robust stability of proteins improves their biological fitness and allows for further optimization. Viewed from an industrial perspective, enzyme stability is crucial for the practical application of enzymes under the required reaction conditions. In this review, we analyze bioinformatic-driven strategies that are used to predict structural changes that can be applied to wild type proteins in order to produce more stable variants. The most commonly employed techniques can be classified into stochastic approaches, empirical or systematic rational design strategies, and design of chimeric proteins. We conclude that bioinformatic analysis can be efficiently used to study large protein superfamilies systematically as well as to predict particular structural changes which increase enzyme stability. Evolution has created a diversity of protein properties that are encoded in genomic sequences and structural data. Bioinformatics has the power to uncover this evolutionary code and provide a reproducible selection of hotspots - key residues to be mutated in order to produce more stable and functionally diverse proteins and enzymes. Further development of systematic bioinformatic procedures is needed to organize and analyze sequences and structures of proteins within large superfamilies and to link them to function, as well as to provide knowledge-based predictions for experimental evaluation.

Payoffs, not tradeoffs, in the adaptation of a virus to ostensibly conflicting selective pressures

The genetic architecture of many phenotypic traits is such that genes often contribute to multiple traits, and mutations in these genes can therefore affect multiple phenotypes. These pleiotropic interactions often manifest as tradeoffs between traits where improvement in one property entails a cost in another. The life cycles of many pathogens include periods of growth within a host punctuated with transmission events, such as passage through a digestive tract or a passive stage of exposure in the environment. Populations exposed to such fluctuating selective pressures are expected to acquire mutations showing tradeoffs between reproduction within and survival outside of a host. We selected for individual mutations under fluctuating selective pressures for a ssDNA microvirid bacteriophage by alternating selection for increased growth rate with selection on biophysical properties of the phage capsid in high-temperature or low-pH conditions. Surprisingly, none of the seven unique mutations identified showed a pleiotropic cost; they all improved both growth rate and pH or temperature stability, suggesting that single mutations even in a simple genetic system can simultaneously improve two distinct traits. Selection on growth rate alone revealed tradeoffs, but some mutations still benefited both traits. Tradeoffs were therefore prevalent when selection acted on a single trait, but payoffs resulted when multiple traits were selected for simultaneously. We employed a molecular-dynamics simulation method to determine the mechanisms underlying beneficial effects for three heat-shock mutations. All three mutations significantly enhanced the affinities of protein-protein interfacial bindings, thereby improving capsid stability. The ancestral residues at the mutation sites did not contribute to protein-protein interfacial binding, indicating that these sites acquired a new function. Computational models, such as those used here, may be used in future work not only as predictive tools for mutational effects on protein stability but, ultimately, for evolution.

Computational library design for increasing haloalkane dehalogenase stability

We explored the use of a computational design framework for the stabilization of the haloalkane dehalogenase LinB. Energy calculations, disulfide bond design, molecular dynamics simulations, and rational inspection of mutant structures predicted many stabilizing mutations. Screening of these in small mutant libraries led to the discovery of seventeen point mutations and one disulfide bond that enhanced thermostability. Mutations located in or contacting flexible regions of the protein had a larger stabilizing effect than mutations outside such regions. The combined introduction of twelve stabilizing mutations resulted in a LinB mutant with a 23 °C increase in apparent melting temperature (Tm,app , 72.5 °C) and an over 200-fold longer half-life at 60 °C. The most stable LinB variants also displayed increased compatibility with co-solvents, thus allowing substrate conversion and kinetic resolution at much higher concentrations than with the wild-type enzyme.

300-Fold increase in production of the Zn2+-dependent dechlorinase TrzN in soluble form via apoenzyme stabilization

Microbial metalloenzymes constitute a large library of biocatalysts, a number of which have already been shown to catalyze the breakdown of toxic chemicals or industrially relevant chemical transformations. However, while there is considerable interest in harnessing these catalysts for biotechnology, for many of the enzymes, their large-scale production in active, soluble form in recombinant systems is a significant barrier to their use. In this work, we demonstrate that as few as three mutations can result in a 300-fold increase in the expression of soluble TrzN, an enzyme from Arthrobacter aurescens with environmental applications that catalyzes the hydrolysis of triazine herbicides, in Escherichia coli. Using a combination of X-ray crystallography, kinetic analysis, and computational simulation, we show that the majority of the improvement in expression is due to stabilization of the apoenzyme rather than the metal ion-bound holoenzyme. This provides a structural and mechanistic explanation for the observation that many compensatory mutations can increase levels of soluble-protein production without increasing the stability of the final, active form of the enzyme. This study provides a molecular understanding of the importance of the stability of metal ion free states to the accumulation of soluble protein and shows that differences between apoenzyme and holoenzyme structures can result in mutations affecting the stability of either state differently.

