Natural selection for kinetic stability is a likely origin of correlations between mutational effects on protein energetics and frequencies of amino acid occurrences in sequence alignments

MSH-DTI: multi-graph convolution with self-supervised embedding and heterogeneous aggregation for drug-target interaction prediction

BACKGROUND

The rise of network pharmacology has led to the widespread use of network-based computational methods in predicting drug target interaction (DTI). However, existing DTI prediction models typically rely on a limited amount of data to extract drug and target features, potentially affecting the comprehensiveness and robustness of features. In addition, although multiple networks are used for DTI prediction, the integration of heterogeneous information often involves simplistic aggregation and attention mechanisms, which may impose certain limitations.

RESULTS

MSH-DTI, a deep learning model for predicting drug-target interactions, is proposed in this paper. The model uses self-supervised learning methods to obtain drug and target structure features. A Heterogeneous Interaction-enhanced Feature Fusion Module is designed for multi-graph construction, and the graph convolutional networks are used to extract node features. With the help of an attention mechanism, the model focuses on the important parts of different features for prediction. Experimental results show that the AUROC and AUPR of MSH-DTI are 0.9620 and 0.9605 respectively, outperforming other models on the DTINet dataset.

CONCLUSION

The proposed MSH-DTI is a helpful tool to discover drug-target interactions, which is also validated through case studies in predicting new DTIs.

Deciphering Structural Traits for Thermal and Kinetic Stability across Protein Family Evolution through Ancestral Sequence Reconstruction

Natural proteins are frequently marginally stable, and an increase in environmental temperature can easily lead to unfolding. As a result, protein engineering to improve protein stability is an area of intensive research. Nonetheless, since there is usually a high degree of structural homology between proteins from thermophilic organisms and their mesophilic counterparts, the identification of structural determinants for thermoadaptation is challenging. Moreover, in many cases, it has become clear that the success of stabilization strategies is often dependent on the evolutionary history of a protein family. In the last few years, the use of ancestral sequence reconstruction (ASR) as a tool for elucidation of the evolutionary history of functional traits of a protein family has gained strength. Here, we used ASR to trace the evolutionary pathways between mesophilic and thermophilic kinases that participate in the biosynthetic pathway of vitamin B1 in bacteria. By combining biophysics approaches, X-ray crystallography, and molecular dynamics simulations, we found that the thermal stability of these enzymes correlates with their kinetic stability, where the highest thermal/kinetic stability is given by an increase in small hydrophobic amino acids that allow a higher number of interatomic hydrophobic contacts, making this type of interaction the main support for stability in this protein architecture. The results highlight the potential benefits of using ASR to explore the evolutionary history of protein sequence and structure to identify traits responsible for the kinetic and thermal stability of any protein architecture.

Engineering the Thermostability of a d-Carbamoylase Based on Ancestral Sequence Reconstruction for the Efficient Synthesis of d-Tryptophan

Employing ancestral sequence reconstruction and consensus sequence analysis, the thermostability of a novel d-carbamoylase derived from Nitratireductor indicus (NiHyuC) was engineered through greedy-oriented iterative combinatorial mutagenesis. A mutant S202P/E208D/R277L (M4Th3) was obtained with significantly elevated thermostability. M4Th3 has a half-life of 36.5 h at 40 °C, about 28.5 times of 1.3 h of its parent M4. For the reaction at 40 °C, M4Th3 can catalyze 10 mM N-carbamoyl-d-tryptophan to produce d-tryptophan with a conversion ratio of 96.4% after 12 h, which is significantly higher than 64.1% of M4. MD simulation reveals that new hydrogen bonds emerging from E208D on the surface can increase the hydrophobicity of the protein, leading to improved stability. More importantly, R277L could contribute to enhanced interface stability of homodimeric M4. This study provides a thermostable d-carbamoylase for the "hydantoinase process", which has potential in the industrial synthesis of optically pure natural and non-natural amino acids.

Circuit topology predicts pathogenicity of missense mutations

The contact topology of a protein determines important aspects of the folding process. The topological measure of contact order has been shown to be predictive of the rate of folding. Circuit topology is emerging as another fundamental descriptor of biomolecular structure, with predicted effects on the folding rate. We analyze the residue‐based circuit topological environments of 21 K mutations labeled as pathogenic or benign. Multiple statistical lines of reasoning support the conclusion that the number of contacts in two specific circuit topological arrangements, namely inverse parallel and cross relations, with contacts involving the mutated residue have discriminatory value in determining the pathogenicity of human variants. We investigate how results vary with residue type and according to whether the gene is essential. We further explore the relationship to a number of structural features and find that circuit topology provides nonredundant information on protein structures and pathogenicity of mutations. Results may have implications for the polymer physics of protein folding and suggest that “local” topological information, including residue‐based circuit topology and residue contact order, could be useful in improving state‐of‐the‐art machine learning algorithms for pathogenicity prediction.

Combining Ancestral Reconstruction with Folding-Landscape Simulations to Engineer Heterologous Protein Expression

Obligate symbionts typically exhibit high evolutionary rates. Consequently, their proteins may differ considerably from their modern and ancestral homologs in terms of both sequence and properties, thus providing excellent models to study protein evolution. Also, obligate symbionts are challenging to culture in the lab and proteins from uncultured organisms must be produced in heterologous hosts using recombinant DNA technology. Obligate symbionts thus replicate a fundamental scenario of metagenomics studies aimed at the functional characterization and biotechnological exploitation of proteins from the bacteria in soil. Here, we use the thioredoxin from Candidatus Photodesmus katoptron, an uncultured symbiont of flashlight fish, to explore evolutionary and engineering aspects of protein folding in heterologous hosts. The symbiont protein is a standard thioredoxin in terms of 3D-structure, stability and redox activity. However, its folding outside the original host is severely impaired, as shown by a very slow refolding in vitro and an inefficient expression in E. coli that leads mostly to insoluble protein. By contrast, resurrected Precambrian thioredoxins express efficiently in E. coli, plausibly reflecting an ancient adaptation to unassisted folding. We have used a statistical-mechanical model of the folding landscape to guide back-to-ancestor engineering of the symbiont protein. Remarkably, we find that the efficiency of heterologous expression correlates with the in vitro (i.e., unassisted) folding rate and that the ancestral expression efficiency can be achieved with only 1-2 back-to-ancestor replacements. These results demonstrate a minimal-perturbation, sequence-engineering approach to rescue inefficient heterologous expression which may potentially be useful in metagenomics efforts targeting recent adaptations.

Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders

Three-dimensional structures of proteins can provide important clues into the efficacy of personalized treatment. We perform a structural analysis of variants within three inherited lysosomal storage disorders, comparing variants responsive to pharmacological chaperone treatment to those unresponsive to such treatment. We find that predicted ΔΔG of mutation is higher on average for variants unresponsive to treatment, in the case of datasets for both Fabry disease and Pompe disease, in line with previous findings. Using both a single decision tree and an advanced machine learning approach based on the larger Fabry dataset, we correctly predict responsiveness of three Gaucher disease variants, and we provide predictions for untested variants. Many variants are predicted to be responsive to treatment, suggesting that drug-based treatments may be effective for a number of variants in Gaucher disease. In our analysis, we observe dependence on a topological feature reporting on contact arrangements which is likely connected to the order of folding of protein residues, and we provide a potential justification for this observation based on steady-state cellular kinetics.

Pharmacological chaperones are small molecule drugs that bind to proteins to help stabilize the folded state. One set of diseases for which this treatment has been effective is the lysosomal storage disorders, which are caused by defective lysosomal enzymes. However, not all genotypes are equally responsive to treatment. For instance, missense mutants that are particularly destabilized relative to WT are less likely to respond. The availability of datasets containing responsiveness data for large numbers of mutants, along with crystal structures of the protein involved in each disease, make machine learning methods incorporating sequence-based and structural data feasible. We hypothesize that data from two diseases, Fabry and Pompe disease, may be useful for predicting responsiveness of variants in the related Gaucher disease. Results suggest that many rare variants in Gaucher disease could be amenable to existing drugs. Results also suggest that drug responsiveness depends on protein topology in such a way that mutations in early-to-fold residues are more likely to be non-responsive to pharmacological chaperone treatment, which is consistent with a simple kinetic model of stability rescue. This study provides an example of how machine learning can be used to inform further studies towards personalized treatment in medicine.

ADDRESS: A Database of Disease-associated Human Variants Incorporating Protein Structure and Folding Stabilities

Numerous human diseases are caused by mutations in genomic sequences. Since amino acid changes affect protein function through mechanisms often predictable from protein structure, the integration of structural and sequence data enables us to estimate with greater accuracy whether and how a given mutation will lead to disease. Publicly available annotated databases enable hypothesis assessment and benchmarking of prediction tools. However, the results are often presented as summary statistics or black box predictors, without providing full descriptive information. We developed a new semi-manually curated human variant database presenting information on the protein contact-map, sequence-to-structure mapping, amino acid identity change, and stability prediction for the popular UniProt database. We found that the profiles of pathogenic and benign missense polymorphisms can be effectively deduced using decision trees and comparative analyses based on the presented dataset. The database is made publicly available through https://zhanglab.ccmb.med.umich.edu/ADDRESS.

Non-conservation of folding rates in the thioredoxin family reveals degradation of ancestral unassisted-folding

Evolution involves not only adaptation, but also the degradation of superfluous features. Many examples of degradation at the morphological level are known (vestigial organs, for instance). However, the impact of degradation on molecular evolution has been rarely addressed. Thioredoxins serve as general oxidoreductases in all cells. Here, we report extensive mutational analyses on the folding of modern and resurrected ancestral bacterial thioredoxins. Contrary to claims from recent literature, in vitro folding rates in the thioredoxin family are not evolutionarily conserved, but span at least a ∼100-fold range. Furthermore, modern thioredoxin folding is often substantially slower than ancestral thioredoxin folding. Unassisted folding, as probed in vitro, thus emerges as an ancestral vestigial feature that underwent degradation, plausibly upon the evolutionary emergence of efficient cellular folding assistance. More generally, our results provide evidence that degradation of ancestral features shapes, not only morphological evolution, but also the evolution of individual proteins.

The burst-phase folding intermediate of ribonuclease H changes conformation over evolutionary history

The amino acid sequence encodes the energy landscape of a protein. Therefore, we expect evolutionary mutations to change features of the protein energy landscape, including the conformations adopted by a polypeptide as it folds to its native state. Ribonucleases H (RNase H) from Escherichia coli and Thermus thermophilus both fold via a partially folded intermediate in which the core region of the protein (helices A-D and strands 4-5) is structured. Strand 1, however, uniquely contributes to the T. thermophilus RNase H folding intermediate (Icore+1 ), but not the E. coli RNase H intermediate (Icore ) (Rosen & Marqusee, PLoS One 2015). We explore the origin of this difference by characterizing the folding intermediate of seven ancestral RNases H spanning the evolutionary history of these two homologs. Using fragment models with or without strand 1 and FRET probes to characterize the folding intermediate of each ancestor, we find a distinct evolutionary trend across the family-the involvement of strand 1 in the folding intermediate is an ancestral feature that is maintained in the thermophilic lineage and is gradually lost in the mesophilic lineage. Evolutionary sequence changes indeed modulate the conformations present on the folding landscape and altered the folding trajectory of RNase H.

