A perspective on enzyme catalysis

Pressure-induced generation of heterogeneous electrocatalytic metal hydride surfaces for sustainable hydrogen transfer

Metal hydrides are crucial intermediates in numerous catalytic reactions. Intensive efforts have been dedicated to constructing molecular metal hydrides, where toxic precursors and delicate mediators are usually involved. Herein, we demonstrate a facile pressure-induced methodology to generate a cost-effective heterogeneous electrocatalytic metal hydride surface for sustainable hydrogen transfer. Taking carbon dioxide (CO2) electroreduction as a model system and zinc (Zn), a well-known carbon monoxide (CO)-selective catalyst, as a model catalyst, we showcase a homogeneous-type hydrogen atom transfer process induced by heterogeneous hydride surfaces, enabling direct hydrogenation pathways traditionally considered "prohibited". Specifically, the maximal Faradaic efficiency for formate is enhanced by ~fivefold to 83% under ambient conditions. Experimental and theoretical analyses reveal that unlike the distal hydrogenation route for CO2 to CO over pristine Zn, the Zn hydride surface enables direct hydrogenation at the carbon site of CO2 to form formate. This work provides a promising material platform for sustainable synthesis.

Biochemical and structural characterization of a novel L-isoleucine-4-dioxygenase (RaIDO) from Rahnella aquatilis

The L-isoleucine-4-dioxygenase converts L-isoleucine (Ile) into(2S,3R,4S)-4-(OH)-isoleucine (4-HIL), a naturally occurring hydroxyl amino acid, which is a promising compound for drug and functional food development. Here, a novel L-isoleucine-4-dioxygenase (RaIDO) from Rahnella aquatilis was cloned, expressed and characterized, as one of only a few reported L-isoleucine-4-dioxygenases. RaIDO showed high catalytic efficiency with Ile as the substrate, as well as good stability. HPLC-MS and NMR confirmed that RaIDO converts Ile into (2S,3R,4S)-4-(OH)-isoleucine. Further, structural analysis of RaIDO revealed key active site residues, including H159, D161 and H212. The RaIDO enzyme showed an optimal reaction temperature range of 30°C-45 °C, with the highest catalytic activity observed at 40 °C. Additionally, the enzyme exhibited an optimal pH of 8.0. Thus, the novel L-isoleucine-4-dioxygenase (RaIDO) has high catalytic efficiency and good stability, making it a strong candidate for industrial applications.

19F NMR Reveals the Dynamics of Substrate Binding and Lid Closure for Iodotyrosine Deiodinase as a Complement to Steady-State Kinetics and Crystallography

Active site lids are common features of enzymes and typically undergo conformational changes upon substrate binding to promote catalysis. Iodotyrosine deiodinase is no exception and contains a lid segment in all of its homologues from human to bacteria. The solution-state dynamics of the lid have now been characterized using 19F NMR spectroscopy with a CF3-labeled enzyme and CF3O-labeled ligands. From two-dimensional 19F-19F NMR exchange spectroscopy, interconversion rates between the free and bound states of a CF3O-substituted tyrosine (45 ± 10 s-1) and the protein label (40 ± 3 s-1) are very similar and suggest a correlation between ligand binding and conformational reorganization of the lid. Both occur at rates that are ∼100-fold faster than turnover, and therefore these steps do not limit catalysis. A simple CF3O-labeled phenol also binds to the active site and induces a conformational change in the lid segment that was not previously detectable by crystallography. Exchange rates of the ligand (130 ± 20 s-1) and protein (98 ± 8 s-1) in this example are faster than those above but remain self-consistent to affirm a correlation between ordering of the lid and binding of the ligand. Both ligands also protect the protein from limited proteolysis, as expected from their ability to stabilize a compact lid structure. However, the minimal turnover of simple phenol substrates indicates that such stabilization may be necessary but is not sufficient for efficient catalysis.

Exploring Conformational Landscapes Along Anharmonic Low-Frequency Vibrations

We aim to automatize the identification of collective variables to simplify and speed up enhanced sampling simulations of conformational dynamics in biomolecules. We focus on anharmonic low-frequency vibrations that exhibit fluctuations on time scales faster than conformational transitions but describe a path of least resistance toward structural change. A key challenge is that harmonic approximations are ill-suited to characterize these vibrations, which are observed at far-infrared frequencies and are easily excited by thermal collisions at room temperature. Here, we approached this problem with a frequency-selective anharmonic (FRESEAN) mode analysis that does not rely on harmonic approximations and successfully isolates anharmonic low-frequency vibrations from short molecular dynamics simulation trajectories. We applied FRESEAN mode analysis to simulations of alanine dipeptide, a common test system for enhanced sampling simulation protocols, and compared the performance of isolated low-frequency vibrations to conventional user-defined collective variables (here backbone dihedral angles) in enhanced sampling simulations. The comparison shows that enhanced sampling along anharmonic low-frequency vibrations not only reproduces known conformational dynamics but can even further improve the sampling of slow transitions compared to user-defined collective variables. Notably, free energy surfaces spanned by low-frequency anharmonic vibrational modes exhibit lower barriers associated with conformational transitions relative to representations in backbone dihedral space. We thus conclude that anharmonic low-frequency vibrations provide a promising path for highly effective and fully automated enhanced sampling simulations of conformational dynamics in biomolecules.