Computationally designed libraries for rapid enzyme stabilization

The ability to engineer enzymes and other proteins to any desired stability would have wide-ranging applications. Here, we demonstrate that computational design of a library with chemically diverse stabilizing mutations allows the engineering of drastically stabilized and fully functional variants of the mesostable enzyme limonene epoxide hydrolase. First, point mutations were selected if they significantly improved the predicted free energy of protein folding. Disulfide bonds were designed using sampling of backbone conformational space, which tripled the number of experimentally stabilizing disulfide bridges. Next, orthogonal in silico screening steps were used to remove chemically unreasonable mutations and mutations that are predicted to increase protein flexibility. The resulting library of 64 variants was experimentally screened, which revealed 21 (pairs of) stabilizing mutations located both in relatively rigid and in flexible areas of the enzyme. Finally, combining 10-12 of these confirmed mutations resulted in multi-site mutants with an increase in apparent melting temperature from 50 to 85°C, enhanced catalytic activity, preserved regioselectivity and a >250-fold longer half-life. The developed Framework for Rapid Enzyme Stabilization by Computational libraries (FRESCO) requires far less screening than conventional directed evolution.

Computational design of novel enzymes without cofactors

In this review we present a recently developed computational method to design de novo enzymes. Starting from the three-dimensional arrangement of the transition state structure and the catalytic side chains around it (theozyme), RosettaMatch identifies successful placements of the theozyme into protein scaffolds. Subsequently, RosettaEnzDes (for EnzymeDesign) redesigns the active site around the theozyme for binding and stabilization of the transition state and the catalytic residues. The resulting computationally designed enzymes are expressed and experimentally tested for catalytic activity.

Probing impact of active site residue mutations on stability and activity of Neisseria polysaccharea amylosucrase

The amylosucrase from Neisseria polysaccharea is a transglucosidase from the GH13 family of glycoside-hydrolases that naturally catalyzes the synthesis of α-glucans from the widely available donor sucrose. Interestingly, natural molecular evolution has modeled a dense hydrogen bond network at subsite -1 responsible for the specific recognition of sucrose and conversely, it has loosened interactions at the subsite +1 creating a highly promiscuous subsite +1. The residues forming these subsites are considered to be likely involved in the activity as well as the overall stability of the enzyme. To assess their role, a structure-based approach was followed to reshape the subsite -1. A strategy based on stability change predictions, using the FoldX algorithm, was considered to identify the best candidates for site-directed mutagenesis and guide the construction of a small targeted library. A miniaturized purification protocol was developed and both mutant stability and substrate promiscuity were explored. A range of 8 °C between extreme melting temperature values was observed and some variants were able to synthesize series of oligosaccharides with distributions differing from that of the parental enzyme. The crucial role of subsite -1 was thus highlighted and the biocatalysts generated can now be considered as starting points for further engineering purposes.

Structure- and sequence-analysis inspired engineering of proteins for enhanced thermostability

Protein engineering strategies for increasing stability can be improved by replacing random mutagenesis and high-throughput screening by approaches that include bioinformatics and computational design. Mutations can be focused on regions in the structure that are most flexible and involved in the early steps of thermal unfolding. Sequence analysis can often predict the position and nature of stabilizing mutations, and may allow the reconstruction of thermostable ancestral sequences. Various computational tools make it possible to design stabilizing features, such as hydrophobic clusters and surface charges. Different methods for designing chimeric enzymes can also support the engineering of more stable proteins without the need of high-throughput screening.