Structure and energy based quantitative missense variant effect analysis provides insights into drug resistance mechanisms of anaplastic lymphoma kinase mutations

Anaplastic lymphoma kinase (ALK) is considered as a validated molecular target in multiple malignancies, such as non-small cell lung cancer (NSCLC). However, the effectiveness of molecularly targeted therapies using ALK inhibitors is almost universally limited by drug resistance. Drug resistance to molecularly targeted therapies has now become a major obstacle to effective cancer treatment and personalized medicine. It is of particular importance to provide an improved understanding on the mechanisms of resistance of ALK inhibitors, thus rational new therapeutic strategies can be developed to combat resistance. We used state-of-the-art computational approaches to systematically explore the mutational effects of ALK mutations on drug resistance properties. We found the activation of ALK was increased by substitution with destabilizing mutations, creating the capacity to confer drug resistance to inhibitors. In addition, results implied that evolutionary constraints might affect the drug resistance properties. Moreover, an extensive profile of drugs against ALK mutations was constructed to give better understanding of the mechanism of drug resistance based on structural transitions and energetic variation. Our work hopes to provide an up-to-date mechanistic framework for understanding the mechanisms of drug resistance induced by ALK mutations, thus tailor treatment decisions after the emergence of resistance in ALK-dependent diseases.

Conformational dynamics and enzyme evolution

Enzymes are dynamic entities, and their dynamic properties are clearly linked to their biological function. It follows that dynamics ought to play an essential role in enzyme evolution. Indeed, a link between conformational diversity and the emergence of new enzyme functionalities has been recognized for many years. However, it is only recently that state-of-the-art computational and experimental approaches are revealing the crucial molecular details of this link. Specifically, evolutionary trajectories leading to functional optimization for a given host environment or to the emergence of a new function typically involve enriching catalytically competent conformations and/or the freezing out of non-competent conformations of an enzyme. In some cases, these evolutionary changes are achieved through distant mutations that shift the protein ensemble towards productive conformations. Multifunctional intermediates in evolutionary trajectories are probably multi-conformational, i.e. able to switch between different overall conformations, each competent for a given function. Conformational diversity can assist the emergence of a completely new active site through a single mutation by facilitating transition-state binding. We propose that this mechanism may have played a role in the emergence of enzymes at the primordial, progenote stage, where it was plausibly promoted by high environmental temperatures and the possibility of additional phenotypic mutations.

Evidence for the principle of minimal frustration in the evolution of protein folding landscapes

Theoretical and experimental studies have firmly established that protein folding can be described by a funneled energy landscape. This funneled energy landscape is the result of foldable protein sequences evolving following the principle of minimal frustration, which allows proteins to rapidly fold to their native biologically functional conformations. For a protein family with a given functional fold, the principle of minimal frustration suggests that, independent of sequence, all proteins within this family should fold with similar rates. However, depending on the optimal living temperature of the organism, proteins also need to modulate their thermodynamic stability. Consequently, the difference in thermodynamic stability should be primarily caused by differences in the unfolding rates. To test this hypothesis experimentally, we performed comprehensive thermodynamic and kinetic analyses of 15 different proteins from the thioredoxin family. Eight of these thioredoxins were extant proteins from psychrophilic, mesophilic, or thermophilic organisms. The other seven protein sequences were obtained using ancestral sequence reconstruction and can be dated back over 4 billion years. We found that all studied proteins fold with very similar rates but unfold with rates that differ up to three orders of magnitude. The unfolding rates correlate well with the thermodynamic stability of the proteins. Moreover, proteins that unfold slower are more resistant to proteolysis. These results provide direct experimental support to the principle of minimal frustration hypothesis.

Evolutionary trend toward kinetic stability in the folding trajectory of RNases H

Proper folding of proteins is critical to producing the biological machinery essential for cellular function. The rates and energetics of a protein's folding process, which is described by its energy landscape, are encoded in the amino acid sequence. Over the course of evolution, this landscape must be maintained such that the protein folds and remains folded over a biologically relevant time scale. How exactly a protein's energy landscape is maintained or altered throughout evolution is unclear. To study how a protein's energy landscape changed over time, we characterized the folding trajectories of ancestral proteins of the ribonuclease H (RNase H) family using ancestral sequence reconstruction to access the evolutionary history between RNases H from mesophilic and thermophilic bacteria. We found that despite large sequence divergence, the overall folding pathway is conserved over billions of years of evolution. There are robust trends in the rates of protein folding and unfolding; both modern RNases H evolved to be more kinetically stable than their most recent common ancestor. Finally, our study demonstrates how a partially folded intermediate provides a readily adaptable folding landscape by allowing the independent tuning of kinetics and thermodynamics.

On the Potential Origins of the High Stability of Reconstructed Ancestral Proteins

Ancestral reconstruction provides instrumental insights regarding the biochemical and biophysical characteristics of past proteins. A striking observation relates to the remarkably high thermostability of reconstructed ancestors. The latter has been linked to high environmental temperatures in the Precambrian era, the era relating to most reconstructed proteins. We found that inferred ancestors of the serum paraoxonase (PON) enzyme family, including the mammalian ancestor, exhibit dramatically increased thermostabilities compared with the extant, human enzyme (up to 30 °C higher melting temperature). However, the environmental temperature at the time of emergence of mammals is presumed to be similar to the present one. Additionally, the mammalian PON ancestor has superior folding properties (kinetic stability)-unlike the extant mammalian PONs, it expresses in E. coli in a soluble and functional form, and at a high yield. We discuss two potential origins of this unexpectedly high stability. First, ancestral stability may be overestimated by a "consensus effect," whereby replacing amino acids that are rare in contemporary sequences with the amino acid most common in the family increases protein stability. Comparison to other reconstructed ancestors indicates that the consensus effect may bias some but not all reconstructions. Second, we note that high stability may relate to factors other than high environmental temperature such as oxidative stress or high radiation levels. Foremost, intrinsic factors such as high rates of genetic mutations and/or of transcriptional and translational errors, and less efficient protein quality control systems, may underlie the high kinetic and thermodynamic stability of past proteins.

