How protein stability and new functions trade off

Directed polymerase evolution

Polymerases evolved in nature to synthesize DNA and RNA, and they underlie the storage and flow of genetic information in all cells. The availability of these enzymes for use at the bench has driven a revolution in biotechnology and medicinal research; however, polymerases did not evolve to function efficiently under the conditions required for some applications and their high substrate fidelity precludes their use for most applications that involve modified substrates. To circumvent these limitations, researchers have turned to directed evolution to tailor the properties and/or substrate repertoire of polymerases for different applications, and several systems have been developed for this purpose. These systems draw on different methods of creating a pool of randomly mutated polymerases and are differentiated by the process used to isolate the most fit members. A variety of polymerases have been evolved, providing new or improved functionality, as well as interesting new insight into the factors governing activity.

Computational analysis of C-reactive protein for assessment of molecular dynamics and interaction properties

Serum C-reactive protein (CRP) is used as a marker of inflammation in several diseases including autoimmune disease and cardiovascular disease. CRP, a member of the pentraxin family, is comprised of five identical subunits. CRP has diverse ligand-binding properties which depend upon different structural states of CRP. However, little is known about the molecular dynamics and interaction properties of CRP. In this study, we used SAPS, SCRATCH protein predictor, PDBsum, ConSurf, ProtScale, Drawhca, ASAView, SCide and SRide server and performed comprehensive analyses of molecular dynamics, protein-protein and residue-residue interactions of CRP. We used 1GNH.pdb file for the crystal structure of human CRP which generated two pentamers (ABCDE and FGHIJ). The number of residues involved in residue-residue interactions between A-B, B-C, C-D, D-E, F-G, G-H, H-I, I-J, A-E and F-J subunits were 12, 11, 10, 11, 12, 11, 10, 11, 10 and 10, respectively. Fifteen antiparallel β sheets were involved in β-sheet topology, and five β hairpins were involved in forming the secondary structure. Analysis of hydrophobic segment distribution revealed deviations in surface hydrophobicity at different cavities present in CRP. Approximately 33 % of all residues were involved in the stabilization centers. We show that the bioinformatics tools can provide a rapid method to predict molecular dynamics and interaction properties of CRP. Our prediction of molecular dynamics and interaction properties of CRP combined with the modeling data based on the known 3D structure of CRP is helpful in designing stable forms of CRP mutants for structure-function studies of CRP and may facilitate in silico drug design for therapeutic targeting of CRP.

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.

Directed evolution of aminoglycoside phosphotransferase (3') type IIIa variants that inactivate amikacin but impose significant fitness costs

The rules that govern adaptive protein evolution remain incompletely understood. Aminoglycoside aminotransferase (3′) type IIIa (hereafter abbreviated APH(3′)-IIIa) is a good model enzyme because it inactivates kanamycin efficiently; it recognizes other aminoglycoside antibiotics, including amikacin, but not nearly as well. Here we direct the evolution of APH(3′)-IIIa variants with increased activity against amikacin. After four rounds of random mutation and selection in Escherichia coli, the minimum inhibitory concentration of amikacin rose from 18 micrograms/mL (wild-type enzyme) to over 1200 micrograms/mL (clone 4.1). The artificially evolved 4.1 APH(3′)-IIIa variant exhibited 19-fold greater catalytic efficiency (k_cat/K_M) than did the wild-type enzyme in reactions with amikacin. E. coli expressing the evolved 4.1 APH(3′)-IIIa also exhibited a four-fold decrease in fitness (as measured by counting colony forming units in liquid cultures with the same optical density) compared with isogenic cells expressing the wild-type protein under non-selective conditions. We speculate that these fitness costs, in combination with the prevalence of other amikacin-modifying enzymes, hinder the evolution of APH(3′)-IIIa in clinical settings.

Genetic variation in Chlamydia trachomatis and their hosts: impact on disease severity and tissue tropism

Chlamydia trachomatis infections are a global health problem. This obligate intracellular bacterial pathogen comprises lymphogranuloma venereum (L1-L3), ocular (A-C) and genital (D-K) serovars. Although genetically similar, each serovar group differs in disease severity and tissue tropism through mechanisms that are not well understood. It is clear that host genetic differences also play a role in chlamydial disease outcome and key host polymorphisms are beginning to emerge from both human and experimental animal studies. In this review, we will highlight pathogen and host genes that link genetic diversity, disease severity and tissue tropism. We will also use this information to provide new insights that may be helpful in developing improved management strategies for these important pathogens.

Path-based approach to random walks on networks characterizes how proteins evolve new functions

We develop a path-based approach to continuous-time random walks on networks with arbitrarily weighted edges. We describe an efficient numerical algorithm for calculating statistical properties of the stochastic path ensemble. After demonstrating our approach on two reaction rate problems, we present a biophysical model that describes how proteins evolve new functions while maintaining thermodynamic stability. We use our methodology to characterize dynamics of evolutionary adaptation, reproducing several key features observed in directed evolution experiments. We find that proteins generally fall into two qualitatively different regimes of adaptation depending on their binding and folding energetics.