A computational-experimental approach identifies mutations that enhance surface expression of an oseltamivir-resistant influenza neuraminidase

The His274→Tyr (H274Y) oseltamivir (Tamiflu) resistance mutation causes a substantial decrease in the total levels of surface-expressed neuraminidase protein and activity in early isolates of human seasonal H1N1 influenza, and in the swine-origin pandemic H1N1. In seasonal H1N1, H274Y only became widespread after the occurrence of secondary mutations that counteracted this decrease. H274Y is currently rare in pandemic H1N1, and it remains unclear whether secondary mutations exist that might similarly counteract the decreased neuraminidase surface expression associated with this resistance mutation in pandemic H1N1. Here we investigate the possibility of predicting such secondary mutations. We first test the ability of several computational approaches to retrospectively identify the secondary mutations that enhanced levels of surface-expressed neuraminidase protein and activity in seasonal H1N1 shortly before the emergence of oseltamivir resistance. We then use the most successful computational approach to predict a set of candidate secondary mutations to the pandemic H1N1 neuraminidase. We experimentally screen these mutations, and find that several of them do indeed partially counteract the decrease in neuraminidase surface expression caused by H274Y. Two of the secondary mutations together restore surface-expressed neuraminidase activity to wildtype levels, and also eliminate the very slight decrease in viral growth in tissue-culture caused by H274Y. Our work therefore demonstrates a combined computational-experimental approach for identifying mutations that enhance neuraminidase surface expression, and describes several specific mutations with the potential to be of relevance to the spread of oseltamivir resistance in pandemic H1N1.

Stabilization of a metabolic enzyme by library selection in Thermus thermophilus

The anthranilate phosphoribosyl transferase from the hyperthermophilic archaeon Sulfolobus solfataricus (sAnPRT, encoded by strpD), which catalyzes the third step in tryptophan biosynthesis, is a thermostable homodimer with low enzymatic activity at room temperature. We have combined two mutations leading to the monomerization and two mutations leading to the activation of sAnPRT. The resulting "activated monomer" sAnPRT-I36E-M47D+D83G-F149S, which is much more labile than wild-type sAnPRT, was stabilized by a combination of random mutagenesis and metabolic library selection using the extremely thermophilic bacterium Thermus thermophilus as host. This approach led to the identification of five mutations that individually increased the thermal stability of sAnPRT-I36E-M47D+D83G-F149S by 1 to 8 °C, and by 13 °C when combined. The beneficial exchanges were located in different parts of the protein structure, but none of them led to the "re-dimerization" of the enzyme. We observed a negative correlation between thermal stability and catalytic activity of the mutants; this suggests that conformational flexibility is required for catalysis by sAnPRT.

Mesophilic and hyperthermophilic adenylate kinases differ in their tolerance to random fragmentation

The extent to which thermostability influences the location of protein fragmentation sites that allow retention of function is not known. To evaluate this, we used a novel transposase-based approach to create libraries of vectors that express structurally-related fragments of Bacillus subtilis adenylate kinase (BsAK) and Thermotoga neapolitana adenylate kinase (TnAK) with identical modifications at their termini, and we selected for variants in each library that complement the growth of Escherichia coli with a temperature-sensitive adenylate kinase (AK). Mutants created using the hyperthermophilic TnAK were found to support growth with a higher frequency (44%) than those generated from the mesophilic BsAK (6%), and selected TnAK mutants complemented E. coli growth more strongly than homologous BsAK variants. Sequencing of functional clones from each library also identified a greater dispersion of fragmentation sites within TnAK. Nondisruptive fission sites were observed within the AMP binding and core domains of both AK homologs. However, only TnAK contained sites within the lid domain, which undergoes dynamic fluctuations that are critical for catalysis. These findings implicate the flexible lid domain as having an increased sensitivity to fission events at physiological temperatures. In addition, they provide evidence that comparisons of nondisruptive fission sites in homologous proteins could be useful for finding dynamic regions whose conformational fluctuations are important for function, and they show that the discovery of protein fragments that cooperatively function in mesophiles can be aided by the use of thermophilic enzymes as starting points for protein design.

Selection for thermostability can lead to the emergence of mutational robustness in an RNA virus

Mutational robustness has important evolutionary implications, yet the mechanisms leading to its emergence remain poorly understood. One possibility is selection acting on a correlated trait, as for instance thermostability (plastogenetic congruence). Here, we examine the correlation between mutational robustness and thermostability in experimental populations of the RNA bacteriophage Qβ. Thermostable viruses evolved after only six serial passages in the presence of heat shocks, and genome sequencing suggested that thermostability can be conferred by several alternative mutations. To test whether thermostable viruses have increased mutational robustness, we performed additional passages in the presence of nitrous acid. Whereas in control lines this treatment produced the expected reduction in growth rate caused by the accumulation of deleterious mutations, thermostable viruses showed no such reduction, indicating that they are more resistant to mutagenesis. Our results suggest that selection for thermostability can lead to the emergence of mutational robustness driven by plastogenetic congruence. As temperature is a widespread selective pressure in nature, the mechanism described here may be relevant to the evolution of mutational robustness.