Selection for Protein Kinetic Stability Connects Denaturation Temperatures to Organismal Temperatures and Provides Clues to Archaean Life

The relationship between the denaturation temperatures of proteins (T_m values) and the living temperatures of their host organisms (environmental temperatures: T_ENV values) is poorly understood. Since different proteins in the same organism may show widely different T_m’s, no simple universal relationship between T_m and T_ENV should hold, other than T_m≥T_ENV. Yet, when analyzing a set of homologous proteins from different hosts, T_m’s are oftentimes found to correlate with T_ENV’s but this correlation is shifted upward on the T_m axis. Supporting this trend, we recently reported T_m’s for resurrected Precambrian thioredoxins that mirror a proposed environmental cooling over long geological time, while remaining a shocking ~50°C above the proposed ancestral ocean temperatures. Here, we show that natural selection for protein kinetic stability (denaturation rate) can produce a T_m↔T_ENV correlation with a large upward shift in T_m. A model for protein stability evolution suggests a link between the T_m shift and the in vivo lifetime of a protein and, more specifically, allows us to estimate ancestral environmental temperatures from experimental denaturation rates for resurrected Precambrian thioredoxins. The T_ENV values thus obtained match the proposed ancestral ocean cooling, support comparatively high Archaean temperatures, and are consistent with a recent proposal for the environmental temperature (above 75°C) that hosted the last universal common ancestor. More generally, this work provides a framework for understanding how features of protein stability reflect the environmental temperatures of the host organisms.

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.

Effect of mutations on the thermostability of Aspergillus aculeatus β-1,4-galactanase

New variants of β-1,4-galactanase from the mesophilic organism Aspergillus aculeatus were designed using the structure of β-1,4-galactanase from the thermophile organism Myceliophthora thermophila as a template. Some of the variants were generated using PROPKA 3.0, a validated pKa prediction tool, to test its usefulness as an enzyme design tool. The PROPKA designed variants were D182N and S185D/Q188T, G104D/A156R. Variants Y295F and G306A were designed by a consensus approach, as a complementary and validated design method. D58N was a stabilizing mutation predicted by both methods. The predictions were experimentally validated by measurements of the melting temperature (Tm ) by differential scanning calorimetry. We found that the Tm is elevated by 1.1 °C for G306A, slightly increased (in the range of 0.34 to 0.65 °C) for D182N, D58N, Y295F and unchanged or decreased for S185D/Q188T and G104D/A156R. The Tm changes were in the range predicted by PROPKA. Given the experimental errors, only the D58N and G306A show significant increase in thermodynamic stability. Given the practical importance of kinetic stability, the kinetics of the irreversible enzyme inactivation process were also investigated for the wild-type and three variants and found to be biphasic. The half-lives of thermal inactivation were approximately doubled in G306A, unchanged for D182N and, disappointingly, a lot lower for D58N. In conclusion, this study tests a new method for estimating Tm changes for mutants, adds to the available data on the effect of substitutions on protein thermostability and identifies an interesting thermostabilizing mutation, which may be beneficial also in other galactanases.

Irreversible denaturation of maltodextrin glucosidase studied by differential scanning calorimetry, circular dichroism, and turbidity measurements

Thermal denaturation of Escherichia coli maltodextrin glucosidase was studied by differential scanning calorimetry, circular dichroism (230 nm), and UV-absorption measurements (340 nm), which were respectively used to monitor heat absorption, conformational unfolding, and the production of solution turbidity. The denaturation was irreversible, and the thermal transition recorded at scan rates of 0.5–1.5 K/min was significantly scan-rate dependent, indicating that the thermal denaturation was kinetically controlled. The absence of a protein-concentration effect on the thermal transition indicated that the denaturation was rate-limited by a mono-molecular process. From the analysis of the calorimetric thermograms, a one-step irreversible model well represented the thermal denaturation of the protein. The calorimetrically observed thermal transitions showed excellent coincidence with the turbidity transitions monitored by UV-absorption as well as with the unfolding transitions monitored by circular dichroism. The thermal denaturation of the protein was thus rate-limited by conformational unfolding, which was followed by a rapid irreversible formation of aggregates that produced the solution turbidity. It is thus important to note that the absence of the protein-concentration effect on the irreversible thermal denaturation does not necessarily means the absence of protein aggregation itself. The turbidity measurements together with differential scanning calorimetry in the irreversible thermal denaturation of the protein provided a very effective approach for understanding the mechanisms of the irreversible denaturation. The Arrhenius-equation parameters obtained from analysis of the thermal denaturation were compared with those of other proteins that have been reported to show the one-step irreversible thermal denaturation. Maltodextrin glucosidase had sufficiently high kinetic stability with a half-life of 68 days at a physiological temperature (37°C).

Changing folding and binding stability in a viral coat protein: a comparison between substitutions accessible through mutation and those fixed by natural selection

Previous studies have shown that most random amino acid substitutions destabilize protein folding (i.e. increase the folding free energy). No analogous studies have been carried out for protein-protein binding. Here we use a structure-based model of the major coat protein in a simple virus, bacteriophage φX174, to estimate the free energy of folding of a single coat protein and binding of five coat proteins within a pentameric unit. We confirm and extend previous work in finding that most accessible substitutions destabilize both protein folding and protein-protein binding. We compare the pool of accessible substitutions with those observed among the φX174-like wild phage and in experimental evolution with φX174. We find that observed substitutions have smaller effects on stability than expected by chance. An analysis of adaptations at high temperatures suggests that selection favors either substitutions with no effect on stability or those that simultaneously stabilize protein folding and slightly destabilize protein binding. We speculate that these mutations might involve adjusting the rate of capsid assembly. At normal laboratory temperature there is little evidence of directional selection. Finally, we show that cumulative changes in stability are highly variable; sometimes they are well beyond the bounds of single substitution changes and sometimes they are not. The variation leads us to conclude that phenotype selection acts on more than just stability. Instances of larger cumulative stability change (never via a single substitution despite their availability) lead us to conclude that selection views stability at a local, not a global, level.