Capturing the mutational landscape of the beta-lactamase TEM-1

Adaptation proceeds through the selection of mutations. The distribution of mutant fitness effect and the forces shaping this distribution are therefore keys to predict the evolutionary fate of organisms and their constituents such as enzymes. Here, by producing and sequencing a comprehensive collection of 10,000 mutants, we explore the mutational landscape of one enzyme involved in the spread of antibiotic resistance, the beta-lactamase TEM-1. We measured mutation impact on the enzyme activity through the estimation of amoxicillin minimum inhibitory concentration on a subset of 990 mutants carrying a unique missense mutation, representing 64% of possible amino acid changes in that protein reachable by point mutation. We established that mutation type, solvent accessibility of residues, and the predicted effect of mutations on protein stability primarily determined alone or in combination changes in minimum inhibitory concentration of mutants. Moreover, we were able to capture the drastic modification of the mutational landscape induced by a single stabilizing point mutation (M182T) by a simple model of protein stability. This work thereby provides an integrated framework to study mutation effects and a tool to understand/define better the epistatic interactions.

Molecular mechanisms of disease-causing missense mutations

Genetic variations resulting in a change of amino acid sequence can have a dramatic effect on stability, hydrogen bond network, conformational dynamics, activity and many other physiologically important properties of proteins. The substitutions of only one residue in a protein sequence, so-called missense mutations, can be related to many pathological conditions and may influence susceptibility to disease and drug treatment. The plausible effects of missense mutations range from affecting the macromolecular stability to perturbing macromolecular interactions and cellular localization. Here we review the individual cases and genome-wide studies that illustrate the association between missense mutations and diseases. In addition, we emphasize that the molecular mechanisms of effects of mutations should be revealed in order to understand the disease origin. Finally, we report the current state-of-the-art methodologies that predict the effects of mutations on protein stability, the hydrogen bond network, pH dependence, conformational dynamics and protein function.

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.

Stability Mechanisms of Laccase Isoforms using a Modified FoldX Protocol Applicable to Widely Different Proteins

A recent computational protocol that accurately predicts and rationalizes protein multisite mutant stabilities has been extended to handle widely different isoforms of laccases. We apply the protocol to four isoenzymes of Trametes versicolor laccase (TvL) with variable lengths (498-503 residues) and thermostability (Topt ∼ 45-80 °C) and with 67-77% sequence identity. The extended protocol uses (i) statistical averaging, (ii) a molecular-dynamics-validated "compromise" homology model to minimize bias that causes proteins close in sequence to a structural template to be too stable due to having the benefits of the better sampled template (typically from a crystal structure), (iii) correction for hysteresis that favors the input template to overdestabilize, and (iv) a preparative protocol to provide robust input sequences of equal length. The computed ΔΔG values are in good agreement with the major trends in experimental stabilities; that is, the approach may be applicable for fast estimates of the relative stabilities of proteins with as little as 70% identity, something that is currently extremely challenging. The computed stability changes associated with variations are Gaussian-distributed, in good agreement with experimental distributions of stability effects from mutation. The residues causing the differential stability of the four isoforms are consistent with a range of compiled laccase wild type data, suggesting that we may have identified general drivers of laccase stability. Several sites near Cu, notably 79, 241, and 245, or near substrate, mainly 265, are identified that contribute to stability-function trade-offs, of relevance to the search for new proficient and stable variants of these important industrial enzymes.

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.

Fisher's geometric model of adaptation meets the functional synthesis: data on pairwise epistasis for fitness yields insights into the shape and size of phenotype space

The functional synthesis uses experimental methods from molecular biology, biochemistry and structural biology to decompose evolutionarily important mutations into their more proximal mechanistic determinants. However these methods are technically challenging and expensive. Noting strong formal parallels between R.A. Fisher's geometric model of adaptation and a recent model for the phenotypic basis of protein evolution, we sought to use the former to make inferences into the latter using data on pairwise fitness epistasis between mutations. We present an analytic framework for classifying pairs of mutations with respect to similarity of underlying mechanism on this basis, and also show that these data can yield an estimate of the number of mutationally labile phenotypes underlying fitness effects. We use computer simulations to explore the robustness of our approach to violations of analytic assumptions and analyze several recently published datasets. This work provides a theoretical complement to the functional synthesis as well as a novel test of Fisher's geometric model.

Environmental dependence of genetic constraint

The epistatic interactions that underlie evolutionary constraint have mainly been studied for constant external conditions. However, environmental changes may modulate epistasis and hence affect genetic constraints. Here we investigate genetic constraints in the adaptive evolution of a novel regulatory function in variable environments, using the lac repressor, LacI, as a model system. We have systematically reconstructed mutational trajectories from wild type LacI to three different variants that each exhibit an inverse response to the inducing ligand IPTG, and analyzed the higher-order interactions between genetic and environmental changes. We find epistasis to depend strongly on the environment. As a result, mutational steps essential to inversion but inaccessible by positive selection in one environment, become accessible in another. We present a graphical method to analyze the observed complex higher-order interactions between multiple mutations and environmental change, and show how the interactions can be explained by a combination of mutational effects on allostery and thermodynamic stability. This dependency of genetic constraint on the environment should fundamentally affect evolutionary dynamics and affects the interpretation of phylogenetic data.