Consensus protein design without phylogenetic bias

Consensus design is an appealing strategy for the stabilization of proteins. It exploits amino acid conservation in sets of homologous proteins to identify likely beneficial mutations. Nevertheless, its success depends on the phylogenetic diversity of the sequence set available. Here, we show that randomization of a single protein represents a reliable alternative source of sequence diversity that is essentially free of phylogenetic bias. A small number of functional protein sequences selected from binary-patterned libraries suffice as input for the consensus design of active enzymes that are easier to produce and substantially more stable than individual members of the starting data set. Although catalytic activity correlates less consistently with sequence conservation in these extensively randomized proteins, less extreme mutagenesis strategies might be adopted in practice to augment stability while maintaining function.

Mathematics, thermodynamics, and modeling to address ten common misconceptions about protein structure, folding, and stability

To fully understand the roles proteins play in cellular processes, students need to grasp complex ideas about protein structure, folding, and stability. Our current understanding of these topics is based on mathematical models and experimental data. However, protein structure, folding, and stability are often introduced as descriptive, qualitative phenomena in undergraduate classes. In the process of learning about these topics, students often form incorrect ideas. For example, by learning about protein folding in the context of protein synthesis, students may come to an incorrect conclusion that once synthesized on the ribosome, a protein spends its entire cellular life time in its fully folded native confirmation. This is clearly not true; proteins are dynamic structures that undergo both local fluctuations and global unfolding events. To prevent and address such misconceptions, basic concepts of protein science can be introduced in the context of simple mathematical models and hands-on explorations of publicly available data sets. Ten common misconceptions about proteins are presented, along with suggestions for using equations, models, sequence, structure, and thermodynamic data to help students gain a deeper understanding of basic concepts relating to protein structure, folding, and stability.

Defining an essence of structure determining residue contacts in proteins

The network of native non-covalent residue contacts determines the three-dimensional structure of a protein. However, not all contacts are of equal structural significance, and little knowledge exists about a minimal, yet sufficient, subset required to define the global features of a protein. Characterisation of this “structural essence” has remained elusive so far: no algorithmic strategy has been devised to-date that could outperform a random selection in terms of 3D reconstruction accuracy (measured as the Ca RMSD). It is not only of theoretical interest (i.e., for design of advanced statistical potentials) to identify the number and nature of essential native contacts—such a subset of spatial constraints is very useful in a number of novel experimental methods (like EPR) which rely heavily on constraint-based protein modelling. To derive accurate three-dimensional models from distance constraints, we implemented a reconstruction pipeline using distance geometry. We selected a test-set of 12 protein structures from the four major SCOP fold classes and performed our reconstruction analysis. As a reference set, series of random subsets (ranging from 10% to 90% of native contacts) are generated for each protein, and the reconstruction accuracy is computed for each subset. We have developed a rational strategy, termed “cone-peeling” that combines sequence features and network descriptors to select minimal subsets that outperform the reference sets. We present, for the first time, a rational strategy to derive a structural essence of residue contacts and provide an estimate of the size of this minimal subset. Our algorithm computes sparse subsets capable of determining the tertiary structure at approximately 4.8 Å Ca RMSD with as little as 8% of the native contacts (Ca-Ca and Cb-Cb). At the same time, a randomly chosen subset of native contacts needs about twice as many contacts to reach the same level of accuracy. This “structural essence” opens new avenues in the fields of structure prediction, empirical potentials and docking.

A protein structure can be visualized as a network of non-covalent contacts existing between amino acids. But not all such contacts are important structural determinants of a protein. We have attempted to identify a subset of amino acid contacts that are essential for reconstructing protein structures. Initially, we followed random sampling of contacts and tested their efficacy to successfully represent the three-dimensional structure. Further, we also developed an algorithm that selects a subset of amino acid contacts from proteins based on the sequence and network properties. The subsets picked by our algorithm represent protein three-dimensional structure better than random subsets, thereby offering direct evidence for the existence of a structural essence in protein structures. The identification of such structure-defining subsets finds application in experimental and computational protein structure determination.