Substrate Turnover Dynamics Guide Ketol-Acid Reductoisomerase Redesign for Increased Specific Activity

The task of adapting enzymes for specific applications is often hampered by our incomplete ability to tune and tailor catalytic functions, particularly when seeking increased activity. Here, we develop and demonstrate a rational approach to address this challenge, applied to ketol-acid reductoisomerase (KARI), which has uses in industrial-scale isobutanol production. While traditional structure-based computational enzyme redesign strategies typically focus on the enzyme-bound ground state (GS) and transition state (TS), we postulated that additionally treating the underlying dynamics of complete turnover events that connect and pass through both states could further elucidate the structural properties affecting catalysis and help identify mutations that lead to increased catalytic activity. To examine the dynamics of substrate conversion with atomistic detail, we adapted and applied computational methods based on path sampling techniques to gather thousands of QM/MM simulations of attempted substrate turnover events by KARI: both productive (reactive) and unproductive (nonreactive) attempts. From these data, machine learning models were constructed and used to identify specific conformational features (interatomic distances, angles, and torsions) associated with successful, productive catalysis. Multistate protein redesign techniques were then used to select mutations that stabilized reactive-like structures over nonreactive-like ones while also meeting additional criteria consistent with enhanced specific activity. This procedure resulted in eight high-confidence enzyme mutants with a significant improvement in calculated specific activity relative to wild type (WT), with the fastest variant's increase in calculated k cat being (2 ± 1) × 104-fold. Collectively, these results suggest that introducing mutations designed to increase the population of reaction-promoting conformations of the enzyme-substrate complex before it reaches the barrier can provide an effective approach to engineering improved enzyme catalysts.

Analysis of the Behavior of Deep Eutectic Solvents upon Addition of Water: Its Effects over a Catalytic Reaction

This study presents the potential role of deep eutectic solvents (DESs) in a lipase-catalyzed hydrolysis reaction as a co-solvent in an aqueous solution given by a phosphate buffer. Ammonium salts, such as choline chloride, were paired with hydrogen bond donors, such as urea, 1,2,3-propanetriol, and 1,2 propanediol. The hydrolysis of p-nitrophenyl laureate was carried out with the lipase Candida antarctica Lipase B (CALB) as a reaction model to evaluate the solvent effect and tested in different DES/buffer phosphate mixtures at different % w/w. The results showed that two mixtures of different DES at 25 % w/w were the most promising solvents, as this percentage enhanced the activities of CALB, as evidenced by its higher catalytic efficiency (kcatKM). The solvent analysis shows that the enzymatic reaction requires a reaction media rich in water molecules to enable hydrogen-bond formation from the reaction media toward the enzymatic reaction, suggesting a better interaction between the substrate and the enzyme-active site. This interaction could be attributed to high degrees of freedom influencing the enzyme conformation given by the reaction media, suggesting that CALB acquires a more restrictive structure in the presence of DES or the stabilized network given by the hydrogen bond from water molecules in the mixture improves the enzymatic activity, conferring conformational stability by solvent effects. This study offers a promising approach for applications and further perspectives on genuinely green industrial solvents.

Cytochrome P450 Enzyme Design by Constraining the Catalytic Pocket in a Diffusion Model

Although cytochrome P450 enzymes are the most versatile biocatalysts in nature, there is insufficient comprehension of the molecular mechanism underlying their functional innovation process. Here, by combining ancestral sequence reconstruction, reverse mutation assay, and progressive forward accumulation, we identified 5 founder residues in the catalytic pocket of flavone 6-hydroxylase (F6H) and proposed a "3-point fixation" model to elucidate the functional innovation mechanisms of P450s in nature. According to this design principle of catalytic pocket, we further developed a de novo diffusion model (P450Diffusion) to generate artificial P450s. Ultimately, among the 17 non-natural P450s we generated, 10 designs exhibited significant F6H activity and 6 exhibited a 1.3- to 3.5-fold increase in catalytic capacity compared to the natural CYP706X1. This work not only explores the design principle of catalytic pockets of P450s, but also provides an insight into the artificial design of P450 enzymes with desired functions.

Amino Functionality Enables Aqueous Synthesis of Carboxylic Acid-Based MOFs at Room Temperature by Biomimetic Crystallization

Enzyme immobilization within metal-organic frameworks (MOFs) is a promising solution to avoid denaturation and thereby utilize the desirable properties of enzymes outside of their native environments. The biomimetic mineralization strategy employs biomacromolecules as nucleation agents to promote the crystallization of MOFs in water at room temperature, thus overcoming pore size limitations presented by traditional postassembly encapsulation. Most biomimetic crystallization studies reported to date have employed zeolitic imidazole frameworks (ZIFs). Herein, we expand the library of MOFs suitable for biomimetic mineralization to include zinc(II) MOFs incorporating functionalized terephthalic acid linkers and study the catalytic performance of the enzyme@MOFs. Amine functionalization of terephthalic acids is shown to accelerate the formation of crystalline MOFs enabling new enzyme@MOFs to be synthesized. The structure and morphology of the enzyme@MOFs were characterized by PXRD, FTIR, and SEM-EDX, and the catalytic potential was evaluated. Increasing the linker length while retaining the amino moiety gave rise to a family of linkers; however, MOFs generated with the 2,2'-aminoterephthalic acid linker displayed the best catalytic performance. Our data also illustrate that the pH of the reaction mixture affects the crystal structure of the MOF and that this structural transformation impacts the catalytic performance of the enzyme@MOF.