Stability mechanisms of a thermophilic laccase probed by molecular dynamics

Laccases are highly stable, industrially important enzymes capable of oxidizing a large range of substrates. Causes for their stability are, as for other proteins, poorly understood. In this work, multiple-seed molecular dynamics (MD) was applied to a Trametes versicolor laccase in response to variable ionic strengths, temperatures, and glycosylation status. Near-physiological conditions provided excellent agreement with the crystal structure (average RMSD ∼0.92 Å) and residual agreement with experimental B-factors. The persistence of backbone hydrogen bonds was identified as a key descriptor of structural response to environment, whereas solvent-accessibility, radius of gyration, and fluctuations were only locally relevant. Backbone hydrogen bonds decreased systematically with temperature in all simulations (∼9 per 50 K), probing structural changes associated with enthalpy-entropy compensation. Approaching T_opt (∼350 K) from 300 K, this change correlated with a beginning “unzipping” of critical β-sheets. 0 M ionic strength triggered partial denucleation of the C-terminal (known experimentally to be sensitive) at 400 K, suggesting a general salt stabilization effect. In contrast, F⁻ (but not Cl⁻) specifically impaired secondary structure by formation of strong hydrogen bonds with backbone NH, providing a mechanism for experimentally observed small anion destabilization, potentially remedied by site-directed mutagenesis at critical intrusion sites. N-glycosylation was found to support structural integrity by increasing persistent backbone hydrogen bonds by ∼4 across simulations, mainly via prevention of F⁻ intrusion. Hydrogen-bond loss in distinct loop regions and ends of critical β-sheets suggest potential strategies for laboratory optimization of these industrially important enzymes.

What makes a protein fold amenable to functional innovation? Fold polarity and stability trade-offs

Protein evolvability includes two elements--robustness (or neutrality, mutations having no effect) and innovability (mutations readily inducing new functions). How are these two conflicting demands bridged? Does the ability to bridge them relate to the observation that certain folds, such as TIM barrels, accommodate numerous functions, whereas other folds support only one? Here, we hypothesize that the key to innovability is polarity--an active site composed of flexible, loosely packed loops alongside a well-separated, highly ordered scaffold. We show that highly stabilized variants of TEM-1 β-lactamase exhibit selective rigidification of the enzyme's scaffold while the active-site loops maintained their conformational plasticity. Polarity therefore results in stabilizing, compensatory mutations not trading off, but instead promoting the acquisition of new activities. Indeed, computational analysis indicates that in folds that accommodate only one function throughout evolution, for example, dihydrofolate reductase, ≥ 60% of the active-site residues belong to the scaffold. In contrast, folds associated with multiple functions such as the TIM barrel show high scaffold-active-site polarity (~20% of the active site comprises scaffold residues) and >2-fold higher rates of sequence divergence at active-site positions. Our work suggests structural measures of fold polarity that appear to be correlated with innovability, thereby providing new insights regarding protein evolution, design, and engineering.

Positively selected sites in cetacean myoglobins contribute to protein stability

Since divergence ∼50 Ma ago from their terrestrial ancestors, cetaceans underwent a series of adaptations such as a ∼10-20 fold increase in myoglobin (Mb) concentration in skeletal muscle, critical for increasing oxygen storage capacity and prolonging dive time. Whereas the O2-binding affinity of Mbs is not significantly different among mammals (with typical oxygenation constants of ∼0.8-1.2 µM(-1)), folding stabilities of cetacean Mbs are ∼2-4 kcal/mol higher than for terrestrial Mbs. Using ancestral sequence reconstruction, maximum likelihood and bayesian tests to describe the evolution of cetacean Mbs, and experimentally calibrated computation of stability effects of mutations, we observe accelerated evolution in cetaceans and identify seven positively selected sites in Mb. Overall, these sites contribute to Mb stabilization with a conditional probability of 0.8. We observe a correlation between Mb folding stability and protein abundance, suggesting that a selection pressure for stability acts proportionally to higher expression. We also identify a major divergence event leading to the common ancestor of whales, during which major stabilization occurred. Most of the positively selected sites that occur later act against other destabilizing mutations to maintain stability across the clade, except for the shallow divers, where late stability relaxation occurs, probably due to the shorter aerobic dive limits of these species. The three main positively selected sites 66, 5, and 35 undergo changes that favor hydrophobic folding, structural integrity, and intra-helical hydrogen bonds.