In the light of directed evolution: pathways of adaptive protein evolution

Directed evolution is a widely-used engineering strategy for improving the stabilities or biochemical functions of proteins by repeated rounds of mutation and selection. These experiments offer empirical lessons about how proteins evolve in the face of clearly-defined laboratory selection pressures. Directed evolution has revealed that single amino acid mutations can enhance properties such as catalytic activity or stability and that adaptation can often occur through pathways consisting of sequential beneficial mutations. When there are no single mutations that improve a particular protein property experiments always find a wealth of mutations that are neutral with respect to the laboratory-defined measure of fitness. These neutral mutations can open new adaptive pathways by at least 2 different mechanisms. Functionally-neutral mutations can enhance a protein's stability, thereby increasing its tolerance for subsequent functionally beneficial but destabilizing mutations. They can also lead to changes in "promiscuous" functions that are not currently under selective pressure, but can subsequently become the starting points for the adaptive evolution of new functions. These lessons about the coupling between adaptive and neutral protein evolution in the laboratory offer insight into the evolution of proteins in nature.

Inferring stabilizing mutations from protein phylogenies: application to influenza hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution.

Mutating a protein frequently causes a change in its stability. As scientists, we often care about these changes because we would like to engineer a protein's stability or understand how its stability is impacted by a naturally occurring mutation. Evolution also cares about mutational stability changes, because a basic evolutionary requirement is that proteins remain sufficiently stable to perform their biological functions. Our work is based on the idea that it should be possible to use the fact that evolution selects for stability to infer from related proteins the effects of specific mutations. We show that we can indeed use protein evolutionary histories to computationally predict previously measured mutational stability changes more accurately than methods based on either of the two main existing strategies. We then test whether we can predict mutations that increase the stability of hemagglutinin, an influenza protein whose rapid evolution is partly responsible for the ability of this virus to cause yearly epidemics. We experimentally create viruses carrying predicted stabilizing mutations and find that several do in fact improve the virus's ability to grow at higher temperatures. Our computational approach may therefore be of use in understanding the evolution of this medically important virus.

Relative tolerance of an enzymatic molten globule and its thermostable counterpart to point mutation

Enzyme structures reflect the complex interplay between the free energy of unfolding (DeltaG) and catalytic efficiency. Consequently, the effects of point mutations on structure, stability, and function are difficult to predict. It has been proposed that the mutational robustness of homologous enzymes correlates with a higher initial DeltaG. To examine this issue, we compared the tolerance of a natural thermostable chorismate mutase and an engineered molten globular variant to targeted mutation. These mutases possess similar sequence, structure, and catalytic efficiency but dramatically different DeltaG values. We find that analogous point mutations can have widely divergent effects on catalytic activity in these scaffolds. In a set of five rationally designed single-amino acid changes, the thermostable scaffold suffers activity losses ranging from 50-fold smaller, for an aspartate-to-glycine substitution at the active site, to 2-fold greater, for a phenylalanine-to-tryptophan substitution in the hydrophobic core, versus that of the molten globular scaffold. However, biophysical characterization indicates that the variations in catalytic efficiency are not caused by losses of either secondary structural integrity or thermodynamic stability. Rather, the activity differences between variant pairs are very much context-dependent and likely stem from subtle changes in the fine structure of the active site. Thus, in many cases, it may be more productive to focus on changes in local conformation than on global stability when attempting to understand and predict how enzymes respond to point mutations.

Do viral proteins possess unique biophysical features?

Natural selection shapes the sequence, structure and biophysical properties of proteins to fit their environment. We hypothesize that highly thermostable proteins and viral proteins represent two opposing adaptation strategies. Thermostable proteins are highly compact and possess well-packed hydrophobic cores and intensely charged surfaces. By contrast, viral proteins, and RNA viral proteins in particular, display a high occurrence of disordered segments and loosely packed cores. These features might endow viral proteins with increased structural flexibility and effective ways to interact with the components of the host. They could also be related to high adaptability levels and mutation rates observed in viruses, thus, representing a unique strategy for buffering the deleterious effects of mutations, such that those that have little (interactions), have little to lose.

