Conformational Tinkering Drives Evolution of a Promiscuous Activity through Indirect Mutational Effects

Reviewing the Structure-Function Paradigm in Polyglutamine Disorders: A Synergistic Perspective on Theoretical and Experimental Approaches

Polyglutamine (polyQ) disorders are a group of neurodegenerative diseases characterized by the excessive expansion of CAG (cytosine, adenine, guanine) repeats within host proteins. The quest to unravel the complex diseases mechanism has led researchers to adopt both theoretical and experimental methods, each offering unique insights into the underlying pathogenesis. This review emphasizes the significance of combining multiple approaches in the study of polyQ disorders, focusing on the structure-function correlations and the relevance of polyQ-related protein dynamics in neurodegeneration. By integrating computational/theoretical predictions with experimental observations, one can establish robust structure-function correlations, aiding in the identification of key molecular targets for therapeutic interventions. PolyQ proteins' dynamics, influenced by their length and interactions with other molecular partners, play a pivotal role in the polyQ-related pathogenic cascade. Moreover, conformational dynamics of polyQ proteins can trigger aggregation, leading to toxic assembles that hinder proper cellular homeostasis. Understanding these intricacies offers new avenues for therapeutic strategies by fine-tuning polyQ kinetics, in order to prevent and control disease progression. Last but not least, this review highlights the importance of integrating multidisciplinary efforts to advancing research in this field, bringing us closer to the ultimate goal of finding effective treatments against polyQ disorders.

Effects of Clinical Mutations in the Second Coordination Sphere and Remote Regions on the Catalytic Mechanism of Non-Heme Fe(II)/2-Oxoglutarate-Dependent Aspartyl Hydroxylase AspH

Aspartyl/asparaginyl hydroxylase (AspH) catalyzes the post-translational hydroxylations of vital human proteins, playing an essential role in maintaining their biological functions. Single-point mutations in the Second Coordination Sphere (SCS) and long-range (LR) residues of AspH have been linked to pathological conditions such as the ophthalmologic condition Traboulsi syndrome and chronic kidney disease (CKD). Although the clinical impacts of these mutations are established, there is a critical knowledge gap regarding their specific atomistic effects on the catalytic mechanism of AspH. In this study, we report integrated computational investigations on the potential mechanistic implications of four mutant forms of human AspH with clinical importance: R735W, R735Q, R688Q, and G434V. All the mutant forms exhibited altered binding interactions with the co-substrate 2-oxoglutarate (2OG) and the main substrate in the ferric-superoxo and ferryl complexes, which are critical for catalysis, compared to the wild-type (WT). Importantly, the mutations strongly influence the energetics of the frontier molecular orbitals (FMOs) and, thereby, the activation energies for the hydrogen atom transfer (HAT) step compared to the WT AspH. Insights from our study can contribute to enzyme engineering and the development of selective modulators for WT and mutants of AspH, ultimately aiding in treating cancers, Traboulsi syndrome and, CKD.

AlphaFold2 Can Predict Single-Mutation Effects

AlphaFold2 (AF) is a promising tool, but is it accurate enough to predict single mutation effects? Here, we report that the localized structural deformation between protein pairs differing by only 1-3 mutations-as measured by the effective strain-is correlated across 3901 experimental and AF-predicted structures. Furthermore, analysis of ∼11 000 proteins shows that the local structural change correlates with various phenotypic changes. These findings suggest that AF can predict the range and magnitude of single-mutation effects on average, and we propose a method to improve precision of AF predictions and to indicate when predictions are unreliable.

Conformational Tuning Shapes the Balance between Functional Promiscuity and Specialization in Paralogous Plasmodium Acyl-CoA Binding Proteins

Paralogous proteins confer enhanced fitness to organisms via complex sequence-conformation codes that shape functional divergence, specialization, or promiscuity. Here, we dissect the underlying mechanism of promiscuous binding versus partial subfunctionalization in paralogues by studying structurally identical acyl-CoA binding proteins (ACBPs) from Plasmodium falciparum that serve as promising drug targets due to their high expression during the protozoan proliferative phase. Combining spectroscopic measurements, solution NMR, SPR, and simulations on two of the paralogues, A16 and A749, we show that minor sequence differences shape nearly every local and global conformational feature. A749 displays a broader and heterogeneous native ensemble, weaker thermodynamic coupling and cooperativity, enhanced fluctuations, and a larger binding pocket volume compared to A16. Site-specific tryptophan probes signal a graded reduction in the sampling of substates in the holo form, which is particularly apparent in A749. The paralogues exhibit a spectrum of binding affinities to different acyl-CoAs with A749, the more promiscuous and hence the likely ancestor, binding 1000-fold stronger to lauroyl-CoA under physiological conditions. We thus demonstrate how minor sequence changes modulate the extent of long-range interactions and dynamics, effectively contributing to the molecular evolution of contrasting functional repertoires in paralogues.