Antibiotics as selectors and accelerators of diversity in the mechanisms of resistance: from the resistome to genetic plasticity in the β-lactamases world

Antibiotics and antibiotic resistance determinants, natural molecules closely related to bacterial physiology and consistent with an ancient origin, are not only present in antibiotic-producing bacteria. Throughput sequencing technologies have revealed an unexpected reservoir of antibiotic resistance in the environment. These data suggest that co-evolution between antibiotic and antibiotic resistance genes has occurred since the beginning of time. This evolutionary race has probably been slow because of highly regulated processes and low antibiotic concentrations. Therefore to understand this global problem, a new variable must be introduced, that the antibiotic resistance is a natural event, inherent to life. However, the industrial production of natural and synthetic antibiotics has dramatically accelerated this race, selecting some of the many resistance genes present in nature and contributing to their diversification. One of the best models available to understand the biological impact of selection and diversification are β-lactamases. They constitute the most widespread mechanism of resistance, at least among pathogenic bacteria, with more than 1000 enzymes identified in the literature. In the last years, there has been growing concern about the description, spread, and diversification of β-lactamases with carbapenemase activity and AmpC-type in plasmids. Phylogenies of these enzymes help the understanding of the evolutionary forces driving their selection. Moreover, understanding the adaptive potential of β-lactamases contribute to exploration the evolutionary antagonists trajectories through the design of more efficient synthetic molecules. In this review, we attempt to analyze the antibiotic resistance problem from intrinsic and environmental resistomes to the adaptive potential of resistance genes and the driving forces involved in their diversification, in order to provide a global perspective of the resistance problem.

iStable: off-the-shelf predictor integration for predicting protein stability changes

BACKGROUND

Mutation of a single amino acid residue can cause changes in a protein, which could then lead to a loss of protein function. Predicting the protein stability changes can provide several possible candidates for the novel protein designing. Although many prediction tools are available, the conflicting prediction results from different tools could cause confusion to users.

RESULTS

We proposed an integrated predictor, iStable, with grid computing architecture constructed by using sequence information and prediction results from different element predictors. In the learning model, several machine learning methods were evaluated and adopted the support vector machine as an integrator, while not just choosing the majority answer given by element predictors. Furthermore, the role of the sequence information played was analyzed in our model, and an 11-window size was determined. On the other hand, iStable is available with two different input types: structural and sequential. After training and cross-validation, iStable has better performance than all of the element predictors on several datasets. Under different classifications and conditions for validation, this study has also shown better overall performance in different types of secondary structures, relative solvent accessibility circumstances, protein memberships in different superfamilies, and experimental conditions.

CONCLUSIONS

The trained and validated version of iStable provides an accurate approach for prediction of protein stability changes. iStable is freely available online at: http://predictor.nchu.edu.tw/iStable.

Residue mutations and their impact on protein structure and function: detecting beneficial and pathogenic changes

The present review focuses on the evolution of proteins and the impact of amino acid mutations on function from a structural perspective. Proteins evolve under the law of natural selection and undergo alternating periods of conservative evolution and of relatively rapid change. The likelihood of mutations being fixed in the genome depends on various factors, such as the fitness of the phenotype or the position of the residues in the three-dimensional structure. For example, co-evolution of residues located close together in three-dimensional space can occur to preserve global stability. Whereas point mutations can fine-tune the protein function, residue insertions and deletions (‘decorations’ at the structural level) can sometimes modify functional sites and protein interactions more dramatically. We discuss recent developments and tools to identify such episodic mutations, and examine their applications in medical research. Such tools have been tested on simulated data and applied to real data such as viruses or animal sequences. Traditionally, there has been little if any cross-talk between the fields of protein biophysics, protein structure–function and molecular evolution. However, the last several years have seen some exciting developments in combining these approaches to obtain an in-depth understanding of how proteins evolve. For example, a better understanding of how structural constraints affect protein evolution will greatly help us to optimize our models of sequence evolution. The present review explores this new synthesis of perspectives.

Structure-guided engineering of Lactococcus lactis alcohol dehydrogenase LlAdhA for improved conversion of isobutyraldehyde to isobutanol

We have determined the X-ray crystal structures of the NADH-dependent alcohol dehydrogenase LlAdhA from Lactococcus lactis and its laboratory-evolved variant LlAdhA(RE1) at 1.9Å and 2.5Å resolution, respectively. LlAdhA(RE1), which contains three amino acid mutations (Y50F, I212T, and L264V), was engineered to increase the microbial production of isobutanol (2-methylpropan-1-ol) from isobutyraldehyde (2-methylpropanal). Structural comparison of LlAdhA and LlAdhA(RE1) indicates that the enhanced activity on isobutyraldehyde stems from increases in the protein's active site size, hydrophobicity, and substrate access. Further structure-guided mutagenesis generated a quadruple mutant (Y50F/N110S/I212T/L264V), whose KM for isobutyraldehyde is ∼17-fold lower and catalytic efficiency (kcat/KM) is ∼160-fold higher than wild-type LlAdhA. Combining detailed structural information and directed evolution, we have achieved significant improvements in non-native alcohol dehydrogenase activity that will facilitate the production of next-generation fuels such as isobutanol from renewable resources.