A Bioinspired Copper-Pair Catalyst in Metal-Organic Frameworks for Molecular Dioxygen Activation and Aerobic Oxidative C-N Coupling

Open Cu sites were loaded to the UiO-67 metal-organic framework (MOF) skeleton by introduction of flexible Cu-binding pyridylmethylamine (pyma) side chains to the biphenyldicarboxylate linkers. Distance between Cu centers in the MOF pores was tuned by controlling the density of metal-binding side chains. "Interacted" Cu-pair or "isolated" monomeric Cu sites were achieved with high and low (pyma)Cu side chain loading, respectively. Spectroscopic and theoretical studies indicate that "interacted" Cu pairs can effectively bind and activate molecular dioxygen to form Cu2O2 clusters, which showed high catalytic activity for aerobic oxidative C-N coupling. On the contrary, MOF catalyst bearing isolated monomeric Cu sites only showed modest catalytic activity. Enhancement in catalytic performance for the Cu-pair catalyst is attributed to the remote synergistic effect of the paired Cu site, which binds molecular dioxygen and cleaves the O═O bond in a collaborative manner. This work demonstrates that noncovalently interacted metal-pair sites can effectively activate inert small molecules and promote heterogeneous catalytic processes.

Solution Ionic Strength Can Modulate Functional Loop Conformations in E. coli Dihydrofolate Reductase

The observation of multiple conformations of a functional loop (termed M20) in the Escherichia coli dihydrofolate reductase (ecDHFR) enzyme triggered the proposition that large-scale motions of protein structural elements contribute to enzyme catalysis. The transition of the M20 loop from a closed conformation to an occluded conformation was thought to aid the rate-limiting release of the products. However, the influence of charged species in the solution environment on the observed M20 loop conformations, independent of charged ligands bound to the enzyme, had not been considered. Molecular dynamics simulations of ecDHFR in model CaCl2 solutions of varying molar ionic strengths IM reveal a substantial free energy barrier between occluded and closed M20 loop states at IM exceeding the E. coli threshold (∼0.24 M). This barrier may facilitate crystallization of ecDHFR in the occluded state, consistent with ecDHFR structures obtained at IM exceeding 0.3 M. At lower IM (≤0.15 M), the M20 loop can explore the occluded state, but prefers an open/partially closed conformation, again consistent with ecDHFR structures. Our findings caution against using ecDHFR structures obtained at nonphysiological ionic strengths in interpreting catalytic events or in structure-based drug design.

Modulating the Primary and Secondary Coordination Spheres of Single Ni(II) Sites in Metal-Organic Frameworks for Boosting Photocatalysis

Though the coordination environment of single metal sites has been recognized to be of great importance in promoting catalysis, the influence of simultaneous precise modulation of primary and secondary coordination spheres on catalysis remains largely unknown. Herein, a series of single Ni(II) sites with altered primary and secondary coordination spheres have been installed onto metal-organic frameworks (MOFs) with UiO-67 skeleton, affording UiO-Ni-X-Y (X = S, O; Y = H, Cl, CF3) with X and Y on the primary and secondary coordination spheres, respectively. Upon deposition with CdS nanoparticles, the resulting composites present high photocatalytic H2 production rates, in which the optimized CdS/UiO-Ni-S-CF3 exhibits an excellent activity of 13.44 mmol g-1, ∼500 folds of the pristine catalyst (29.6 μmol g-1 for CdS/UiO), in 8 h, highlighting the key role of microenvironment modulation around Ni sites. Charge kinetic analysis and theoretical calculation results demonstrate that the charge transfer dynamics and reaction energy barrier are closely correlated with their coordination spheres. This work manifests the advantages of MOFs in the fabrication of structurally precise catalysts and the elucidation of particular influences of microenvironment modulation around single metal sites on the catalytic performance.

Temporal Resolution of Activity-Related Solvation Dynamics in the TIM Barrel Enzyme Murine Adenosine Deaminase

Murine adenosine deaminase (mADA) is a prototypic system for studying the thermal activation of active site chemistry within the TIM barrel family of enzyme reactions. Previous temperature-dependent hydrogen deuterium exchange studies under various conditions have identified interconnected thermal networks for heat transfer from opposing protein-solvent interfaces to active site residues in mADA. One of these interfaces contains a solvent exposed helix-loop-helix moiety that presents the hydrophobic face of its long α-helix to the backside of bound substrate. Herein we pursue the time and temperature dependence of solvation dynamics at the surface of mADA, for comparison to established kinetic parameters that represent active site chemistry. We first created a modified protein devoid of native tryptophans with close to native kinetic behavior. Single site-specific tryptophan mutants were back inserted into each of the four positions where native tryptophans reside. Measurements of nanosecond fluorescence relaxation lifetimes and Stokes shift decays, that reflect time dependent environmental reoroganization around the photo-excited state of Trp*, display minimal temperature dependences. These regions serve as controls for the behavior of a new single tryptophan inserted into a solvent exposed region near the helix-loop-helix moiety located behind the bound substrate, Lys54Trp. This installed Trp displays a significantly elevated value for Ea ( k Stokes shift ) ; further, when Phe61 within the long helix positioned behind bound substrate is replaced by a series of aliphatic hydrophobic side chains, the trends in Ea ( k Stokes shift ) mirror the earlier reported impact of the same series of function-altering hydrophobic side chains on the activation energy of catalysis, Ea ( k cat ) .The reported experimental findings implicate a solvent initiated and rapid (>ns) protein restructuring that contributes to the enthalpic activation barrier to catalysis in mADA.