Mutational studies on resurrected ancestral proteins reveal conservation of site-specific amino acid preferences throughout evolutionary history

Local protein interactions (“molecular context” effects) dictate amino acid replacements and can be described in terms of site-specific, energetic preferences for any different amino acid. It has been recently debated whether these preferences remain approximately constant during evolution or whether, due to coevolution of sites, they change strongly. Such research highlights an unresolved and fundamental issue with far-reaching implications for phylogenetic analysis and molecular evolution modeling. Here, we take advantage of the recent availability of phenotypically supported laboratory resurrections of Precambrian thioredoxins and β-lactamases to experimentally address the change of site-specific amino acid preferences over long geological timescales. Extensive mutational analyses support the notion that evolutionary adjustment to a new amino acid may occur, but to a large extent this is insufficient to erase the primitive preference for amino acid replacements. Generally, site-specific amino acid preferences appear to remain conserved throughout evolutionary history despite local sequence divergence. We show such preference conservation to be readily understandable in molecular terms and we provide crystallographic evidence for an intriguing structural-switch mechanism: Energetic preference for an ancestral amino acid in a modern protein can be linked to reorganization upon mutation to the ancestral local structure around the mutated site. Finally, we point out that site-specific preference conservation naturally leads to one plausible evolutionary explanation for the existence of intragenic global suppressor mutations.

The lower limits for protein stability and foldability in primary hyperoxaluria type I

Mutational effects on protein stability and foldability are important to understand conformational diseases and protein evolution. In this work, we perform a comprehensive investigation on the energetic basis underlying mutational effects on the stability of human alanine:glyoxylate aminotransferase (AGT). We study twenty two variants whose kinetic stabilities span over eleven orders of magnitude and are classified into two groups: i) ten naturally-occurring variants, including the most common mutations causing primary hyperoxaluria type I (PH1); and ii) twelve consensus variants obtained by sequence-alignment statistics. We show that AGT dimer stability determines denaturation rates, and mutations modulate stability by changes in the effective thermodynamic stability, the aggregation propensity of partially/globally unfolded states and subtle energetic changes in the rate-limiting denaturation step. In combination with our previous expression analyses in eukaryotic cells, we propose the existence of two lower limits for AGT stability, one linked to optimal folding efficiency (close to the major allele stability) and the other setting a minimal efficiency compatible with glyoxylate detoxification in vivo (close to the minor allele stability). These lower limits could explain the high prevalence of misfolding as a disease mechanism in PH1 and support the use of pharmacological ligands aimed to increase AGT stability as therapies for this disease.

Phenotypic comparisons of consensus variants versus laboratory resurrections of Precambrian proteins

Consensus-sequence engineering has generated protein variants with enhanced stability, and sometimes, with modulated biological function. Consensus mutations are often interpreted as the introduction of ancestral amino acid residues. However, the precise relationship between consensus engineering and ancestral protein resurrection is not fully understood. Here, we report the properties of proteins encoded by consensus sequences derived from a multiple sequence alignment of extant, class A β-lactamases, as compared with the properties of ancient Precambrian β-lactamases resurrected in the laboratory. These comparisons considered primary sequence, secondary, and tertiary structure, as well as stability and catalysis against different antibiotics. Out of the three consensus variants generated, one could not be expressed and purified (likely due to misfolding and/or low stability) and only one displayed substantial stability having substrate promiscuity, although to a lower extent than ancient β-lactamases. These results: (i) highlight the phenotypic differences between consensus variants and laboratory resurrections of ancestral proteins; (ii) question interpretations of consensus proteins as phenotypic proxies of ancestral proteins; and (iii) support the notion that ancient proteins provide a robust approach toward the preparation of protein variants having large numbers of mutational changes while possessing unique biomolecular properties.

pH-dependent relationship between thermodynamic and kinetic stability in the denaturation of human phosphoglycerate kinase 1

Human phosphoglycerate kinase 1 (hPGK1) is a glycolytic enzyme essential for ATP synthesis, and it is implicated in different pathological conditions such as inherited diseases, oncogenesis and activation of drugs for cancer and viral treatments. Particularly, mutations in hPGK1 cause human PGK1 deficiency, a rate metabolic conformational disease. We have recently found that most of these mutations cause protein kinetic destabilization by significant changes in the structure/energetics of the transition state for irreversible denaturation. In this work, we explore the relationships between protein conformation, thermodynamic and kinetic stability in hPGK1 by performing comprehensive analyses in a wide pH range (2.5-8). hPGK1 remains in a native conformation at pH 5-8, but undergoes a conformational transition to a molten globule-like state at acidic pH. Interestingly, hPGK1 kinetic stability remains essentially constant at pH 6-8, but is significantly reduced when pH is decreased from 6 to 5. We found that this decrease in kinetic stability is caused by significant changes in the energetic/structural balance of the denaturation transition state, which diverge from those found for disease-causing mutations. We also show that protein kinetic destabilization by acidic pH is strongly linked to lower thermodynamic stability, while in disease-causing mutations seems to be linked to lower unfolding cooperativity. These results highlight the plasticity of the hPGK1 denaturation mechanism that responds differently to changes in pH and in disease-causing mutations. New insight is presented into the different factors contributing to hPGK1 thermodynamic and kinetic stability and the role of denaturation mechanisms in hPGK1 deficiency.

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

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

GroEL/ES buffering and compensatory mutations promote protein evolution by stabilizing folding intermediates

Maintaining stability is a major constraint in protein evolution because most mutations are destabilizing. Buffering and/or compensatory mechanisms that counteract this progressive destabilization during functional adaptation are pivotal for protein evolution as well as protein engineering. However, the interplay of these two mechanisms during a full evolutionary trajectory has never been explored. Here, we unravel such dynamics during the laboratory evolution of a phosphotriesterase into an arylesterase. A controllable GroEL/ES chaperone co-expression system enabled us to vary the selection environment between buffering and compensatory, which smoothened the trajectory along the fitness landscape to achieve a >10(4) increase in arylesterase activity. Biophysical characterization revealed that, in contrast to prevalent models of protein stability and evolution, the variants' soluble cellular expression did not correlate with in vitro stability, and compensatory mutations were linked to a stabilization of folding intermediates. Thus, folding kinetics in the cell are a key feature of protein evolvability.