Emergence of symmetric protein architecture from a simple peptide motif: evolutionary models

Structural symmetry is observed in the majority of fundamental protein folds and gene duplication and fusion evolutionary processes are postulated to be responsible. However, convergent evolution leading to structural symmetry has also been proposed; additionally, there is debate regarding the extent to which exact primary structure symmetry is compatible with efficient protein folding. Issues of symmetry in protein evolution directly impact strategies for de novo protein design as symmetry can substantially simplify the design process. Additionally, when considering gene duplication and fusion in protein evolution, there are two competing models: "emergent architecture" and "conserved architecture". Recent experimental work has shed light on both the evolutionary process leading to symmetric protein folds as well as the ability of symmetric primary structure to efficiently fold. Such studies largely support a "conserved architecture" evolutionary model, suggesting that complex protein architecture was an early evolutionary achievement involving oligomerization of smaller polypeptides.

Pharmacokinetic properties of 2nd-generation fibroblast growth factor-1 mutants for therapeutic application

Fibroblast growth factor-1 (FGF-1) is an angiogenic factor with therapeutic potential for the treatment of ischemic disease. FGF-1 has low intrinsic thermostability and is characteristically formulated with heparin as a stabilizing agent. Heparin, however, adds a number of undesirable properties that negatively impact safety and cost. Mutations that increase the thermostability of FGF-1 may obviate the need for heparin in formulation and may prove to be useful “2nd-generation” forms for therapeutic use. We report a pharmacokinetic (PK) study in rabbits of human FGF-1 in the presence and absence of heparin, as well as three mutant forms having differential effects upon thermostability, buried reactive thiols, and heparin affinity. The results support the hypothesis that heparan sulfate proteoglycan (HSPG) in the vasculature of liver, kidney and spleen serves as the principle peripheral compartment in the distribution kinetics. The addition of heparin to FGF-1 is shown to increase endocrine-like properties of distribution. Mutant forms of FGF-1 that enhance thermostability or eliminate buried reactive thiols demonstrate a shorter distribution half-life, a longer elimination half-life, and a longer mean residence time (MRT) in comparison to wild-type FGF-1. The results show how such mutations can produce useful 2nd-generation forms with tailored PK profiles for specific therapeutic application.

Analysis of the relationships between evolvability, thermodynamics, and the functions of intrinsically disordered proteins/regions

The evolvability of proteins is not only restricted by functional and structural importance, but also by other factors such as gene duplication, protein stability, and an organism's robustness. Recently, intrinsically disordered proteins (IDPs)/regions (IDRs) have been suggested to play a role in facilitating protein evolution. However, the mechanisms by which this occurs remain largely unknown. To address this, we have systematically analyzed the relationship between the evolvability, stability, and function of IDPs/IDRs. Evolutionary analysis shows that more recently emerged IDRs have higher evolutionary rates with more functional constraints relaxed (or experiencing more positive selection), and that this may have caused accelerated evolution in the flanking regions and in the whole protein. A systematic analysis of observed stability changes due to single amino acid mutations in IDRs and ordered regions shows that while most mutations induce a destabilizing effect in proteins, mutations in IDRs cause smaller stability changes than in ordered regions. The weaker impact of mutations in IDRs on protein stability may have advantages for protein evolvability in the gain of new functions. Interestingly, however, an analysis of functional motifs in the PROSITE and ELM databases showed that motifs in IDRs are more conserved, characterized by smaller entropy and lower evolutionary rate, than in ordered regions. This apparently opposing evolutionary effect may be partly due to the flexible nature of motifs in IDRs, which require some key amino acid residues to engage in tighter interactions with other molecules. Our study suggests that the unique conformational and thermodynamic characteristics of IDPs/IDRs play an important role in the evolvability of proteins to gain new functions.

Computer-Aided Protein Directed Evolution: a Review of Web Servers, Databases and other Computational Tools for Protein Engineering

The combination of computational and directed evolution methods has proven a winning strategy for protein engineering. We refer to this approach as computer-aided protein directed evolution (CAPDE) and the review summarizes the recent developments in this rapidly growing field. We will restrict ourselves to overview the availability, usability and limitations of web servers, databases and other computational tools proposed in the last five years. The goal of this review is to provide concise information about currently available computational resources to assist the design of directed evolution based protein engineering experiment.

Recent advances in rational approaches for enzyme engineering

Enzymes are an attractive alternative in the asymmetric syntheses of chiral building blocks. To meet the requirements of industrial biotechnology and to introduce new functionalities, the enzymes need to be optimized by protein engineering. This article specifically reviews rational approaches for enzyme engineering and de novo enzyme design involving structure-based approaches developed in recent years for improvement of the enzymes’ performance, broadened substrate range, and creation of novel functionalities to obtain products with high added value for industrial applications.