Analysis of neutral mutational drift in an allosteric enzyme

Neutral mutational drift is an important source of biological diversity that remains underexploited in fundamental studies of protein biophysics. This study uses a synthetic transcriptional circuit to study neutral drift in protein tyrosine phosphatase 1B (PTP1B), a mammalian signaling enzyme for which conformational changes are rate limiting. Kinetic assays of purified mutants indicate that catalytic activity, rather than thermodynamic stability, guides enrichment under neutral drift, where neutral or mildly activating mutations can mitigate the effects of deleterious ones. In general, mutants show a moderate activity-stability tradeoff, an indication that minor improvements in the activity of PTP1B do not require concomitant losses in its stability. Multiplexed sequencing of large mutant pools suggests that substitutions at allosterically influential sites are purged under biological selection, which enriches for mutations located outside of the active site. Findings indicate that the positional dependence of neutral mutations within drifting populations can reveal the presence of allosteric networks and illustrate an approach for using synthetic transcriptional systems to explore these mutations in regulatory enzymes.

Decoupling of catalysis and transition state analog binding from mutations throughout a phosphatase revealed by high-throughput enzymology

Using high-throughput microfluidic enzyme kinetics (HT-MEK), we measured over 9,000 inhibition curves detailing impacts of 1,004 single-site mutations throughout the alkaline phosphatase PafA on binding affinity for two transition state analogs (TSAs), vanadate and tungstate. As predicted by catalytic models invoking transition state complementary, mutations to active site and active-site-contacting residues had highly similar impacts on catalysis and TSA binding. Unexpectedly, most mutations to more distal residues that reduced catalysis had little or no impact on TSA binding and many even increased tungstate affinity. These disparate effects can be accounted for by a model in which distal mutations alter the enzyme's conformational landscape, increasing the occupancy of microstates that are catalytically less effective but better able to accommodate larger transition state analogs. In support of this ensemble model, glycine substitutions (rather than valine) were more likely to increase tungstate affinity (but not more likely to impact catalysis), presumably due to increased conformational flexibility that allows previously disfavored microstates to increase in occupancy. These results indicate that residues throughout an enzyme provide specificity for the transition state and discriminate against analogs that are larger only by tenths of an Ångström. Thus, engineering enzymes that rival the most powerful natural enzymes will likely require consideration of distal residues that shape the enzyme's conformational landscape and fine-tune active-site residues. Biologically, the evolution of extensive communication between the active site and remote residues to aid catalysis may have provided the foundation for allostery to make it a highly evolvable trait.

Ultrahigh-Throughput Directed Evolution of a Metal-Free α/β-Hydrolase with a Cys-His-Asp Triad into an Efficient Phosphotriesterase

Finding new mechanistic solutions for biocatalytic challenges is key in the evolutionary adaptation of enzymes, as well as in devising new catalysts. The recent release of man-made substances into the environment provides a dynamic testing ground for observing biocatalytic innovation at play. Phosphate triesters, used as pesticides, have only recently been introduced into the environment, where they have no natural counterpart. Enzymes have rapidly evolved to hydrolyze phosphate triesters in response to this challenge, converging onto the same mechanistic solution, which requires bivalent cations as a cofactor for catalysis. In contrast, the previously identified metagenomic promiscuous hydrolase P91, a homologue of acetylcholinesterase, achieves slow phosphotriester hydrolysis mediated by a metal-independent Cys-His-Asp triad. Here, we probe the evolvability of this new catalytic motif by subjecting P91 to directed evolution. By combining a focused library approach with the ultrahigh throughput of droplet microfluidics, we increase P91's activity by a factor of ≈360 (to a k_cat/K_M of ≈7 × 10⁵ M^-1 s^-1) in only two rounds of evolution, rivaling the catalytic efficiencies of naturally evolved, metal-dependent phosphotriesterases. Unlike its homologue acetylcholinesterase, P91 does not suffer suicide inhibition; instead, fast dephosphorylation rates make the formation of the covalent adduct rather than its hydrolysis rate-limiting. This step is improved by directed evolution, with intermediate formation accelerated by 2 orders of magnitude. Combining focused, combinatorial libraries with the ultrahigh throughput of droplet microfluidics can be leveraged to identify and enhance mechanistic strategies that have not reached high efficiency in nature, resulting in alternative reagents with novel catalytic machineries.

How to Recruit a Promiscuous Enzyme to Serve a New Function

Promiscuous enzymes can be recruited to serve new functions when a genetic or environmental change makes catalysis of a novel reaction important for fitness or even survival. Subsequently, gene duplication and divergence can lead to evolution of an efficient and specialized new enzyme. Every organism likely has thousands of promiscuous enzyme activities that provide a vast reservoir of catalytic potential. However, much of this potential may not be accessible. We compiled kinetic parameters for promiscuous reactions catalyzed by 108 enzymes. The median value of k_cat/K_M is a very modest 31 M^-1 s^-1. Based upon the fluxes through metabolic pathways in E. coli, we estimate that many, if not most, promiscuous activities are too inefficient to impact fitness. However, mutations can elevate the level of an insufficient promiscuous activity by increasing enzyme expression, improving k_cat/K_M, or altering concentrations of the promiscuous and native substrates and allosteric regulators. Particularly in large bacterial populations, stochastic mutations may provide a viable pathway for recruitment of even inefficient promiscuous activities.

