Activation Free Energy, Substrate Binding Free Energy, and Enzyme Efficiency Fall in a Very Narrow Range of Values for Most Enzymes

Unraveling Copper Exchange in the Atox1-Cu(I)-Mnk1 Heterodimer: A Simulation Approach

Copper, an essential metal for various cellular processes, requires tight regulation to prevent cytotoxicity. Intracellular pathways crucial for maintaining optimal copper levels involve soluble and membrane transporters, namely, metallochaperones and P-type ATPases, respectively. In this study, we used a simulation workflow based on free-energy perturbation (FEP) theory and parallel bias metadynamics (PBMetaD) to predict the Cu(I) exchange mechanism between the human Cu(I) chaperone, Atox1, and one of its two physiological partners, ATP7A. ATP7A, also known as the Menkes disease protein, is a transmembrane protein and one of the main copper-transporting ATPases. It pumps copper into the trans-Golgi network for the maturation of cuproenzymes and is also essential for the efflux of excess copper across the plasma membrane. In this analysis, we utilized the nuclear magnetic resonance (NMR) structure of the Cu(I)-mediated complex between Atox1 and the first soluble domain of the Menkes protein (Mnk1) as a starting point. Independent free-energy simulations were conducted to investigate the dissociation of both Atox1 and Mnk1. The calculations revealed that the two dissociations require free energy values of 6.3 and 6.2 kcal/mol, respectively, following a stepwise dissociation mechanism.

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

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

Lipase A from Bacillus subtilis: Substrate Binding, Conformational Dynamics, and Signatures of a Lid

Protein-ligand binding studies are crucial for understanding the molecular basis of biological processes and for further advancing industrial biocatalysis and drug discovery. Using computational modeling and molecular dynamics simulations, we investigated the binding of a butyrate ester substrate to the lipase A (LipA) enzyme of Bacillus subtilis. Besides obtaining a close agreement of the binding free energy with the experimental value, the study reveals a remarkable reorganization of the catalytic triad upon substrate binding, leading to increased essential hydrogen bond populations. The investigation shows the distortion of the oxyanion hole in both the substrate-bound and unbound states of LipA and highlights the strengthening of the same in the tetrahedral intermediate complex. Principal component analysis of the unbound ensemble reveals the dominant motion in LipA to be the movement of Loop-1 (Tyr129-Arg142) between two states that cover and uncover the active site, mirroring that of a lid prevalent in several lipases. This lid-like motion of Loop-1 is also supported by its tendency to spontaneously open up at an oil-water interface. Overall, this study provides valuable insights into the impact of substrate binding on the structure, flexibility, and conformational dynamics of the LipA enzyme.

Promiscuous Yet Specific: A Methionine-Aromatic Interaction Drives the Reaction Scope of the Family 1 Glycosyltransferase GmUGT88E3 from Soybean

Family 1 glycosyltransferases (GT1s, UGTs) catalyze the regioselective glycosylation of natural products in a single step. We identified GmUGT88E3 as a particularly promising biocatalyst able to produce a variety of pure, single glycosidic products from polyphenols with high chemical yields. We investigated this particularly desirable duality toward specificity, i.e., promiscuous toward acceptors while regiospecific. Using high-field NMR, kinetic characterization, molecular dynamics simulations, and mutagenesis studies, we uncovered that the main molecular determinant of GmUGT88E3 specificity is a methionine-aromatic bridge, an interaction often present in protein structures but never reported for enzyme-substrate interactions. Here, mutating Met127 led to inactive proteins or 100-fold reduced activity.

Mutexa: A Computational Ecosystem for Intelligent Protein Engineering

Protein engineering holds immense promise in shaping the future of biomedicine and biotechnology. This Review focuses on our ongoing development of Mutexa, a computational ecosystem designed to enable "intelligent protein engineering". In this vision, researchers will seamlessly acquire sequences of protein variants with desired functions as biocatalysts, therapeutic peptides, and diagnostic proteins through a finely-tuned computational machine, akin to Amazon Alexa's role as a versatile virtual assistant. The technical foundation of Mutexa has been established through the development of a database that combines and relates enzyme structures and their respective functions (e.g., IntEnzyDB), workflow software packages that enable high-throughput protein modeling (e.g., EnzyHTP and LassoHTP), and scoring functions that map the sequence-structure-function relationship of proteins (e.g., EnzyKR and DeepLasso). We will showcase the applications of these tools in benchmarking the convergence conditions of enzyme functional descriptors across mutants, investigating protein electrostatics and cavity distributions in SAM-dependent methyltransferases, and understanding the role of nonelectrostatic dynamic effects in enzyme catalysis. Finally, we will conclude by addressing the future steps and fundamental challenges in our endeavor to develop new Mutexa applications that assist the identification of beneficial mutants in protein engineering.