Engineering a model protein cavity to catalyze the Kemp elimination

Synthetic cavitands and protein cavities have been widely studied as models for ligand recognition. Here we investigate the Met102 → His substitution in the artificial L99A cavity in T4 lysozyme as a Kemp eliminase. The resulting enzyme had k(cat)/K(M) = 0.43 M(-1) s(-1) and a (k(cat)/K(M))/k(uncat) = 10(7) at pH 5.0. The crystal structure of this enzyme was determined at 1.30 Å, as were the structures of four complexes of substrate and product analogs. The absence of ordered waters or hydrogen bonding interactions, and the presence of a common catalytic base (His102) in an otherwise hydrophobic, buried cavity, facilitated detailed analysis of the reaction mechanism and its optimization. Subsequent substitutions increased eliminase activity by an additional four-fold. As activity-enhancing substitutions were engineered into the cavity, protein stability decreased, consistent with the stability-function trade-off hypothesis. This and related model cavities may provide templates for studying protein design principles in radically simplified environments.

Correlated electrostatic mutations provide a reservoir of stability in HIV protease

HIV protease, an aspartyl protease crucial to the life cycle of HIV, is the target of many drug development programs. Though many protease inhibitors are on the market, protease eventually evades these drugs by mutating at a rapid pace and building drug resistance. The drug resistance mutations, called primary mutations, are often destabilizing to the enzyme and this loss of stability has to be compensated for. Using a coarse-grained biophysical energy model together with statistical inference methods, we observe that accessory mutations of charged residues increase protein stability, playing a key role in compensating for destabilizing primary drug resistance mutations. Increased stability is intimately related to correlations between electrostatic mutations – uncorrelated mutations would strongly destabilize the enzyme. Additionally, statistical modeling indicates that the network of correlated electrostatic mutations has a simple topology and has evolved to minimize frustrated interactions. The model's statistical coupling parameters reflect this lack of frustration and strongly distinguish like-charge electrostatic interactions from unlike-charge interactions for of the most significantly correlated double mutants. Finally, we demonstrate that our model has considerable predictive power and can be used to predict complex mutation patterns, that have not yet been observed due to finite sample size effects, and which are likely to exist within the larger patient population whose virus has not yet been sequenced.

HIV is incurable because its enzymes evolve rapidly by developing resistance mutations to retroviral inhibitors. Most of these mutations work synergistically, but the biophysical basis behind their cooperation is not well understood. Our work addresses these important issues by bridging the gap between the statistical modeling of HIV protease subtype B sequences with the energetics of mutations involving charged amino acids by showing that electrostatic stability is intimately related to correlations. Moreover, we demonstrate that our statistical model has considerable predictive power and can be used to predict complex mutation patterns that have not yet been observed due to the finite sizes of the current sequence databases. In other words, as the database size increases, our model has the ability to predict the identities of the high probability mutations patterns, which are more likely to be observed. Knowing which currently unobserved mutations are more likely to be observed can be very advantageous in combating the disease.

Weak selection and protein evolution

The "nearly neutral" theory of molecular evolution proposes that many features of genomes arise from the interaction of three weak evolutionary forces: mutation, genetic drift, and natural selection acting at its limit of efficacy. Such forces generally have little impact on allele frequencies within populations from generation to generation but can have substantial effects on long-term evolution. The evolutionary dynamics of weakly selected mutations are highly sensitive to population size, and near neutrality was initially proposed as an adjustment to the neutral theory to account for general patterns in available protein and DNA variation data. Here, we review the motivation for the nearly neutral theory, discuss the structure of the model and its predictions, and evaluate current empirical support for interactions among weak evolutionary forces in protein evolution. Near neutrality may be a prevalent mode of evolution across a range of functional categories of mutations and taxa. However, multiple evolutionary mechanisms (including adaptive evolution, linked selection, changes in fitness-effect distributions, and weak selection) can often explain the same patterns of genome variation. Strong parameter sensitivity remains a limitation of the nearly neutral model, and we discuss concave fitness functions as a plausible underlying basis for weak selection.

Prediction of mutational tolerance in HIV-1 protease and reverse transcriptase using flexible backbone protein design

Predicting which mutations proteins tolerate while maintaining their structure and function has important applications for modeling fundamental properties of proteins and their evolution; it also drives progress in protein design. Here we develop a computational model to predict the tolerated sequence space of HIV-1 protease reachable by single mutations. We assess the model by comparison to the observed variability in more than 50,000 HIV-1 protease sequences, one of the most comprehensive datasets on tolerated sequence space. We then extend the model to a second protein, reverse transcriptase. The model integrates multiple structural and functional constraints acting on a protein and uses ensembles of protein conformations. We find the model correctly captures a considerable fraction of protease and reverse-transcriptase mutational tolerance and shows comparable accuracy using either experimentally determined or computationally generated structural ensembles. Predictions of tolerated sequence space afforded by the model provide insights into stability-function tradeoffs in the emergence of resistance mutations and into strengths and limitations of the computational model.