Logistic Regression-Guided Identification of Cofactor Specificity-Contributing Residues in Enzyme with Sequence Datasets Partitioned by Catalytic Properties

Changing the substrate/cofactor specificity of an enzyme requires multiple mutations at spatially adjacent positions around the substrate pocket. However, this is challenging when solely based on crystal structure information because enzymes undergo dynamic conformational changes during the reaction process. Herein, we proposed a method for estimating the contribution of each amino acid residue to substrate specificity by deploying a phylogenetic analysis with logistic regression. Since this method can estimate the candidate amino acids for mutation by ranking, it is readable and can be used in protein engineering. We demonstrated our concept using redox cofactor conversion of the Escherichia coli malic enzyme as a model, which still lacks crystal structure elucidation. The use of logistic regression with amino acid sequences classified by cofactor specificity showed that the NADP⁺-dependent malic enzyme completely switched cofactor specificity to NAD⁺ dependence without the need for a practical screening step. The model showed that surrounding residues made a greater contribution to cofactor specificity than those in the interior of the substrate pocket. These residues might be difficult to identify from crystal structure observations. We show that a highly accurate and inferential machine learning model was obtained using amino acid sequences of structurally homologous and functionally distinct enzymes as input data.

Distal Mutations Shape Substrate-Binding Sites during Evolution of a Metallo-Oxidase into a Laccase

Laccases are in increasing demand as innovative solutions in the biorefinery fields. Here, we combine mutagenesis with structural, kinetic, and in silico analyses to characterize the molecular features that cause the evolution of a hyperthermostable metallo-oxidase from the multicopper oxidase family into a laccase (k _cat 273 s^-1 for a bulky aromatic substrate). We show that six mutations scattered across the enzyme collectively modulate dynamics to improve the binding and catalysis of a bulky aromatic substrate. The replacement of residues during the early stages of evolution is a stepping stone for altering the shape and size of substrate-binding sites. Binding sites are then fine-tuned through high-order epistasis interactions by inserting distal mutations during later stages of evolution. Allosterically coupled, long-range dynamic networks favor catalytically competent conformational states that are more suitable for recognizing and stabilizing the aromatic substrate. This work provides mechanistic insight into enzymatic and evolutionary molecular mechanisms and spots the importance of iterative experimental and computational analyses to understand local-to-global changes.

Design of novel cyanovirin-N variants by modulation of binding dynamics through distal mutations

We develop integrated co-evolution and dynamic coupling (ICDC) approach to identify, mutate, and assess distal sites to modulate function. We validate the approach first by analyzing the existing mutational fitness data of TEM-1 β-lactamase and show that allosteric positions co-evolved and dynamically coupled with the active site significantly modulate function. We further apply ICDC approach to identify positions and their mutations that can modulate binding affinity in a lectin, cyanovirin-N (CV-N), that selectively binds to dimannose, and predict binding energies of its variants through Adaptive BP-Dock. Computational and experimental analyses reveal that binding enhancing mutants identified by ICDC impact the dynamics of the binding pocket, and show that rigidification of the binding residues compensates for the entropic cost of binding. This work suggests a mechanism by which distal mutations modulate function through dynamic allostery and provides a blueprint to identify candidates for mutagenesis in order to optimize protein function.

Second-Shell Amino Acid R266 Helps Determine N-Succinylamino Acid Racemase Reaction Specificity in Promiscuous N-Succinylamino Acid Racemase/o-Succinylbenzoate Synthase Enzymes

Catalytic promiscuity is the coincidental ability to catalyze nonbiological reactions in the same active site as the native biological reaction. Several lines of evidence show that catalytic promiscuity plays a role in the evolution of new enzyme functions. Thus, studying catalytic promiscuity can help identify structural features that predispose an enzyme to evolve new functions. This study identifies a potentially preadaptive residue in a promiscuous N-succinylamino acid racemase/o-succinylbenzoate synthase (NSAR/OSBS) enzyme from Amycolatopsis sp. T-1-60. This enzyme belongs to a branch of the OSBS family which includes many catalytically promiscuous NSAR/OSBS enzymes. R266 is conserved in all members of the NSAR/OSBS subfamily. However, the homologous position is usually hydrophobic in other OSBS subfamilies, whose enzymes lack NSAR activity. The second-shell amino acid R266 is close to the catalytic acid/base K263, but it does not contact the substrate, suggesting that R266 could affect the catalytic mechanism. Mutating R266 to glutamine in Amycolatopsis NSAR/OSBS profoundly reduces NSAR activity but moderately reduces OSBS activity. This is due to a 1000-fold decrease in the rate of proton exchange between the substrate and the general acid/base catalyst K263. This mutation is less deleterious for the OSBS reaction because K263 forms a cation-π interaction with the OSBS substrate and/or the intermediate, rather than acting as a general acid/base catalyst. Together, the data explain how R266 contributes to NSAR reaction specificity and was likely an essential preadaptation for the evolution of NSAR activity.