Exploring the Antarctic aminopeptidase P from Pseudomonas sp. strain AMS3 through structural analysis and molecular dynamics simulation

Aminopeptidase P (APPro) is a crucial metalloaminopeptidase involved in amino acid cleavage from peptide N-termini, playing essential roles as versatile biocatalysts with applications ranging from pharmaceuticals to industrial processes. Despite acknowledging its potential for catalysis in lower temperatures, detailed molecular basis and biotechnological implications in cold environments are yet to be explored. Therefore, this research aims to investigate the molecular mechanisms underlying the cold-adapted characteristics of APPro from Pseudomonas sp. strain AMS3 (AMS3-APPro) through a detailed analysis of its structure and dynamics. In this study, structure analysis and molecular dynamics (MD) simulation of a predicted model of AMS3-APPro has been performed at different temperatures to assess structural flexibility and thermostability across a temperature range of 0-60 °C over 100 ns. The MD simulation results revealed that the structure were able to remain stable at low temperatures. Increased temperatures present a potential threat to the overall stability of AMS3-APPro by disrupting the intricate hydrogen bond networks crucial for maintaining structural integrity, thereby increasing the likelihood of protein unfolding. While the metal binding site at the catalytic core exhibits resilience at higher temperatures, highlighting its local structural integrity, the overall enzyme structure undergoes fluctuations and potential denaturation. This extensive structural instability surpasses the localized stability observed at the metal binding site. Consequently, these assessments offer in-depth understanding of the cold-adapted characteristics of AMS3-APPro, highlighting its capability to uphold its native conformation and stability in low-temperature environments. In summary, this research provides valuable insights into the cold-adapted features of AMS3-APPro, suggesting its efficient operation in low thermal conditions, particularly relevant for potential biotechnological applications in cold environments.Communicated by Ramaswamy H. Sarma.

An optimized purification protocol for enzymatically synthesized S-adenosyl-L-methionine (SAM) for applications in solution state infrared spectroscopic studies

S-adenosyl-L-methionine (SAM) is an abundant biomolecule used by methyltransferases to regulate a wide range of essential cellular processes such as gene expression, cell signaling, protein functions, and metabolism. Despite considerable effort, there remain many specificity challenges associated with designing small molecule inhibitors for methyltransferases, most of which exhibit off-target effects. Interestingly, NMR evidence suggests that SAM undergoes conformeric exchange between several states when free in solution. Infrared spectroscopy can detect different conformers of molecules if present in appreciable populations. When SAM is noncovalently bound within enzyme active sites, the nature and the number of different conformations of the molecule are likely to be altered from when it is free in solution. If there are unique structures or different numbers of conformers between different methyltransferase active sites, solution-state information may provide promising structural leads to increase inhibitor specificity for a particular methyltransferase. Toward this goal, frequencies measured in SAM's infrared spectra must be assigned to the motions of specific atoms via isotope incorporation at discrete positions. The incorporation of isotopes into SAM's structure can be accomplished via an established enzymatic synthesis using isotopically labeled precursors. However, published protocols produced an intense and highly variable IR signal which overlapped with many of the signals from SAM rendering comparison between isotopes challenging. We observed this intense absorption to be from co-purifying salts and the SAM counterion, producing a strong, broad signal at 1100 cm-1. Here, we report a revised SAM purification protocol that mitigates the contaminating salts and present the first IR spectra of isotopically labeled CD3-SAM. These results provide a foundation for isotopic labeling experiments of SAM that will define which atoms participate in individual molecular vibrations, as a means to detect specific molecular conformations.

Electrostatics as a Guiding Principle in Understanding and Designing Enzymes

Enzyme design faces challenges related to the implementation of the basic principles that govern the catalytic activity in natural enzymes. In this work, we revisit basic electrostatic concepts that have been shown to explain the origin of enzymatic efficiency like preorganization and reorganization. Using magnitudes such as the electrostatic potential and the electric field generated by the protein, we explain how these concepts work in different enzymes and how they can be used to rationalize the consequences of point mutations. We also discuss examples of protein design in which electrostatic effects have been implemented. For the near future, molecular simulations, coupled with the use of machine learning methods, can be used to implement electrostatics as a guiding principle for enzyme designs.

Structural Effects on the Temperature Dependence of Hydride Kinetic Isotope Effects of the NADH/NAD+ Model Reactions in Acetonitrile: Charge-Transfer Complex Tightness Is a Key

It has recently frequently been found that the kinetic isotope effect (KIE) is independent of temperature (T) in H-tunneling reactions in enzymes but becomes dependent on T in their mutants. Many enzymologists found that the trend is related to different donor-acceptor distances (DADs) at tunneling-ready states (TRSs), which could be sampled by protein dynamics. That is, a more rigid system of densely populated short DADs gives rise to a weaker T dependence of KIEs. Theoreticians have attempted to develop H-tunneling theories to explain the observations, but none have been universally accepted. It is reasonable to assume that the DAD sampling concept, if it exists, applies to the H-transfer reactions in solution, as well. In this work, we designed NADH/NAD+ model reactions to investigate their structural effects on the T dependence of hydride KIEs in acetonitrile. Hammett correlations together with N-CH3/CD3 secondary KIEs were used to provide the electronic structure of the TRSs and thus the rigidity of their charge-transfer complexation vibrations. In all three pairs of reactions, a weaker T dependence of KIEs always corresponds to a steeper Hammett slope on the substituted hydride acceptors. It was found that a tighter/rigid charge-transfer complexation system corresponds with a weaker T dependence of KIEs, consistent with the observations in enzymes.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Assembly and catalytic activity of short prion-inspired peptides

Enzymes play a crucial role in biochemical reactions, but their inherent structural instability limits their performance in industrial processes. In contrast, amyloid structures, known for their exceptional stability, are emerging as promising candidates for synthetic catalysis. This article explores the development of metal-decorated nanozymes formed by short peptides, inspired by prion-like domains. We detail the rational design of synthetic short Tyrosine-rich peptide sequences, focusing on their self-assembly into stable amyloid structures and their metallization with biologically relevant divalent metal cations, such as Cu2+, Ni2+, Co2+ and Zn2+. The provided experimental framework offers a step-by-step guide for researchers interested in exploring the catalytic potential of metal-decorated peptides. By bridging the gap between amyloid structures and catalytic function, these hybrid molecules open new avenues for developing novel metalloenzymes with potential applications in diverse chemical reactions.