Many related protein sequences can be consistent with the structure and function of a given protein, suggesting that proteins may be quite robust to mutations. This tolerance to mutations is frequently exploited by pathogens. In particular, pathogens can rapidly evolve mutated proteins that have a new function - resistance against a therapeutic inhibitor - without abandoning other functions essential for the pathogen. This principle may also hold more generally: Proteins tolerant to mutational changes can more easily acquire new functions while maintaining their existing properties. The ability to predict the tolerance of proteins to mutation could thus help both to analyze the emergence of resistance mutations in pathogens and to engineer proteins with new functions. Here we develop a computational model to predict protein mutational tolerance towards point mutations accessible by single nucleotide changes, and validate it using two important pathogenic proteins and therapeutic targets: the protease and reverse transcriptase from HIV-1. The model provides insights into how resistance emerges and makes testable predictions on mutations that have not been seen yet. Similar models of mutational tolerance should be useful for characterizing and reengineering the functions of other proteins for which a three-dimensional structure is available.

Multidimensional epistasis and fitness landscapes in enzyme evolution

The conventional analysis of enzyme evolution is to regard one single salient feature as a measure of fitness, expressed in a milieu exposing the possible selective advantage at a given time and location. Given that a single protein may serve more than one function, fitness should be assessed in several dimensions. In the present study we have explored individual mutational steps leading to a triple-point-mutated human GST (glutathione transferase) A2-2 displaying enhanced activity with azathioprine. A total of eight alternative substrates were used to monitor the diverse evolutionary trajectories. The epistatic effects of the mutations on catalytic activity were variable in sign and magnitude and depended on the substrate used, showing that epistasis is a multidimensional quality. Evidently, the multidimensional fitness landscape can lead to alternative trajectories resulting in enzymes optimized for features other than the selectable markers relevant at the origin of the evolutionary process. In this manner the evolutionary response is robust and can adapt to changing environmental conditions.

Sequence-function-stability relationships in proteins from datasets of functionally annotated variants: the case of TEM β-lactamases

A dataset of TEM lactamase variants with different substrate and inhibition profiles was compiled and analyzed. Trends show that loops are the main evolvable regions in these enzymes, gradually accumulating mutations to generate increasingly complex functions. Notably, many mutations present in evolved enzymes are also found in simpler variants, probably originating functional promiscuity. Following a function-stability tradeoff, the increase in functional complexity driven by accumulation of mutations fosters the incorporation of other stability-restoring substitutions, although our analysis suggests they might not be as "global" as generally accepted and seem instead specific to different networks of protein sites. Finally, we show how this dataset can be used to model functional changes in TEMs based on the physicochemical properties of the amino acids.

Enhancing the promiscuous phosphotriesterase activity of a thermostable lactonase (GkaP) for the efficient degradation of organophosphate pesticides

The phosphotriesterase-like lactonase (PLL) enzymes in the amidohydrolase superfamily hydrolyze various lactones and exhibit latent phosphotriesterase activities. These enzymes serve as attractive templates for in vitro evolution of neurotoxic organophosphates (OPs) with hydrolytic capabilities that can be used as bioremediation tools. Here, a thermostable PLL from Geobacillus kaustophilus HTA426 (GkaP) was targeted for joint laboratory evolution with the aim of enhancing its catalytic efficiency against OP pesticides. By a combination of site saturation mutagenesis and whole-gene error-prone PCR approaches, several improved variants were isolated. The most active variant, 26A8C, accumulated eight amino acid substitutions and demonstrated a 232-fold improvement over the wild-type enzyme in reactivity (k(cat)/K(m)) for the OP pesticide ethyl-paraoxon. Concomitantly, this variant showed a 767-fold decrease in lactonase activity with δ-decanolactone, imparting a specificity switch of 1.8 × 10(5)-fold. 26A8C also exhibited high hydrolytic activities (19- to 497-fold) for several OP pesticides, including parathion, diazinon, and chlorpyrifos. Analysis of the mutagenesis sites on the GkaP structure revealed that most mutations are located in loop 8, which determines substrate specificity in the amidohydrolase superfamily. Molecular dynamics simulation shed light on why 26A8C lost its native lactonase activity and improved the promiscuous phosphotriesterase activity. These results permit us to obtain further insights into the divergent evolution of promiscuous enzymes and suggest that laboratory evolution of GkaP may lead to potential biological solutions for the efficient decontamination of neurotoxic OP compounds.

Intramolecular epistasis and the evolution of a new enzymatic function

Atrazine chlorohydrolase (AtzA) and its close relative melamine deaminase (TriA) differ by just nine amino acid substitutions but have distinct catalytic activities. Together, they offer an informative model system to study the molecular processes that underpin the emergence of new enzymatic function. Here we have constructed the potential evolutionary trajectories between AtzA and TriA, and characterized the catalytic activities and biophysical properties of the intermediates along those trajectories. The order in which the nine amino acid substitutions that separate the enzymes could be introduced to either enzyme, while maintaining significant catalytic activity, was dictated by epistatic interactions, principally between three amino acids within the active site: namely, S331C, N328D and F84L. The mechanistic basis for the epistatic relationships is consistent with a model for the catalytic mechanisms in which protonation is required for hydrolysis of melamine, but not atrazine.