High-throughput computational investigation of protein electrostatics and cavity for SAM-dependent methyltransferases

S-adenosyl methionine (SAM)-dependent methyl transferases (MTases) are a ubiquitous class of enzymes catalyzing dozens of essential life processes. Despite targeting a large space of substrates with diverse intrinsic reactivity, SAM MTases have similar catalytic efficiency. While understanding of MTase mechanism has grown tremendously through the integration of structural characterization, kinetic assays, and multiscale simulations, it remains elusive how these enzymes have evolved to fit the diverse chemical needs of their respective substrates. In this work, we performed a high-throughput molecular modeling analysis of 91 SAM MTases to better understand how their properties (i.e., electric field [EF] strength and active site volumes) help achieve similar catalytic efficiency toward substrates of different reactivity. We found that EF strengths have largely adjusted to make the target atom a better methyl acceptor. For MTases that target RNA/DNA and histone proteins, our results suggest that EF strength accommodates formal hybridization state and variation in cavity volume trends with diversity of substrate classes. Metal ions in SAM MTases contribute negatively to EF strength for methyl donation and enzyme scaffolds tend to offset these contributions.

Behavior of enzymes under high pressure in food processing: mechanisms, applications, and developments

High pressure processing (HPP) offers the benefits of safety, uniformity, energy-efficient, and low waste, which is widely applied for microbial inactivation and shelf-life extension for foods. Over the past forty years, HPP has been extensively researched in the food industry, enabling the inactivation or activation of different enzymes in future food by altering their molecular structure and active site conformation. Such activation or inactivation of enzymes effectively hinders the spoilage of food and the production of beneficial substances, which is crucial for improving food quality. This paper reviews the mechanism in which high pressure affects the stability and activity of enzymes, concludes the roles of key enzymes in the future food processed using high pressure technologies. Moreover, we discuss the application of modified enzymes based on high pressure, providing insights into the future direction of enzyme evolution under complex food processing conditions (e.g. high temperature, high pressure, high shear, and multiple elements). Finally, we conclude with prospects of high pressure technology and research directions in the future. Although HPP has shown positive effects in improving the future food quality, there is still a pressing need to develop new and effective combined processing methods, upgrade processing modes, and promote sustainable lifestyles.

Protein-Glutaminase Engineering Based on Isothermal Compressibility Perturbation for Enhanced Modification of Soy Protein Isolate

Protein-glutaminase plays a significant role in future food (e.g., plant-based meat) processing as a result of its ability to improve the solubility, foaming, emulsifying, and gel properties of plant-based proteins. However, poor stability, activity, high pressure, and high shear processing environments hinder its application. Therefore, we developed an application-oriented method isothermal compressibility perturbation engineering strategy to improve enzyme performance by simulating the high-pressure environment. The best variant with remarkable improvement in specific activity and half-time, N16M/Q21H/T113E, exhibited a 4.28-fold increase compared to the wild type in specific activity (117.18 units/mg) and a 1.23-fold increase in half-time (472 min), as one of the highest comprehensive performances ever reported. The solubility of the soy protein isolate deaminated by the N16M/Q21H/T113E mutant was 55.74% higher than that deaminated by the wild type, with a tinier particle size and coarser texture. Overall, this strategy has the potential to improve the functional performance of enzymes under complex food processing conditions.