Selective cascade activation of polycyclic aromatic hydrocarbons in human cells: Role of enzyme's intrinsic electric field

Polycyclic aromatic hydrocarbons (PAHs) are major environmental organic pollutants. Some metabolites of PAHs show greater toxicity to humans while the others do not. It is highly important to decipher PAHs' regioselective activation mechanism and identify the major metabolites to accurately evaluate their public health risk. Here, we have performed a thorough computational study of benzo[a]anthracene (BA) metabolized by P450 1A1 by employing molecular docking, molecular dynamics simulations, quantum chemical calculation, and quantum mechanics/molecular mechanics calculations. Our findings show that highly-reactive species such as 3,4-epoxide, 8,9-epoxide, 3,4-diol-1,2-epoxide, and 8,9-diol-10,11-epoxide were major metabolites, which can efficiently react with guanine and damage DNA with extremely low energy barrier, therefore, supports the regioselective metabolism of BA. The origin of this selective activation is mainly contributed to both the oxygen‑carbon distance and previously overlooked enzyme's intrinsic electric field. Consequently, based on the resolved activation selectivity of BA. We built a high-throughput strategy to efficiently predict the metabolites of other PAHs. The accuracy of the strategy is validated by studying 16 PAHs on the priority control list. Hopefully this will aid the accurate evaluation of public health risks associated with PAH emissions.

Characterization of amyloid-like metal-amino acid assemblies with remarkable catalytic activity

While enzymes are potentially useful in various applications, their limited operational stability and production costs have led to an extensive search for stable catalytic agents that will retain the efficiency, specificity, and environmental-friendliness of natural enzymes. Despite extensive efforts, there is still an unmet need for improved enzyme mimics and novel concepts to discover and optimize such agents. Inspired by the catalytic activity of amyloids and the formation of amyloid-like assemblies by metabolites, our group pioneered the development of novel metabolite-metal co-assemblies (bio-nanozymes) that produce nanomaterials mimicking the catalytic function of common metalloenzymes that are being used for various technological applications. In addition to their notable activity, bio-nanozymes are remarkably safe as they are purely composed of amino acids and minerals that are harmless to the environment. The bio-nanozymes exhibit high efficiency and exceptional robustness, even under extreme conditions of temperature, pH, and salinity that are impractical for enzymes. Our group has recently also demonstrated the formation of ordered amino acid co-assemblies showing selective and preferential interactions comparable to the organization of residues in folded proteins. The identified bio-nanozymes can be used in various applications including environmental remediation, synthesis of new materials, and green energy.

FADH2-mediated radical polymerization amplification for microRNA-21 detection

For early diagnosis of disease, ultrasensitive mircoRNA-21 detection has considerable potential. In this paper, an ultra-sensitive fluorescence detection method for microRNA was developed by atom transfer radical polymerization (ATRP). This ATRP reaction was first initiated by using flavin mononucleotide (FADH2). The DNA probe 1 modified with amino group was fixed on the magnetic nanoparticle Fe3O4, and microRNA-21 was added to form the probe 1-microRNA-21. Another carboxy-modified DNA 2 forms a sandwich structure with the bound microRNA-21. Two terminally modified DNA types are used as microRNA probes, using complementary base pairing to form a stable super-sandwich structure between the DNA probe and the microRNA. Under optimal conditions, microRNA was detected in PBS buffer with a detection limit of 0.19 fM. And even in 10% of human serum, microRNA-21 can be detected with a detection limit of 47.8 fM. Results show that this method has high selectivity, efficiency and stability, which broad application prospect in microRNA ultra-sensitive detection.

Rational Design and Synthesis of an Artificial Enzyme for SN2 Reactions through Micellar Imprinting

The rational design of catalysts with enzyme-like properties is an elusive goal of chemists despite tremendous interest. Molecular imprinting inside surfactant micelles, followed by postmodification, creates a tailored active site in a water-soluble polymeric "artificial enzyme" for the benzylation of 4-nitrophenol. The reaction happens under neutral conditions with excellent substrate selectivity. Similar to many enzymes, electrostatics play vital roles in catalysis and can be tuned through different bases introduced into the active site.

Elucidating Dynamics of Adenylate Kinase from Enzyme Opening to Ligand Release

This study explores ligand-driven conformational changes in adenylate kinase (AK), which is known for its open-to-close conformational transitions upon ligand binding and release. By utilizing string free energy simulations, we determine the free energy profiles for both enzyme opening and ligand release and compare them with profiles from the apoenzyme. Results reveal a three-step ligand release process, which initiates with the opening of the adenosine triphosphate-binding subdomain (ATP lid), followed by ligand release and concomitant opening of the adenosine monophosphate-binding subdomain (AMP lid). The ligands then transition to nonspecific positions before complete dissociation. In these processes, the first step is energetically driven by ATP lid opening, whereas the second step is driven by ATP release. In contrast, the AMP lid opening and its ligand release make minor contributions to the total free energy for enzyme opening. Regarding the ligand binding mechanism, our results suggest that AMP lid closure occurs via an induced-fit mechanism triggered by AMP binding, whereas ATP lid closure follows conformational selection. This difference in the closure mechanisms provides an explanation with implications for the debate on ligand-driven conformational changes of AK. Additionally, we determine an X-ray structure of an AK variant that exhibits significant rearrangements in the stacking of catalytic arginines, explaining its reduced catalytic activity. In the context of apoenzyme opening, the sequence of events is different. Here, the AMP lid opens first while the ATP lid remains closed, and the free energy associated with ATP lid opening varies with orientation, aligning with the reported AK opening and closing rate heterogeneity. Finally, this study, in conjunction with our previous research, provides a comprehensive view of the intricate interplay between various structural elements, ligands, and catalytic residues that collectively contribute to the robust catalytic power of the enzyme.