A hierarchy of coupling free energies underlie the thermodynamic and functional architecture of protein structures

Protein sequences and structures evolve by satisfying varied physical and biochemical constraints. This multi-level selection is enabled not just by the patterning of amino acids on the sequence, but also via coupling between residues in the native structure. Here, we employ an energetically detailed statistical mechanical model with millions of microstates to extract such long-range structural correlations, i.e. thermodynamic coupling free energies, from a diverse family of protein structures. We find that despite the intricate and anisotropic distribution of coupling patterns, the majority of residues (>70%) are only marginally coupled contributing to functional motions and catalysis. Physical origins of ‘sectors’, determinants of native ensemble heterogeneity in extant, ancient and designed proteins, and the basis for allostery emerge naturally from coupling free energies. The statistical framework highlights how evolutionary selection and optimization occur at the level of global interaction network for a given protein fold impacting folding, function, and allosteric outputs.

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Evolution of protein structures occurs at the level of global interaction network.

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More than 70% of the protein residues are weakly or marginally coupled.

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Functional ‘sector’ regions are a manifestation of marginal coupling.

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Coupling indices vary across the entire proteins in extant-ancient and natural-designed pairs.

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The proposed methodology can be used to understand allostery and epistasis.

Identification and Characterization of a New Quorum-Quenching N-acyl Homoserine Lactonase in the Plant Pathogen Erwinia amylovora

Quorum quenching (QQ) is the ability to interfere with bacterial cell to cell communication, known as quorum sensing (QS). QQ enzymes that degrade or modify acyl homoserine lactones (AHLs) have been attracting increasing interest as promising agents for inhibiting QS-mediated bacterial pathogenicity. Plant pathogens from the genus Erwinia cause diseases in several economically important crops. Fire blight is a devastating plant disease caused by Erwinia amylovora, affecting a wide range of host species within the Rosaceae and posing a major global threat for commercial apple and pear production. While QS has been described in Erwinia species, no AHL-degrading enzymes were identified and characterized. Here, phylogenetic analysis and structural modeling were applied to identify an AHL lactonase in E. amylovora (dubbed EaAiiA). Following recombinant expression and purification, the enzyme was biochemically characterized. EaAiiA lactonase activity was dependent on metal ions and effectively degraded AHLs with high catalytic efficiency. Its highest specific activity (k_cat/K_M value) was observed against one of the AHLs (3-oxo-C6-homoserine lactone) secreted from E. amylovora. Exogenous addition of the purified enzyme to cultures of E. amylovora reduced the formation of levan, a QS-regulated virulence factor, by 40% and the transcription level of the levansucrase-encoding gene by 55%. Furthermore, preincubation of E. amylovora cultures with EaAiiA inhibited the progress of fire blight symptoms in immature Pyrus communis fruits. These results demonstrate the ability of the identified enzyme from E. amylovora to act as a quorum-quenching lactonase.

Pervasive cooperative mutational effects on multiple catalytic enzyme traits emerge via long-range conformational dynamics

Multidimensional fitness landscapes provide insights into the molecular basis of laboratory and natural evolution. To date, such efforts usually focus on limited protein families and a single enzyme trait, with little concern about the relationship between protein epistasis and conformational dynamics. Here, we report a multiparametric fitness landscape for a cytochrome P450 monooxygenase that was engineered for the regio- and stereoselective hydroxylation of a steroid. We develop a computational program to automatically quantify non-additive effects among all possible mutational pathways, finding pervasive cooperative signs and magnitude epistasis on multiple catalytic traits. By using quantum mechanics and molecular dynamics simulations, we show that these effects are modulated by long-range interactions in loops, helices and β-strands that gate the substrate access channel allowing for optimal catalysis. Our work highlights the importance of conformational dynamics on epistasis in an enzyme involved in secondary metabolism and offers insights for engineering P450s.

Connecting conformational dynamics and epistasis has so far been limited to a few proteins and a single fitness trait. Here, the authors provide evidence of positive epistasis on multiple catalytic traits in the evolution and dynamics of engineered cytochrome P450 monooxygenase, offering insights for in silico protein design.

Influence of Disease-Causing Mutations on Protein Structural Networks

The interactions between residues in a protein tertiary structure can be studied effectively using the approach of protein structure network (PSN). A PSN is a node-edge representation of the structure with nodes representing residues and interactions between residues represented by edges. In this study, we have employed weighted PSNs to understand the influence of disease-causing mutations on proteins of known 3D structures. We have used manually curated information on disease mutations from UniProtKB/Swiss-Prot and their corresponding protein structures of wildtype and disease variant from the protein data bank. The PSNs of the wildtype and disease-causing mutant are compared to analyse variation of global and local dissimilarity in the overall network and at specific sites. We study how a mutation at a given site can affect the structural network at a distant site which may be involved in the function of the protein. We have discussed specific examples of the disease cases where the protein structure undergoes limited structural divergence in their backbone but have large dissimilarity in their all atom networks and vice versa, wherein large conformational alterations are observed while retaining overall network. We analyse the effect of variation of network parameters that characterize alteration of function or stability.

Biomolecular QM/MM Simulations: What Are Some of the "Burning Issues"?