Modulating protein stability - directed evolution strategies for improved protein function

Protein engineering is widely used to generate proteins with novel or enhanced function. However, manipulating protein function in the laboratory can prove laborious, protracted and challenging. Recent developments in the understanding of protein evolutionary dynamics have unveiled the full extent by which the evolution of function is limited by protein stability - a revelation that may be applied to protein engineering on a whole. Thus, strategies that modulate protein stability and reduce its constraining effects may facilitate the engineering of protein function. A combinatorial approach involving the introduction of compensatory mutations and manipulation of the stability threshold by chaperone buffering during directed evolution can improve the functional adaptation of a protein, thereby fostering our ability to attain ever-more ambitious protein functions in the laboratory.

Hyperstability and substrate promiscuity in laboratory resurrections of Precambrian β-lactamases

We report a sequence reconstruction analysis targeting several Precambrian nodes in the evolution of class-A β-lactamases and the preparation and experimental characterization of their encoded proteins. Despite extensive sequence differences with the modern enzymes (~100 amino acid differences), the proteins resurrected in the laboratory properly fold into the canonical lactamase structure. The encoded proteins from 2-3 billion years (Gyr)-old β-lactamase sequences undergo cooperative two-state thermal denaturation and display very large denaturation temperature enhancements (~35 °C) relative to modern β-lactamases. They degrade different antibiotics in vitro with catalytic efficiencies comparable to that of an average modern enzyme. This enhanced substrate promiscuity is not accompanied by significant changes in the active-site region as seen in static X-ray structures, suggesting a plausible role for dynamics in the evolution of function in these proteins. Laboratory resurrections of 2-3 Gyr-old β-lactamases also endowed modern microorganisms with significant levels of resistance toward a variety of antibiotics, opening up the possibility of performing laboratory replays of the molecular tape of lactamase evolution. Overall, these results support the notions that Precambrian life was thermophilic and that proteins can evolve from substrate-promiscuous generalists into specialists during the course of natural evolution. They also highlight the biotechnological potential of laboratory resurrection of Precambrian proteins, as both high stability and enhanced promiscuity (likely contributors to high evolvability) are advantageous features in protein scaffolds for molecular design and laboratory evolution.

Structural and energetic basis of protein kinetic destabilization in human phosphoglycerate kinase 1 deficiency

Protein kinetic destabilization is a common feature of many human genetic diseases. Human phosphoglycerate kinase 1 (PGK1) deficiency is a rare genetic disease caused by mutations in the PGK1 protein, which often shows reduced kinetic stability. In this work, we have performed an in-depth characterization of the thermal stability of the wild type and four disease-causing mutants (I47N, L89P, E252A, and T378P) of human PGK1. PGK1 thermal denaturation is a process under kinetic control, and it is described well by a two-state irreversible denaturation model. Kinetic analysis of differential scanning calorimetry profiles shows that the disease-causing mutations decrease PGK1 kinetic stability from ~5-fold (E252A) to ~100000-fold (L89P) compared to that of wild-type PGK1, and in some cases, mutant enzymes are denatured on a time scale of a few minutes at physiological temperature. We show that changes in protein kinetic stability are associated with large differences in enthalpic and entropic contributions to denaturation free energy barriers. It is also shown that the denaturation transition state becomes more nativelike in terms of solvent exposure as the protein is destabilized by mutations (Hammond effect). Unfolding experiments with urea further suggest a scenario in which the thermodynamic stability of PGK1 at least partly determines its kinetic stability. ATP and ADP kinetically stabilize PGK1 enzymes, and kinetic stabilization is nucleotide- and mutant-selective. Overall, our data provide insight into the structural and energetic basis underlying the low kinetic stability displayed by some mutants causing human PGK1 deficiency, which may have important implications for the development of native state kinetic stabilizers for the treatment of this disease.

Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59

Computational design is a test of our understanding of enzyme catalysis and a means of engineering novel, tailor-made enzymes. While the de novo computational design of catalytically efficient enzymes remains a challenge, designed enzymes may comprise unique starting points for further optimization by directed evolution. Directed evolution of two computationally designed Kemp eliminases, KE07 and KE70, led to low to moderately efficient enzymes (k(cat)/K(m) values of ≤ 5 10(4) M(-1)s(-1)). Here we describe the optimization of a third design, KE59. Although KE59 was the most catalytically efficient Kemp eliminase from this design series (by k(cat)/K(m), and by catalyzing the elimination of nonactivated benzisoxazoles), its impaired stability prevented its evolutionary optimization. To boost KE59's evolvability, stabilizing consensus mutations were included in the libraries throughout the directed evolution process. The libraries were also screened with less activated substrates. Sixteen rounds of mutation and selection led to > 2,000-fold increase in catalytic efficiency, mainly via higher k(cat) values. The best KE59 variants exhibited k(cat)/K(m) values up to 0.6 10(6) M(-1)s(-1), and k(cat)/k(uncat) values of ≤ 10(7) almost regardless of substrate reactivity. Biochemical, structural, and molecular dynamics (MD) simulation studies provided insights regarding the optimization of KE59. Overall, the directed evolution of three different designed Kemp eliminases, KE07, KE70, and KE59, demonstrates that computational designs are highly evolvable and can be optimized to high catalytic efficiencies.