BioCARS: Synchrotron facility for probing structural dynamics of biological macromolecules

A major goal in biomedical science is to move beyond static images of proteins and other biological macromolecules to the internal dynamics underlying their function. This level of study is necessary to understand how these molecules work and to engineer new functions and modulators of function. Stemming from a visionary commitment to this problem by Keith Moffat decades ago, a community of structural biologists has now enabled a set of x-ray scattering technologies for observing intramolecular dynamics in biological macromolecules at atomic resolution and over the broad range of timescales over which motions are functionally relevant. Many of these techniques are provided by BioCARS, a cutting-edge synchrotron radiation facility built under Moffat leadership and located at the Advanced Photon Source at Argonne National Laboratory. BioCARS enables experimental studies of molecular dynamics with time resolutions spanning from 100 ps to seconds and provides both time-resolved x-ray crystallography and small- and wide-angle x-ray scattering. Structural changes can be initiated by several methods-UV/Vis pumping with tunable picosecond and nanosecond laser pulses, substrate diffusion, and global perturbations, such as electric field and temperature jumps. Studies of dynamics typically involve subtle perturbations to molecular structures, requiring specialized computational techniques for data processing and interpretation. In this review, we present the challenges in experimental macromolecular dynamics and describe the current state of experimental capabilities at this facility. As Moffat imagined years ago, BioCARS is now positioned to catalyze the scientific community to make fundamental advances in understanding proteins and other complex biological macromolecules.

Designed Local Electric Fields-Promising Tools for Enzyme Engineering

Designing efficient catalysts is one of the ultimate goals of chemists. In this Perspective, we discuss how local electric fields (LEFs) can be exploited to improve the catalytic performance of supramolecular catalysts, such as enzymes. More specifically, this Perspective starts by laying out the fundamentals of how local electric fields affect chemical reactivity and review the computational tools available to study electric fields in various settings. Subsequently, the advances made so far in optimizing enzymatic electric fields through targeted mutations are discussed critically and concisely. The Perspective ends with an outlook on some anticipated evolutions of the field in the near future. Among others, we offer some pointers on how the recent data science/machine learning revolution, engulfing all science disciplines, could potentially provide robust and principled tools to facilitate rapid inference of electric field effects, as well as the translation between optimal electrostatic environments and corresponding chemical modifications.

Late-Stage Halogenation of Peptides, Drugs and (Hetero)aromatic Compounds with a Nucleophilic Hydrazide Catalyst

Unlike its other halogen atom siblings, chlorination of a bioactive compound can change its physiological characteristics, improve its pharmacological profile, and function as a point of diversification through cross-coupling reactions. As a result, it has been a crucial strategy for drug discovery and development. However, functional groups such as amines, amides, hydroxy groups, or carboxylic acids trap the Cl+ , severely limiting the reactivity and making direct chlorination far too difficult to be practical. Herein, we introduce a nucleophilic sulfonohydrazide catalyst for late-stage halogenation of peptides and drugs. This direct, mild and metal-free protocol shows high functional-group tolerance and is compatible with a range of structurally diverse peptides, drugs and aromatic compounds. Furthermore, DFT studies indicate that the reaction most likely proceeds via a cationic transition state. The gram-scale synthesis, high stability and efficiency of the catalyst provide a facile route for late-stage functionalization and intermediates for further derivatization.

Recent advances in structure-based enzyme engineering for functional reconstruction

Structural information can help engineer enzymes. Usually, specific amino acids in particular regions are targeted for functional reconstruction to enhance the catalytic performance, including activity, stereoselectivity, and thermostability. Appropriate selection of target sites is the key to structure-based design, which requires elucidation of the structure-function relationships. Here, we summarize the mutations of residues in different specific regions, including active center, access tunnels, and flexible loops, on fine-tuning the catalytic performance of enzymes, and discuss the effects of altering the local structural environment on the functions. In addition, we keep up with the recent progress of structure-based approaches for enzyme engineering, aiming to provide some guidance on how to take advantage of the structural information.

Recent advances in metal-organic frameworks: Synthesis, application and toxicity

Metal-organic frameworks (MOFs) are a new class of crystalline porous hybrid materials with high porosity, large specific surface area and adjustable channel structure and biocompatibility, which are being investigated with increasing interest for energy storage and conversion, gas adsorption/separation, catalysis, sensing and biomedicine. However, the practical applications of MOFs make them release into the environment inevitable, posing a threat to humans and organisms. In this article, we cover advances in the currently available MOFs synthesis methods and the emerging applications of MOFs, especially in the biomedical field (therapeutic agents and bioimaging). Additionally, after evaluating the current status of main exposure routes and affecting factors in the field of MOFs-toxicity, the molecular mechanism is also clarified and identified. Knowledge gaps are identified from such a summarization and frontier development are explored for MOFs. Afterwards, we also present the limitations, challenges, and future perspectives in the study of the entire life cycle of MOFs. This review emphasizes the need for a more targeted discussion of the latest, widely used and effective versatile material class in order to exploit the full potential of high-performance and non-toxicity MOFs in the future.