QM/MM simulations have become an indispensable tool in many chemical and biochemical investigations. Considering the tremendous degree of success, including recognition by a 2013 Nobel Prize in Chemistry, are there still "burning challenges" in QM/MM methods, especially for biomolecular systems? In this short Perspective, we discuss several issues that we believe greatly impact the robustness and quantitative applicability of QM/MM simulations to many, if not all, biomolecules. We highlight these issues with observations and relevant advances from recent studies in our group and others in the field. Despite such limited scope, we hope the discussions are of general interest and will stimulate additional developments that help push the field forward in meaningful directions.

Evolution of new enzymes by gene duplication and divergence

Thousands of new metabolic and regulatory enzymes have evolved by gene duplication and divergence since the dawn of life. New enzyme activities often originate from promiscuous secondary activities that have become important for fitness due to a change in the environment or a mutation. Mutations that make a promiscuous activity physiologically relevant can occur in the gene encoding the promiscuous enzyme itself, but can also occur elsewhere, resulting in increased expression of the enzyme or decreased competition between the native and novel substrates for the active site. If a newly useful activity is inefficient, gene duplication/amplification will set the stage for divergence of a new enzyme. Even a few mutations can increase the efficiency of a new activity by orders of magnitude. As efficiency increases, amplified gene arrays will shrink to provide two alleles, one encoding the original enzyme and one encoding the new enzyme. Ultimately, genomic rearrangements eliminate co-amplified genes and move newly evolved paralogs to a distant region of the genome.

A mechanistic view of enzyme evolution

New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes to enhance their activities? Can we infer general mechanisms that are common to most enzymes, or does each enzyme require a unique optimization process? The ability to predict the location and type of mutations necessary to enhance an enzyme's activity is critical to protein engineering and rational design. In this review, via the detailed examination of recent studies that have shed new light on the molecular changes underlying the optimization of enzyme function, we provide a mechanistic perspective of enzyme evolution. We first present a global survey of the prevalence of activity-enhancing mutations and their distribution within protein structures. We then delve into the molecular solutions that mediate functional optimization, specifically highlighting several common mechanisms that have been observed across multiple examples. As distinct protein sequences encounter different evolutionary bottlenecks, different mechanisms are likely to emerge along evolutionary trajectories toward improved function. Identifying the specific mechanism(s) that need to be improved upon, and tailoring our engineering efforts to each sequence, may considerably improve our chances to succeed in generating highly efficient catalysts in the future.

Harnessing Conformational Plasticity to Generate Designer Enzymes

Recent years have witnessed an explosion of interest in understanding the role of conformational dynamics both in the evolution of new enzymatic activities from existing enzymes and in facilitating the emergence of enzymatic activity de novo on scaffolds that were previously non-catalytic. There are also an increasing number of examples in the literature of targeted engineering of conformational dynamics being successfully used to alter enzyme selectivity and activity. Despite the obvious importance of conformational dynamics to both enzyme function and evolvability, many (although not all) computational design approaches still focus either on pure sequence-based approaches or on using structures with limited flexibility to guide the design. However, there exist a wide variety of computational approaches that can be (re)purposed to introduce conformational dynamics as a key consideration in the design process. Coupled with laboratory evolution and more conventional existing sequence- and structure-based approaches, these techniques provide powerful tools for greatly expanding the protein engineering toolkit. This Perspective provides an overview of evolutionary studies that have dissected the role of conformational dynamics in facilitating the emergence of novel enzymes, as well as advances in computational approaches that allow one to target conformational dynamics as part of enzyme design. Harnessing conformational dynamics in engineering studies is a powerful paradigm with which to engineer the next generation of designer biocatalysts.

The Role of Conformational Dynamics and Allostery in Modulating Protein Evolution

Advances in sequencing techniques and statistical methods have made it possible not only to predict sequences of ancestral proteins but also to identify thousands of mutations in the human exome, some of which are disease associated. These developments have motivated numerous theories and raised many questions regarding the fundamental principles behind protein evolution, which have been traditionally investigated horizontally using the tip of the phylogenetic tree through comparative studies of extant proteins within a family. In this article, we review a vertical comparison of the modern and resurrected ancestral proteins. We focus mainly on the dynamical properties responsible for a protein's ability to adapt new functions in response to environmental changes. Using the Dynamic Flexibility Index and the Dynamic Coupling Index to quantify the relative flexibility and dynamic coupling at a site-specific, single-amino-acid level, we provide evidence that the migration of hinges, which are often functionally critical rigid sites, is a mechanism through which proteins can rapidly evolve. Additionally, we show that disease-associated mutations in proteins often result in flexibility changes even at positions distal from mutational sites, particularly in the modulation of active site dynamics.