Relationship between energy distribution and fold stability: Insights from molecular dynamics simulations of native and mutant proteins

Most proteins must fold to a well-defined structure with a minimal stability to perform their function. Here we use a simple, molecular dynamics-based, energy decomposition approach to map the principal energetic interactions in a set of proteins representative of different folds. This work involves the all-atom simulation and analysis of the native structures and mutants of five different proteins representative of an all-alpha (yACPB, Protein A), all-beta (SH3), and a mixed alpha/beta fold (Proteins G and L). Given a certain structure, a native sequence and a set of mutants, we show that our model discriminates the ability of a mutation to yield a more or less stable protein, in agreement with experimental data, catching the principal energetic determinants of protein stabilization. Our approach identifies the interaction determinants responsible to define a fold and shows that mutations can either modulate the strength of pair-wise coupling between residues important for folding, or modify the profile of the principal interactions. Furthermore, we address the question of how to evaluate the fitness of a sequence to a given structure by comparing the information contained in the energy map, which recapitulates the chemistry of the sequence, to that contained in the contact map, which recapitulates the fold topology. The results show that the better fit between the energetic properties of the sequence and the fold topology corresponds to a higher stabilization of the protein. We discuss the relevance of these observations to the analysis of protein designability and to the rational evolution of new sequences.

How protein stability and new functions trade off

Numerous studies have noted that the evolution of new enzymatic specificities is accompanied by loss of the protein's thermodynamic stability (ΔΔG), thus suggesting a tradeoff between the acquisition of new enzymatic functions and stability. However, since most mutations are destabilizing (ΔΔG>0), one should ask how destabilizing mutations that confer new or altered enzymatic functions relative to all other mutations are. We applied ΔΔG computations by FoldX to analyze the effects of 548 mutations that arose from the directed evolution of 22 different enzymes. The stability effects, location, and type of function-altering mutations were compared to ΔΔG changes arising from all possible point mutations in the same enzymes. We found that mutations that modulate enzymatic functions are mostly destabilizing (average ΔΔG = +0.9 kcal/mol), and are almost as destabilizing as the “average” mutation in these enzymes (+1.3 kcal/mol). Although their stability effects are not as dramatic as in key catalytic residues, mutations that modify the substrate binding pockets, and thus mediate new enzymatic specificities, place a larger stability burden than surface mutations that underline neutral, non-adaptive evolutionary changes. How are the destabilizing effects of functional mutations balanced to enable adaptation? Our analysis also indicated that many mutations that appear in directed evolution variants with no obvious role in the new function exert stabilizing effects that may compensate for the destabilizing effects of the crucial function-altering mutations. Thus, the evolution of new enzymatic activities, both in nature and in the laboratory, is dependent on the compensatory, stabilizing effect of apparently “silent” mutations in regions of the protein that are irrelevant to its function.

To perform its function, a protein must fold into a complex, three-dimensional structure that is maintained by a network of interactions between its amino acid residues. Evolution of a new protein function will be driven by mutation of amino acids in key positions (new-function mutations). Such mutation can also hamper interactions that ensure the stability of a protein's fold—sometimes to a degree that renders the protein non-functional. Indeed, previous studies have noted that the evolution of new enzymatic functions is accompanied by significant losses in protein stability, suggesting a “tradeoff” between acquisition of new enzymatic functions and stability. But since most mutations are destabilizing, we sought to compare new-function mutations with other types of mutations. We performed a comprehensive analysis of the type, location, and stability effects of mutations that have conferred new enzymatic functions in laboratory evolution experiments. We found that stability changes (ΔΔG) of new-function mutations are similar to those of all other mutations, but are weaker than those of mutations that characterize neutral evolutionary changes (mutations that accumulate with no change of structure and function). Our analysis also revealed the important role of neutral (i.e., “non-functional”) mutations in compensating for the destabilizing effects of the “new-function” mutations.

Genetic constraints on protein evolution

Evolution requires the generation and optimization of new traits ("adaptation") and involves the selection of mutations that improve cellular function. These mutations were assumed to arise by selection of neutral mutations present at all times in the population. Here we review recent evidence that indicates that deleterious mutations are more frequent in the population than previously recognized and that these mutations play a significant role in protein evolution through continuous positive selection. Positively selected mutations include adaptive mutations, i.e. mutations that directly affect enzymatic function, and compensatory mutations, which suppress the pleiotropic effects of adaptive mutations. Compensatory mutations are by far the most frequent of the two and would allow potentially adaptive but deleterious mutations to persist long enough in the population to be positively selected during episodes of adaptation. Compensatory mutations are, by definition, context-dependent and thus constrain the paths available for evolution. This provides a mechanistic basis for the examples of highly constrained evolutionary landscapes and parallel evolution reported in natural and experimental populations. The present review article describes these recent advances in the field of protein evolution and discusses their implications for understanding the genetic basis of disease and for protein engineering in vitro.