Carbon-Carbon Bond Cleavage for Late-Stage Functionalization

Late-stage functionalization (LSF) introduces functional group or structural modification at the final stage of the synthesis of natural products, drugs, and complex compounds. It is anticipated that late-stage functionalization would improve drug discovery's effectiveness and efficiency and hasten the creation of various chemical libraries. Consequently, late-stage functionalization of natural products is a productive technique to produce natural product derivatives, which significantly impacts chemical biology and drug development. Carbon-carbon bonds make up the fundamental framework of organic molecules. Compared with the carbon-carbon bond construction, the carbon-carbon bond activation can directly enable molecular editing (deletion, insertion, or modification of atoms or groups of atoms) and provide a more efficient and accurate synthetic strategy. However, the efficient and selective activation of unstrained carbon-carbon bonds is still one of the most challenging projects in organic synthesis. This review encompasses the strategies employed in recent years for carbon-carbon bond cleavage by explicitly focusing on their applicability in late-stage functionalization. This review expands the current discourse on carbon-carbon bond cleavage in late-stage functionalization reactions by providing a comprehensive overview of the selective cleavage of various types of carbon-carbon bonds. This includes C-C(sp), C-C(sp2), and C-C(sp3) single bonds; carbon-carbon double bonds; and carbon-carbon triple bonds, with a focus on catalysis by transition metals or organocatalysts. Additionally, specific topics, such as ring-opening processes involving carbon-carbon bond cleavage in three-, four-, five-, and six-membered rings, are discussed, and exemplar applications of these techniques are showcased in the context of complex bioactive molecules or drug discovery. This review aims to shed light on recent advancements in the field and propose potential avenues for future research in the realm of late-stage carbon-carbon bond functionalization.

Recent advances in porous molecular cages for photocatalytic organic conversions

Photocatalytic organic conversion is considered an efficient, environmentally friendly, and energy-saving strategy for organic synthesis. In recent decades, the molecular cage has emerged as a creative functional material with broad applications in host-guest recognition, drug delivery, catalysis, intelligent materials and other fields. Based on the unique properties of porous molecular cage materials, they provide an ideal platform for leveraging pre-structuring in catalytic reactions and show great potential in various photocatalytic organic reactions. As a result, they have emerged as promising alternatives to conventional molecules or inorganic photocatalysts in redox processes. In this Review, the synthesis strategies based on coordination cages and organic cages, as well as their recent progress in photocatalytic organic conversion, are comprehensively summarized. Finally, we deliver the persistent challenges associated with porous molecular cage compounds that need to be overcome for further development in this field.

Turning on Asymmetric Catalysis of Achiral Metal-Organic Frameworks by Imparting Chiral Microenvironment

The development of heterogeneous asymmetric catalysts has attracted increasing interest in synthetic chemistry but mostly relies on the immobilization of homogeneous chiral catalysts. Herein, a series of chiral metal-organic frameworks (MOFs) have been fabricated by anchoring similar chiral hydroxylated molecules (catalytically inactive) with different lengths onto Zr-oxo clusters in achiral PCN-222(Cu). The resulting chiral MOFs exhibit regulated enantioselectivity up to 83 % ee in the asymmetric ring-opening of cyclohexene oxide. The chiral molecules furnished onto the catalytic Lewis sites in the MOF create multilevel microenvironment, including the hydrogen interaction between the substrate and the chiral -OH group, the steric hindrance endowed by the benzene ring on the chiral molecules, and the proximity between the catalytic sites and chiral molecules confined in the MOF pores, which play crucial roles and synergistically promote chiral catalysis. This work nicely achieves heterogeneous enantioselective catalysis by chiral microenvironment modulation around Lewis acid sites.

Natural Antibodies Produced in Vaccinated Patients and COVID-19 Convalescents Recognize and Hydrolyze Oligopeptides Corresponding to the S-Protein of SARS-CoV-2

The S-protein is the major antigen of the SARS-CoV-2 virus, against which protective antibodies are generated. The S-protein gene was used in adenoviral vectors and mRNA vaccines against COVID-19. While the primary function of antibodies is to bind to antigens, catalytic antibodies can hydrolyze various substrates, including nucleic acids, proteins, oligopeptides, polysaccharides, and some other molecules. In this study, antibody fractions with affinity for RBD and S-protein (RBD-IgG and S-IgG) were isolated from the blood of COVID-19 patients vaccinated with Sputnik V. The fractions were analyzed for their potential to hydrolyze 18-mer oligopeptides corresponding to linear fragments of the SARS-CoV-2 S-protein. Here, we show that the IgG antibodies hydrolyze six out of nine oligopeptides efficiently, with the antibodies of COVID-19-exposed donors demonstrating the most significant activity. The IgGs of control donors not exposed to SARS-CoV-2 were found to be inactive in oligopeptide hydrolysis. The antibodies of convalescents and vaccinated patients were found to hydrolyze oligopeptides in a wide pH range, with the optimal pH range between 6.5 and 7.5. The hydrolysis of most oligopeptides by RBD-IgG antibodies is inhibited by thiol protease inhibitors, whereas S-IgG active centers generally combine several types of proteolytic activities. Ca2+ ions increase the catalytic activity of IgG preparations containing metalloprotease-like active centers. Thus, the proteolytic activity of natural antibodies against the SARS-CoV-2 protein is believed to be due to the similarity of catalytic antibodies' active centers to canonical proteases. This work raises the question of the possible physiological role of proteolytic natural RBD-IgG and S-IgG resulting from vaccination and exposure to COVID-19.