Selective inhibition of APOBEC3 enzymes by single-stranded DNAs containing 2'-deoxyzebularine

To restrict pathogens, in a normal human cell, APOBEC3 enzymes mutate cytosine to uracil in foreign single-stranded DNAs. However, in cancer cells, APOBEC3B (one of seven APOBEC3 enzymes) has been identified as the primary source of genetic mutations. As such, APOBEC3B promotes evolution and progression of cancers and leads to development of drug resistance in multiple cancers. As APOBEC3B is a non-essential protein, its inhibition can be used to suppress emergence of drug resistance in existing anti-cancer therapies. Because of the vital role of APOBEC3 enzymes in innate immunity, selective inhibitors targeting only APOBEC3B are required. Here, we use the discriminative properties of wild-type APOBEC3A, APOBEC3B and APOBEC3G to deaminate different cytosines in the CCC-recognition motif in order to best place the cytidine analogue 2'-deoxyzebularine (dZ) in the CCC-motif. Using several APOBEC3 variants that mimic deamination patterns of wild-type enzymes, we demonstrate that selective inhibition of APOBEC3B in preference to other APOBEC3 constructs is feasible for the dZCC motif. This work is an important step towards development of in vivo tools to inhibit APOBEC3 enzymes in living cells by using short, chemically modified oligonucleotides.

Carboxylic Ester Hydrolases in Bacteria: Active Site, Structure, Function and Application

Carboxylic ester hydrolases (CEHs), which catalyze the hydrolysis of carboxylic esters to produce alcohol and acid, are identified in three domains of life. In the Protein Data Bank (PDB), 136 crystal structures of bacterial CEHs (424 PDB codes) from 52 genera and metagenome have been reported. In this review, we categorize these structures based on catalytic machinery, structure and substrate specificity to provide a comprehensive understanding of the bacterial CEHs. CEHs use Ser, Asp or water as a nucleophile to drive diverse catalytic machinery. The α/β/α sandwich architecture is most frequently found in CEHs, but 3-solenoid, β-barrel, up-down bundle, α/β/β/α 4-layer sandwich, 6 or 7 propeller and α/β barrel architectures are also found in these CEHs. Most are substrate-specific to various esters with types of head group and lengths of the acyl chain, but some CEHs exhibit peptidase or lactamase activities. CEHs are widely used in industrial applications, and are the objects of research in structure- or mutation-based protein engineering. Structural studies of CEHs are still necessary for understanding their biological roles, identifying their structure-based functions and structure-based engineering and their potential industrial applications.

Active site residue identity regulates cleavage preference of LAGLIDADG homing endonucleases

LAGLIDADG homing endonucleases (meganucleases) are site-specific mobile endonucleases that can be adapted for genome-editing applications. However, one problem when reprogramming meganucleases on non-native substrates is indirect readout of DNA shape and flexibility at the central 4 bases where cleavage occurs. To understand how the meganuclease active site regulates DNA cleavage, we used functional selections and deep sequencing to profile the fitness landscape of 1600 I-LtrI and I-OnuI active site variants individually challenged with 67 substrates with central 4 base substitutions. The wild-type active site was not optimal for cleavage on many substrates, including the native I-LtrI and I-OnuI targets. Novel combinations of active site residues not observed in known meganucleases supported activity on substrates poorly cleaved by the wild-type enzymes. Strikingly, combinations of E or D substitutions in the two metal-binding residues greatly influenced cleavage activity, and E184D variants had a broadened cleavage profile. Analyses of I-LtrI E184D and the wild-type proteins co-crystallized with the non-cognate AACC central 4 sequence revealed structural differences that correlated with kinetic constants for cleavage of individual DNA strands. Optimizing meganuclease active sites to enhance cleavage of non-native central 4 target sites is a straightforward addition to engineering workflows that will expand genome-editing applications.

Exploring the sequence, function, and evolutionary space of protein superfamilies using sequence similarity networks and phylogenetic reconstructions

Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions by enabling the observation and investigation of complex sequence-structure-function and evolutionary relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) and phylogenetic reconstructions to map the functional divergence and evolutionary history of protein superfamilies. We exemplify this approach using the nitroreductase (NTR) flavoenzyme superfamily, demonstrating that SSN investigations can provide a rapid and effective means to classify groups of proteins, expose sequence similarity relationships across the global scale of a protein superfamily, and efficiently support detailed phylogenetic analyses. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes, their evolution, and their associated physiological roles.

Protein engineering: the potential of remote mutations

Engineered proteins, especially enzymes, are now commonly used in many industries owing to their catalytic power, specific binding of ligands, and properties as materials and food additives. As the number of potential uses for engineered proteins has increased, the interest in engineering or designing proteins to have greater stability, activity and specificity has increased in turn. With any rational engineering or design pursuit, the success of these endeavours relies on our fundamental understanding of the systems themselves; in the case of proteins, their structure-dynamics-function relationships. Proteins are most commonly rationally engineered by targeting the residues that we understand to be functionally important, such as enzyme active sites or ligand-binding sites. This means that the majority of the protein, i.e. regions remote from the active- or ligand-binding site, is often ignored. However, there is a growing body of literature that reports on, and rationalises, the successful engineering of proteins at remote sites. This minireview will discuss the current state of the art in protein engineering, with a particular focus on engineering regions that are remote from active- or ligand-binding sites. As the use of protein technologies expands, exploiting the potential improvements made possible through modifying remote regions will become vital if we are to realise the full potential of protein engineering and design.