Deciphering modern glucocorticoid cross-pharmacology using ancestral corticosteroid receptors

Steroid receptors (SRs) are the largest family of metazoan transcription factors and control genes involved in development, endocrine signaling, reproduction, immunity, and cancer. The entire hormone receptor system is driven by a molecular switch triggered by the binding of small lipophilic ligands. This makes the SRs ideal pharmaceutical targets, yet even the best clinically approved synthetic steroidal agonists are prone to cross-reactivity and off-target pharmacology. The mechanism underlying this promiscuity is derived from the fact that SRs share common structural features derived from their evolutionary relationship. More often than not, rational attempts to probe SR drug selectivity via mutagenesis fail even when high quality structural and functional data are available due to the fact that important mutations often result in nonfunctional receptors. This highlights the fact that SRs suffer from instability, preventing in-depth mutational analysis and hampering crystallization of key receptor-ligand complexes. We have taken a unique approach to address this problem by using a resurrected ancestral protein to determine the structure of a previously intractable complex and identified the structural mechanisms that confer activation and selectivity for a widely used glucocorticoid, mometasone furoate. Moreover, we have identified a single residue located outside of the ligand-binding pocket that controls mometasone furoate antagonism versus agonism in the human mineralocorticoid receptor.

Highly anomalous energetics of protein cold denaturation linked to folding-unfolding kinetics

Despite several careful experimental analyses, it is not yet clear whether protein cold-denaturation is just a “mirror image” of heat denaturation or whether it shows unique structural and energetic features. Here we report that, for a well-characterized small protein, heat denaturation and cold denaturation show dramatically different experimental energetic patterns. Specifically, while heat denaturation is endothermic, the cold transition (studied in the folding direction) occurs with negligible heat effect, in a manner seemingly akin to a gradual, second-order-like transition. We show that this highly anomalous energetics is actually an apparent effect associated to a large folding/unfolding free energy barrier and that it ultimately reflects kinetic stability, a naturally-selected trait in many protein systems. Kinetics thus emerges as an important factor linked to differential features of cold denaturation. We speculate that kinetic stabilization against cold denaturation may play a role in cold adaptation of psychrophilic organisms. Furthermore, we suggest that folding-unfolding kinetics should be taken into account when analyzing in vitro cold-denaturation experiments, in particular those carried out in the absence of destabilizing conditions.

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.

Single-molecule paleoenzymology probes the chemistry of resurrected enzymes

A journey back in time is possible at the molecular level by reconstructing proteins from extinct organisms. Here we report the reconstruction, based on sequence predicted by phylogenetic analysis, of seven Precambrian thioredoxin enzymes (Trx), dating back between ~1.4 and ~4 billion years (Gyr). The reconstructed enzymes are up to 32° C more stable than modern enzymes and the oldest show significantly higher activity than extant ones at pH 5. We probed their mechanisms of reduction using single-molecule force spectroscopy. From the force-dependency of the rate of reduction of an engineered substrate, we conclude that ancient Trxs utilize chemical mechanisms of reduction similar to those of modern enzymes. While Trx enzymes have maintained their reductase chemistry unchanged, they have adapted over a 4 Gyr time span to the changes in temperature and ocean acidity that characterize the evolution of the global environment from ancient to modern Earth.

Deciphering the role of the thermodynamic and kinetic stabilities of SH3 domains on their aggregation inside bacteria

The formation of insoluble deposits by globular proteins underlies the onset of many human diseases. Recent studies suggest a relationship between the thermodynamic stability of proteins and their in vivo aggregation. However, it has been argued that, in the cell, the occurrence of irreversible aggregation might shift the system from equilibrium, in such a way that it could be the rate of unfolding and associated kinetic stability instead of the conformational stability that controls protein deposition. This is an important but difficult to decipher question, because kinetic and thermodynamic stabilities appear usually correlated. Here we address this issue by comparing the in vitro folding kinetics and stability features of a set of non-natural SH3 domains with their aggregation properties when expressed in bacteria. In addition, we compare the in vitro stability of the isolated domains with their effective stability in conditions that mimic the cytosolic environment. Overall, the data argue in favor of a thermodynamic rather than a kinetic control of the intracellular aggregation propensities of small globular proteins in which folding and unfolding velocities largely exceed aggregation rates. These results have implications regarding the evolution of proteins.

Single-Molecule characterization of oligomerization kinetics and equilibria of the tumor suppressor p53

The state of oligomerization of the tumor suppressor p53 is an important factor in its various biological functions. It has a well-defined tetramerization domain, and the protein exists as monomers, dimers and tetramers in equilibrium. The dissociation constants between oligomeric forms are so low that they are at the limits of measurement by conventional methods in vitro. Here, we have used the high sensitivity of single-molecule methods to measure the equilibria and kinetics of oligomerization of full-length p53 and its isolated tetramerization domain, p53tet, at physiological temperature, pH and ionic strength using fluorescence correlation spectroscopy (FCS) in vitro. The dissociation constant at 37°C for tetramers dissociating into dimers for full-length p53 was 50 ± 7 nM, and the corresponding value for dimers into monomers was 0.55 ± 0.08 nM. The half-lives for the two processes were 20 and 50 min, respectively. The equivalent quantities for p53tet were 150 ± 10 nM, 1.0 ± 0.14 nM, 2.5 ± 0.4 min and 13 ± 2 min. The data suggest that unligated p53 in unstressed cells should be predominantly dimeric. Single-molecule FCS is a useful procedure for measuring dissociation equilibria, kinetics and aggregation at extreme sensitivity.