Designability and disease

Structural designability is the number of ways it is possible to encode for structure. A protein's designability has been equated with the size of sequence space encoding for the protein's structure, a measure that reflects the structure's robustness to mutation. Current evidence suggests that designability is fundamental to our understanding of the evolvability and distribution of structures in nature and is a significant factor associated with human disease. Here, we describe definitions and principles underlying the concept of designability and discuss its relation to disease.

Evolution favors protein mutational robustness in sufficiently large populations

Background

An important question is whether evolution favors properties such as mutational robustness or evolvability that do not directly benefit any individual but can influence the course of future evolution. Functionally similar proteins can differ substantially in their robustness to mutations and capacity to evolve new functions, but it has remained unclear whether any of these differences might be due to evolutionary selection for these properties.

Results

Here, we use laboratory experiments to demonstrate that evolution favors protein mutational robustness if the evolving population is sufficiently large. We neutrally evolve cytochrome P450 proteins under identical selection pressures and mutation rates in populations of different sizes, and show that proteins from the larger and thus more polymorphic population tend towards higher mutational robustness. Proteins from the larger population also evolve greater stability, a biophysical property that is known to enhance both mutational robustness and evolvability. The excess mutational robustness and stability is well described by mathematical theory, and can be quantitatively related to the way that the proteins occupy their neutral network.

Conclusion

Our work is the first experimental demonstration of the general tendency of evolution to favor mutational robustness and protein stability in highly polymorphic populations. We suggest that this phenomenon could contribute to the mutational robustness and evolvability of viruses and bacteria that exist in large populations.

Neutral genetic drift can alter promiscuous protein functions, potentially aiding functional evolution

Background

Many of the mutations accumulated by naturally evolving proteins are neutral in the sense that they do not significantly alter a protein's ability to perform its primary biological function. However, new protein functions evolve when selection begins to favor other, "promiscuous" functions that are incidental to a protein's original biological role. If mutations that are neutral with respect to a protein's primary biological function cause substantial changes in promiscuous functions, these mutations could enable future functional evolution.

Results

Here we investigate this possibility experimentally by examining how cytochrome P450 enzymes that have evolved neutrally with respect to activity on a single substrate have changed in their abilities to catalyze reactions on five other substrates. We find that the enzymes have sometimes changed as much as four-fold in the promiscuous activities. The changes in promiscuous activities tend to increase with the number of mutations, and can be largely rationalized in terms of the chemical structures of the substrates. The activities on chemically similar substrates tend to change in a coordinated fashion, potentially providing a route for systematically predicting the change in one activity based on the measurement of several others.

Conclusion

Our work suggests that initially neutral genetic drift can lead to substantial changes in protein functions that are not currently under selection, in effect poising the proteins to more readily undergo functional evolution should selection favor new functions in the future.

Reviewers

This article was reviewed by Martijn Huynen, Fyodor Kondrashov, and Dan Tawfik (nominated by Christoph Adami).

The stability effects of protein mutations appear to be universally distributed

How the thermodynamic stability effects of protein mutations (DeltaDeltaG) are distributed is a fundamental property related to the architecture, tolerance to mutations (mutational robustness), and evolutionary history of proteins. The stability effects of mutations also dictate the rate and dynamics of protein evolution, with deleterious mutations being the main inhibitory factor. Using the FoldX algorithm that attempts to computationally predict DeltaDeltaG effects of mutations, we deduced the overall distributions of stability effects for all possible mutations in 21 different globular, single domain proteins. We found that these distributions are strikingly similar despite a range of sizes and folds, and largely follow a bi-Gaussian function: The surface residues exhibit a narrow distribution with a mildly destabilizing mean DeltaDeltaG ( approximately 0.6 kcal/mol), whereas the core residues exhibit a wider distribution with a stronger destabilizing mean ( approximately 1.4 kcal/mol). Since smaller proteins have a higher fraction of surface residues, the relative weight of these single distributions correlates with size. We also found that proteins evolved in the laboratory follow an essentially identical distribution, whereas de novo designed folds show markedly less destabilizing distributions (i.e. they seem more robust to the effects of mutations). This bi-Gaussian model provides an analytical description of the predicted distributions of mutational stability effects. It comprises a novel tool for analyzing proteins and protein models, for simulating the effect of mutations under evolutionary processes, and a quantitative description of mutational robustness.