Cryptic genetic variation shapes the adaptive evolutionary potential of enzymes

Genetic variation among orthologous proteins can cause cryptic phenotypic properties that only manifest in changing environments. Such variation may impact the evolvability of proteins, but the underlying molecular basis remains unclear. Here, we performed comparative directed evolution of four orthologous metallo-β-lactamases toward a new function and found that different starting genotypes evolved to distinct evolutionary outcomes. Despite a low initial fitness, one ortholog reached a significantly higher fitness plateau than its counterparts, via increasing catalytic activity. By contrast, the ortholog with the highest initial activity evolved to a less-optimal and phenotypically distinct outcome through changes in expression, oligomerization and activity. We show how cryptic molecular properties and conformational variation of active site residues in the initial genotypes cause epistasis, that could lead to distinct evolutionary outcomes. Our work highlights the importance of understanding the molecular details that connect genetic variation to protein function to improve the prediction of protein evolution.

Synergistic effects of functionally distinct substitutions in β-lactamase variants shed light on the evolution of bacterial drug resistance

The CTX-M β-lactamases have emerged as the most widespread extended-spectrum β-lactamases (ESBLs) in Gram-negative bacteria. These enzymes rapidly hydrolyze cefotaxime, but not the related cephalosporin, ceftazidime. ESBL variants have evolved, however, that provide enhanced ceftazidime resistance. We show here that a natural variant at a nonactive site, i.e. second-shell residue N106S, enhances enzyme stability but reduces catalytic efficiency for cefotaxime and ceftazidime and decreases resistance levels. However, when the N106S variant was combined with an active-site variant, D240G, that enhances enzyme catalytic efficiency, but decreases stability, the resultant double mutant exhibited higher resistance levels than predicted on the basis of the phenotypes of each variant. We found that this epistasis is due to compensatory effects, whereby increased stability provided by N106S overrides its cost of decreased catalytic activity. X-ray structures of the variant enzymes in complex with cefotaxime revealed conformational changes in the active-site loop spanning residues 103-106 that were caused by the N106S substitution and relieve steric strain to stabilize the enzyme, but also alter contacts with cefotaxime and thereby reduce catalytic activity. We noted that the 103-106 loop conformation in the N106S-containing variants is different from that of WT CTX-M but nearly identical to that of the non-ESBL, TEM-1 β-lactamase, having a serine at the 106 position. Therefore, residue 106 may serve as a "switch" that toggles the conformations of the 103-106 loop. When it is serine, the loop is in the non-ESBL, TEM-like conformation, and when it is asparagine, the loop is in a CTX-M-like, cefotaximase-favorable conformation.

Modulation of allosteric coupling by mutations: from protein dynamics and packing to altered native ensembles and function

A large body of work has gone into understanding the effect of mutations on protein structure and function. Conventional treatments have involved quantifying the change in stability, activity and relaxation rates of the mutants with respect to the wild-type protein. However, it is now becoming increasingly apparent that mutational perturbations consistently modulate the packing and dynamics of a significant fraction of protein residues, even those that are located >10–15 Å from the mutated site. Such long-range modulation of protein features can distinctly tune protein stability and the native conformational ensemble contributing to allosteric modulation of function. In this review, I summarize a series of experimental and computational observations that highlight the incredibly pliable nature of proteins and their response to mutational perturbations manifested via the intra-protein interaction network. I highlight how an intimate understanding of mutational effects could pave the way for integrating stability, folding, cooperativity and even allostery within a single physical framework.

Revealing Unexplored Sequence-Function Space Using Sequence Similarity Networks

The rapidly expanding number of protein sequences found in public databases can improve our understanding of how protein functions evolve. However, our current knowledge of protein function likely represents a small fraction of the diverse repertoire that exists in nature. Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions through the observation and investigation of the complex sequence-structure-function relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) to identify previously unexplored sequence and function space. We exemplify this approach using the nitroreductase (NTR) superfamily. We demonstrate that SSN investigations can provide a rapid and effective means to classify groups of proteins, therefore exposing experimentally unexplored sequences that may exhibit novel functionality. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes and their associated physiological roles.

On the networked architecture of genotype spaces and its critical effects on molecular evolution

Evolutionary dynamics is often viewed as a subtle process of change accumulation that causes a divergence among organisms and their genomes. However, this interpretation is an inheritance of a gradualistic view that has been challenged at the macroevolutionary, ecological and molecular level. Actually, when the complex architecture of genotype spaces is taken into account, the evolutionary dynamics of molecular populations becomes intrinsically non-uniform, sharing deep qualitative and quantitative similarities with slowly driven physical systems: nonlinear responses analogous to critical transitions, sudden state changes or hysteresis, among others. Furthermore, the phenotypic plasticity inherent to genotypes transforms classical fitness landscapes into multiscapes where adaptation in response to an environmental change may be very fast. The quantitative nature of adaptive molecular processes is deeply dependent on a network-of-networks multilayered structure of the map from genotype to function that we begin to unveil.

Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1

The high-energy sulfate donor 3′-phosphoadenosine-5′-phosphosulfate (PAPS), generated by human PAPS synthase isoforms PAPSS1 and PAPSS2, is required for all human sulfation pathways. Sulfotransferase SULT2A1 uses PAPS for sulfation of the androgen precursor dehydroepiandrosterone (DHEA), thereby reducing downstream activation of DHEA to active androgens. Human PAPSS2 mutations manifest with undetectable DHEA sulfate, androgen excess, and metabolic disease, suggesting that ubiquitous PAPSS1 cannot compensate for deficient PAPSS2 in supporting DHEA sulfation. In knockdown studies in human adrenocortical NCI-H295R1 cells, we found that PAPSS2, but not PAPSS1, is required for efficient DHEA sulfation. Specific APS kinase activity, the rate-limiting step in PAPS biosynthesis, did not differ between PAPSS1 and PAPSS2. Co-expression of cytoplasmic SULT2A1 with a cytoplasmic PAPSS2 variant supported DHEA sulfation more efficiently than co-expression with nuclear PAPSS2 or nuclear/cytosolic PAPSS1. Proximity ligation assays revealed protein–protein interactions between SULT2A1 and PAPSS2 and, to a lesser extent, PAPSS1. Molecular docking studies showed a putative binding site for SULT2A1 within the PAPSS2 APS kinase domain. Energy-dependent scoring of docking solutions identified the interaction as specific for the PAPSS2 and SULT2A1 isoforms. These findings elucidate the mechanistic basis for the selective requirement for PAPSS2 in human DHEA sulfation.

Some Surprising Implications of NMR-directed Simulations of Substrate Recognition and Binding by Cytochrome P450cam (CYP101A1)

Cytochrome P450_cam (CYP101A1) catalyzes the stereospecific 5-exo hydroxylation of d-camphor by molecular oxygen. Previously, residual dipolar couplings measured for backbone amide ¹H-¹⁵N correlations in both substrate-free and bound forms of CYP101A1 were used as restraints in soft annealing molecular dynamic simulations in order to identify average conformations of the enzyme with and without substrate bound. Multiple substrate-dependent conformational changes remote from the enzyme active site were identified, and site-directed mutagenesis and activity assays confirmed the importance of these changes in substrate recognition. The current work makes use of perturbation response scanning (PRS) and umbrella sampling molecular dynamic of the residual dipolar coupling-derived CYP101A1 structures to probe the roles of remote structural features in enforcing the regio- and stereospecific nature of the hydroxylation reaction catalyzed by CYP101A1. An improper dihedral angle Ψ was defined and used to maintain substrate orientation in the CYP101A1 active site, and it was observed that different values of Ψ result in different PRS response maps. Umbrella sampling methods show that the free energy of the system is sensitive to Ψ, and bound substrate forms an important mechanical link in the transmission of mechanical coupling through the enzyme structure. Finally, a qualitative approach to interpreting PRS maps in terms of the roles of secondary structural features is proposed.

Understanding enzyme function evolution from a computational perspective

In this review, we will explore recent computational approaches to understand enzyme evolution from the perspective of protein structure, dynamics and promiscuity. We will present quantitative methods to measure the size of evolutionary steps within a structural domain, allowing the correlation between change in substrate and domain structure to be assessed, and giving insights into the evolvability of different domains in terms of the number, types and sizes of evolutionary steps observed. These approaches will help to understand the evolution of new catalytic and non-catalytic functionality in response to environmental demands, showing potential to guide de novoenzyme design and directed evolution experiments.

Single-mutation fitness landscapes for an enzyme on multiple substrates reveal specificity is globally encoded

Our lack of total understanding of the intricacies of how enzymes behave has constrained our ability to robustly engineer substrate specificity. Furthermore, the mechanisms of natural evolution leading to improved or novel substrate specificities are not wholly defined. Here we generate near-comprehensive single-mutation fitness landscapes comprising >96.3% of all possible single nonsynonymous mutations for hydrolysis activity of an amidase expressed in E. coli with three different substrates. For all three selections, we find that the distribution of beneficial mutations can be described as exponential, supporting a current hypothesis for adaptive molecular evolution. Beneficial mutations in one selection have essentially no correlation with fitness for other selections and are dispersed throughout the protein sequence and structure. Our results further demonstrate the dependence of local fitness landscapes on substrate identity and provide an example of globally distributed sequence-specificity determinants for an enzyme.

Systematically understanding the sequence determinants to substrate specificity for enzymes has implications in areas from evolutionary biology to biocatalysis. Here, Whitehead and colleagues generate and analyse near-comprehensive single-mutation fitness landscapes for an amidase with three different substrates.

Constrained evolution of a bispecific enzyme: lessons for biocatalyst design

Analysis of the natural evolution of bispecificity in triazine hydrolase highlights the importance of epistasis in protein engineering and evolution.

Evolutionary studies of ligand binding sites in proteins

Biological processes at their most fundamental molecular aspects are defined by molecular interactions with ligand-protein interactions in particular at the core of cellular functions such as metabolism and signalling. Divergent and convergent processes shape the evolution of ligand binding sites. The competition between similar ligands and binding sites across protein families create evolutionary pressures that affect the specificity and selectivity of interactions. This short review showcases recent studies of the evolution of ligand binding-sites and methods used to detect binding-site similarities.