Glucosylation mechanism of resveratrol through the mutant Q345F sucrose phosphorylase from the organism Bifidobacterium adolescentis: a computational study

Mainly due to their great antioxidant, anti-inflammatory and anticancer capacities, natural polyphenolic compounds have many properties with important applications in the food, cosmetic and pharmaceutical industries. Unfortunately, these molecules have very low water solubility and bioavailability. Glucosylation of polyphenols is an excellent alternative to overcome these drawbacks. Specifically, for the natural polyphenol resveratrol this process is very inefficiently performed by the native enzyme sucrose phosphorylase (BaSP) from the organism Bifidobacterium adolescentis (4%). However, the Q345F point mutation of the sucrose phosphorylase (BaSP Q345F) has been shown to achieve 97% monoglucosylation for the same substrate and the mechanism is still unknown. This report presents an analysis of MD simulations performed with the BaSP Q345F and BaSP systems in complex with resveratrol monoglucoside, followed by a study of the transglucosylation reaction of the mutant enzyme BaSP Q345F with resveratrol through the QM/MM hybrid method. With respect to the MD simulations, both protein structures showed greater similarity to the phosphate-binding conformation, and a larger active site and conformational changes in certain structures were found for the mutant system compared with the native enzyme; all this is in agreement with experimental data. With regard to the QM/MM calculations, the structure of an oxocarbenium ion-like transition state and the minimum energy adiabatic path (MEP) that connects the reactants with the products were obtained with a 20.3 kcal mol^-1 energy barrier, which fits within the known experimental range for this type of enzyme. Finally, the analyses performed along the MEP suggest a concerted but asynchronous mechanism. In particular, they show that the interactions involving the residues of the catalytic triad (Asp¹⁹², Glu²³², and Asp²⁹⁰) together with two water molecules at the active site strongly contribute to the stabilization of the transition state. The understanding of this glucosylation mechanism of the polyphenol resveratrol carried out by the mutant sucrose phosphorylase enzyme presented in this work could serve as the basis for subsequent studies on related carbohydrate-active enzymes.

The chemistry of snake venom and its medicinal potential

The fascination and fear of snakes dates back to time immemorial, with the first scientific treatise on snakebite envenoming, the Brooklyn Medical Papyrus, dating from ancient Egypt. Owing to their lethality, snakes have often been associated with images of perfidy, treachery and death. However, snakes did not always have such negative connotations. The curative capacity of venom has been known since antiquity, also making the snake a symbol of pharmacy and medicine. Today, there is renewed interest in pursuing snake-venom-based therapies. This Review focuses on the chemistry of snake venom and the potential for venom to be exploited for medicinal purposes in the development of drugs. The mixture of toxins that constitute snake venom is examined, focusing on the molecular structure, chemical reactivity and target recognition of the most bioactive toxins, from which bioactive drugs might be developed. The design and working mechanisms of snake-venom-derived drugs are illustrated, and the strategies by which toxins are transformed into therapeutics are analysed. Finally, the challenges in realizing the immense curative potential of snake venom are discussed, and chemical strategies by which a plethora of new drugs could be derived from snake venom are proposed.

Sabatier Principle for Rationalizing Enzymatic Hydrolysis of a Synthetic Polyester

Interfacial enzyme reactions are common in Nature and in industrial settings, including the enzymatic deconstruction of poly(ethylene terephthalate) (PET) waste. Kinetic descriptions of PET hydrolases are necessary for both comparative analyses, discussions of structure-function relations and rational optimization of technical processes. We investigated whether the Sabatier principle could be used for this purpose. Specifically, we compared the kinetics of two well-known PET hydrolases, leaf-branch compost cutinase (LCC) and a cutinase from the bacterium Thermobifida fusca (TfC), when adding different concentrations of the surfactant cetyltrimethylammonium bromide (CTAB). We found that CTAB consistently lowered the strength of enzyme-PET interactions, while its effect on enzymatic turnover was strongly biphasic. Thus, at gradually increasing CTAB concentrations, turnover was initially promoted and subsequently suppressed. This correlation with maximal turnover at an intermediate binding strength was in accordance with the Sabatier principle. One consequence of these results was that both enzymes had too strong intrinsic interaction with PET for optimal turnover, especially TfC, which showed a 20-fold improvement of k _cat at the maximum. LCC on the other hand had an intrinsic substrate affinity closer to the Sabatier optimum, and the turnover rate was 5-fold improved at weakened substrate binding. Our results showed that the Sabatier principle may indeed rationalize enzymatic PET degradation and support process optimization. Finally, we suggest that future discovery efforts should consider enzymes with weakened substrate binding because strong adsorption seems to limit their catalytic performance.