Role of conservative mutations in protein multi-property adaptation

Protein physicochemical properties must undergo complex changes during evolution, as a response to modifications in the organism environment, the result of the proteins taking up new roles or because of the need to cope with the evolution of molecular interacting partners. Recent work has emphasized the role of stability and stability-function trade-offs in these protein adaptation processes. In the present study, on the other hand, we report that combinations of a few conservative, high-frequency-of-fixation mutations in the thioredoxin molecule lead to largely independent changes in both stability and the diversity of catalytic mechanisms, as revealed by single-molecule atomic force spectroscopy. Furthermore, the changes found are evolutionarily significant, as they combine typically hyperthermophilic stability enhancements with modulations in function that span the ranges defined by the quite different catalytic patterns of thioredoxins from bacterial and eukaryotic origin. These results suggest that evolutionary protein adaptation may use, in some cases at least, the potential of conservative mutations to originate a multiplicity of evolutionarily allowed mutational paths leading to a variety of protein modulation patterns. In addition the results support the feasibility of using evolutionary information to achieve protein multi-feature optimization, an important biotechnological goal.

Proteolytic scanning calorimetry: a novel methodology that probes the fundamental features of protein kinetic stability

We introduce proteolytic scanning calorimetry, a modification of the differential scanning calorimetry approach to the determination of protein stability in which a proteolytic enzyme (thermolysin) is used to mimic a harsh environment. This methodology allows the straightforward calculation of the rate of irreversible denaturation as a function of temperature and concentration of proteolytic enzyme and, as a result, has the potential to probe efficiently the fundamental biophysical features of protein kinetic stability. In the particular case of Escherichia coli thioredoxin (used as an illustrative example in this article), we find that the rate of irreversible denaturation is determined by 1), the global unfolding mechanism at low thermolysin concentrations, indicating that thermodynamic stability may contribute directly to the kinetic stability of thioredoxin under moderately harsh conditions and 2), the rate of unfolding at high thermolysin concentrations, indicating that the free-energy barrier for unfolding may act as a safety mechanism that ensures significant kinetic stability, even in very harsh environments. This thioredoxin picture, however, is by no means expected to be general and different proteins may show different patterns of kinetic stabilization. Proteolytic scanning calorimetry is particularly well-suited to probe this diversity at a fundamental biophysical level.

Extreme sensitivity of botulinum neurotoxin domains towards mild agitation

Botulinum neurotoxins (BoNTs) and their fragments are targets of therapeutic developments and are increasingly used as therapeutic, prophylactic, and research reagents. However, published data on their properties vary widely. In order to gain a better understanding of these variations, we initiated a systematic investigation of the stability parameters of catalytic light chains (Lc) as well as of cell surface binding domains (Hc) of the neurotoxin. When followed by CD spectroscopy, we noticed that the recombinant light chains of serotypes A (LcA), B, D, E, and G rapidly lost their secondary structures by mild stirring. Denaturation of LcA increased with stirring speed and temperature resulting in a catalytically inactive precipitate. Reducing agents or an anaerobic environment were ineffective in the denaturation. Under identical conditions, bovine serum albumin, ovalbumin, carboxypeptidase B, and of thermolysin, a structural and functional analogue of LcA, remained unchanged. Hc domains of serotype A, B, C, E, and F were also denatured by mild stirring. Adding the nonionic detergent Tween-20 to LcA completely prevented the denaturation. We speculate that the BoNT domains undergo surface denaturation due to rapid exposure of hydrophobic residues by mechanical agitation. This study has important implications for handling BoNT proteins used in therapeutic development.

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.

Between-species variation in the kinetic stability of TIM proteins linked to solvation-barrier free energies

Theoretical, computational, and experimental studies have suggested the existence of solvation barriers in protein unfolding and denaturation processes. These barriers are related to the finite size of water molecules and can be envisioned as arising from the asynchrony between water penetration and breakup of internal interactions. Solvation barriers have been proposed to play roles in protein cooperativity and kinetic stability; therefore, they may be expected to be subject to natural selection. We study the thermal denaturation, in the presence and in the absence of chemical denaturants, of triosephosphate isomerases (TIMs) from three different species: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania mexicana. In all cases, denaturation was irreversible and kinetically controlled. Surprisingly, however, we found large differences between the kinetic denaturation parameters, with T. cruzi TIM showing a much larger activation energy value (and, consequently, much lower room-temperature, extrapolated denaturation rates). This disparity cannot be accounted for by variations in the degree of exposure to solvent in transition states (as measured by kinetic urea m values) and is, therefore, to be attributed mainly to differences in solvation-barrier contributions. This was supported by structure-energetics analyses of the transition states and by application of a novel procedure to estimate from experimental data the solvation-barrier impact at the entropy and free-energy levels. These analyses were actually performed with an extended protein set (including six small proteins plus seven variants of lipase from Thermomyces lanuginosus and spanning a wide range of activation parameters), allowing us to delineate the general trends of the solvation-barrier contributions. Overall, this work supports that proteins sharing the same structure and function but belonging to different organisms may show widely different solvation barriers, possibly as a result of different levels of the selection pressure associated with cooperativity, kinetic stability, and related factors.

Intense neutral drifts yield robust and evolvable consensus proteins

What changes occur when a natural protein that had been under low mutation rates is subjected to a neutral drift at high mutational loads, thus generating genetically diverse (polymorphic) gene ensembles that all maintain the protein's original function and structure? To address this question we subjected large populations of TEM-1 beta-lactamase to a prolonged neutral drift, applying high mutation rates and purifying selection to maintain TEM-1's existing penicillinase activity. Purging of deleterious mutations and enrichment of beneficial ones maintained the sequence of these ensembles closer to TEM-1's family consensus and inferred ancestor. In particular, back-to-consensus/ancestor mutations that increase TEM-1's kinetic and thermodynamic stability were enriched. These acted as global suppressors and enabled the tolerance of a broad range of deleterious mutations, thus further increasing the genetic diversity of the drifting populations. The probability of a new function emerging (cefotaxime degradation) was also substantially increased in these ensembles owing to the presence of many gene variants carrying the global suppressors. Our findings indicate the unique features of large, polymorphic neutral ensembles generated under high mutational loads and prompt the speculation that the progenitors of today's proteins may have evolved under high mutational loads. The results also suggest that predictable back-to-consensus/ancestor changes can be used in the laboratory to generate highly diverse and evolvable gene libraries.