Designing proteins from simple motifs: opportunities in Top-Down Symmetric Deconstruction

The purpose of this review is to describe the development of 'top-down' approaches to protein design. It will be argued that a diverse number of studies over the past decade, involving many investigators, and focused upon elucidating the role of symmetry in protein evolution and design, are converging into a novel top-down approach to protein design. Top-down design methodologies have successfully produced comparatively simple polypeptide 'building blocks' (typically comprising 40-60 amino acids) useful in generating complex protein architecture, and have produced compelling data in support of macro-evolutionary pathways of protein structure. Furthermore, a distillation of the experimental approaches utilized in such studies suggests the potential for method formalism, one that may accelerate future success in this field.

Enumerating pathways of proton abstraction based on a spatial and electrostatic analysis of residues in the catalytic site

The pathways of proton abstraction (PA), a key aspect of most catalytic reactions, is often controversial and highly debated. Ultrahigh-resolution diffraction studies, molecular dynamics, quantum mechanics and molecular mechanic simulations are often adopted to gain insights in the PA mechanisms in enzymes. These methods require expertise and effort to setup and can be computationally intensive. We present a push button methodology--Proton abstraction Simulation (PRISM)--to enumerate the possible pathways of PA in a protein with known 3D structure based on the spatial and electrostatic properties of residues in the proximity of a given nucleophilic residue. Proton movements are evaluated in the vicinity of this nucleophilic residue based on distances, potential differences, spatial channels and characteristics of the individual residues (polarity, acidic, basic, etc). Modulating these parameters eliminates their empirical nature and also might reveal pathways that originate from conformational changes. We have validated our method using serine proteases and concurred with the dichotomy in PA in Class A β-lactamases, both of which are hydrolases. The PA mechanism in a transferase has also been corroborated. The source code is made available at www.sanchak.com/prism.

Thermal instability of ΔF508 cystic fibrosis transmembrane conductance regulator (CFTR) channel function: protection by single suppressor mutations and inhibiting channel activity

Deletion of Phe508 from cystic fibrosis transmembrane conductance regulator (CFTR) results in a temperature-sensitive folding defect that impairs protein maturation and chloride channel function. Both of these adverse effects, however, can be mitigated to varying extents by second-site suppressor mutations. To better understand the impact of second-site mutations on channel function, we compared the thermal sensitivity of CFTR channels in Xenopus oocytes. CFTR-mediated conductance of oocytes expressing wt or ΔF508 CFTR was stable at 22 °C and increased at 28 °C, a temperature permissive for ΔF508 CFTR expression in mammalian cells. At 37 °C, however, CFTR-mediated conductance was further enhanced, whereas that due to ΔF508 CFTR channels decreased rapidly toward background, a phenomenon referred to here as "thermal inactivation." Thermal inactivation of ΔF508 was mitigated by each of five suppressor mutations, I539T, R553M, G550E, R555K, and R1070W, but each exerted unique effects on the severity of, and recovery from, thermal inactivation. Another mutation, K1250A, known to increase open probability (P(o)) of ΔF508 CFTR channels, exacerbated thermal inactivation. Application of potentiators known to increase P(o) of ΔF508 CFTR channels at room temperature failed to protect channels from inactivation at 37 °C and one, PG-01, actually exacerbated thermal inactivation. Unstimulated ΔF508CFTR channels or those inhibited by CFTR(inh)-172 were partially protected from thermal inactivation, suggesting a possible inverse relationship between thermal stability and gating transitions. Thermal stability of channel function and temperature-sensitive maturation of the mutant protein appear to reflect related, but distinct facets of the ΔF508 CFTR conformational defect, both of which must be addressed by effective therapeutic modalities.

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.

A measure of the promiscuity of proteins and characteristics of residues in the vicinity of the catalytic site that regulate promiscuity

Promiscuity, the basis for the evolution of new functions through 'tinkering' of residues in the vicinity of the catalytic site, is yet to be quantitatively defined. We present a computational method Promiscuity Indices Estimator (PROMISE)--based on signatures derived from the spatial and electrostatic properties of the catalytic residues, to estimate the promiscuity (PromIndex) of proteins with known active site residues and 3D structure. PromIndex reflects the number of different active site signatures that have congruent matches in close proximity of its native catalytic site, the quality of the matches and difference in the enzymatic activity. Promiscuity in proteins is observed to follow a lognormal distribution (μ = 0.28, σ = 1.1 reduced chi-square = 3.0E-5). The PROMISE predicted promiscuous functions in any protein can serve as the starting point for directed evolution experiments. PROMISE ranks carboxypeptidase A and ribonuclease A amongst the more promiscuous proteins. We have also investigated the properties of the residues in the vicinity of the catalytic site that regulates its promiscuity. Linear regression establishes a weak correlation (R(2)∼0.1) between certain properties of the residues (charge, polar, etc) in the neighborhood of the catalytic residues and PromIndex. A stronger relationship states that most proteins with high promiscuity have high percentages of charged and polar residues within a radius of 3 Å of the catalytic site, which is validated using one-tailed hypothesis tests (P-values∼0.05). Since it is known that these characteristics are key factors in catalysis, their relationship with the promiscuity index cross validates the methodology of PROMISE.