Rate-Perturbing Single Amino Acid Mutation for Hydrolases: A Statistical Profiling

Hydrolases are a critical component for modern chemical, pharmaceutical, and environmental sciences. Identifying mutations that enhance catalytic efficiency presents a roadblock to design and to discover new hydrolases for broad academic and industrial uses. Here, we report the statistical profiling for rate-perturbing mutant hydrolases with a single amino acid substitution. We constructed an integrated structure-kinetics database for hydrolases, IntEnzyDB, which contains 3907 k_cats, 4175 K_Ms, and 2715 Protein Data Bank IDs. IntEnzyDB adopts a relational architecture with a flattened data structure, enabling facile and efficient access to clean and tabulated data for machine learning uses. We conducted statistical analyses on how single amino acids mutations influence the turnover number (i.e., k_cat) and efficiency (i.e., k_cat/K_M), with a particular emphasis on profiling the features for rate-enhancing mutations. The results show that mutation to bulky nonpolar residues with a hydrocarbon chain involves a higher likelihood for rate acceleration than to other types of residues. Linear regression models reveal geometric descriptors of substrate and mutation residues that mediate rate-perturbing outcomes for hydrolases with bulky nonpolar mutations. On the basis of the analyses of the structure-kinetics relationship, we observe that the propensity for rate enhancement is independent of protein sizes. In addition, we observe that distal mutations (i.e., >10 Å from the active site) in hydrolases are significantly more prone to induce efficiency neutrality and avoid efficiency deletion but involve similar propensity for rate enhancement. The studies reveal the statistical features for identifying rate-enhancing mutations in hydrolases, which will potentially guide hydrolase discovery in biocatalysis.

Physical constraints and functional plasticity of cellulases

Enzyme reactions, both in Nature and technical applications, commonly occur at the interface of immiscible phases. Nevertheless, stringent descriptions of interfacial enzyme catalysis remain sparse, and this is partly due to a shortage of coherent experimental data to guide and assess such work. In this work, we produced and kinetically characterized 83 cellulases, which revealed a conspicuous linear free energy relationship (LFER) between the substrate binding strength and the activation barrier. The scaling occurred despite the investigated enzymes being structurally and mechanistically diverse. We suggest that the scaling reflects basic physical restrictions of the hydrolytic process and that evolutionary selection has condensed cellulase phenotypes near the line. One consequence of the LFER is that the activity of a cellulase can be estimated from its substrate binding strength, irrespectively of structural and mechanistic details, and this appears promising for in silico selection and design within this industrially important group of enzymes.

MnO2-graphene oxide hybrid nanomaterial with oxidase-like activity for ultrasensitive colorimetric detection of cancer cells

Robust and sensitive cell-based enzyme-linked immunosorbent assay (CELISA) is of great significance in the diagnosis and screening of cancer. However, the method is limited by the high rate of negative results attributed to the instability of horseradish peroxidase (HRP), H₂O₂, and antibody. Here, we construct a folic acid-functionalized in situ-grown MnO₂ nanosheet/graphene oxide hybrid (FA-MnO₂/GO) with oxidase-like activity instead of the anti-folate receptor antibody in traditional CELISA to resist the possible negative interference arising from unstable HRP, H₂O₂, and antibodies for more robust colorimetric detection of cancer cells. The functionalization of FA enables the selective binding between hybrid and cancer cells through the over-expressed folate receptor, and then the binding events are converted into quantitative colorimetric signals though the oxidation of the chromogenic substrate TMB catalyzed by MnO₂, allowing the detection of cancer cells with colorimetric method. Moreover, the construction of MnO₂/GO hybrid can synergistically enhance the oxidase-like activity of MnO₂ and promote its dispersion in water, further ensuring the accuracy and sensitivity of the detection. A detection limit of 20 cancer cells is obtained by a plate reader, which is lower than those obtained by most reported CELISA methods for cancer cell detection, and as few as 75 cancer cells can be identified by the naked eye. This study not only provides a multifunctional sensing platform for robust and sensitive cancer cell detection, but also offers a promising oxidase-like mimic in the field of bioanalysis.