Enantioselective Biomimetic Structures Inspired by Oxi-Dase-Type Metalloenzymes, Utilizing Polynuclear Compounds Containing Copper (II) and Manganese (II) Ions as Building Blocks

This study focuses on developing and evaluating two novel enantioselective biomimetic models for the active centers of oxidases (ascorbate oxidase and catalase). These models aim to serve as alternatives to enzymes, which often have limited action and a delicate nature. For the ascorbate oxidase (AO) model (compound 1), two enantiomers, S,S(+)cpse and R,R(-)cpse, were combined in a crystalline structure, resulting in a racemic compound. The analysis of their magnetic properties and electrochemical behavior revealed electronic transfer between six metal centers. Compound 1 effectively catalyzed the oxidation of ascorbic to dehydroascorbic acid, showing a 45.5% yield for the racemic form. This was notably higher than the enantiopure compounds synthesized previously and tested in the current report, which exhibited yields of 32% and 28% for the S,S(+)cpse and R,R(-)cpse enantiomers, respectively. This outcome highlights the influence of electronic interactions between metal ions in the racemic compound compared to pure enantiomers. On the other hand, for the catalase model (compound 2), both the compound and its enantiomer displayed polymeric properties and dimeric behavior in the solid and solution states, respectively. Compound 2 proved to be effective in catalyzing the oxidation of hydrogen peroxide to oxygen with a yield of 64.7%. In contrast, its enantiomer (with R,R(-)cpse) achieved only a 27% yield. This further validates the functional nature of the prepared biomimetic models for oxidases. This research underscores the importance of understanding and designing biomimetic models of metalloenzyme active centers for both biological and industrial applications. These models show promising potential as viable alternatives to natural enzymes in various processes.

Amyloid Fibrils Formed by Short Prion-Inspired Peptides Are Metalloenzymes

Enzymes typically fold into defined 3D protein structures exhibiting a high catalytic efficiency and selectivity. It has been proposed that the earliest enzymes may have arisen from the self-assembly of short peptides into supramolecular amyloid-like structures. Several artificial amyloids have been shown to display catalytic activity while offering advantages over natural enzymes in terms of modularity, flexibility, stability, and reusability. Hydrolases, especially esterases, are the most common artificial amyloid-like nanozymes with some reported to act as carbonic anhydrases (CA). Their hydrolytic activity is often dependent on the binding of metallic cofactors through a coordination triad composed of His residues in the β-strands, which mimic the arrangement found in natural metalloenzymes. Tyr residues contribute to the coordination of metal ions in the active center of metalloproteins; however, their use has been mostly neglected in the design of metal-containing amyloid-based nanozymes. We recently reported that four different polar prion-inspired heptapeptides spontaneously self-assembled into amyloid fibrils. Their sequences lack His but contain three alternate Tyr residues exposed to solvent. We combine experiments and simulations to demonstrate that the amyloid fibrils formed by these peptides can efficiently coordinate and retain different divalent metal cations, functioning as both metal scavengers and nanozymes. The metallized fibrils exhibit esterase and CA activities without the need for a histidine triad. These findings highlight the functional versatility of prion-inspired peptide assemblies and provide a new sequential context for the creation of artificial metalloenzymes. Furthermore, our data support amyloid-like structures acting as ancestral catalysts at the origin of life.

Recent advances in the synthesis and applications of single-atom nanozymes in food safety monitoring

Nanozymes are synthetic compounds with enzyme-like tunable catalytic properties. The success of nanozymes for catalytic applications can be attributed to their small dimensions, cost-effective synthesis, appreciable stability, and scalability to molecular dimensions. The emergence of single atom nanozymes (SANzymes) has opened up new possibilities in bioanalytical applications. In this regard, this review outlines enzyme-mimicking features of SANzymes for food safety applications in relation to the key variables controlling their catalytic performance. The discussion is extended further to cover the applications of SANzymes for the monitoring of various compounds/biomaterials of significance with respect to food safety (e.g., pesticides, veterinary drug residues, foodborne pathogenic bacteria, mycotoxins/bacterial endotoxin, antioxidant residues, hydrogen peroxide residues, and heavy metal ions). Furthermore, the performance of SANzymes is evaluated in terms of various performance metrics such as limit of detection (LOD), linear dynamic range, and figure of merit (FoM). The challenges and future road map for the applications of SANzymes are also addressed along with their upscaling in the area of food safety.

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

A survey of protein databases indicates that the majority of enzymes exist in oligomeric forms, with about half of those found in the UniProt database being homodimeric. Understanding why many enzymes are in their dimeric form is imperative. Recent developments in experimental and computational techniques have allowed for a deeper comprehension of the cooperative interactions between the subunits of dimeric enzymes. This review aims to succinctly summarize these recent advancements by providing an overview of experimental and theoretical methods, as well as an understanding of cooperativity in substrate binding and the molecular mechanisms of cooperative catalysis within homodimeric enzymes. Focus is set upon the beneficial effects of dimerization and cooperative catalysis. These advancements not only provide essential case studies and theoretical support for comprehending dimeric enzyme catalysis but also serve as a foundation for designing highly efficient catalysts, such as dimeric organic catalysts. Moreover, these developments have significant implications for drug design, as exemplified by Paxlovid, which was designed for the homodimeric main protease of SARS-CoV-2.

Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction data

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363 K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

Enantio- and Diastereoenriched Enzymatic Synthesis of 1,2,3-Polysubstituted Cyclopropanes from (Z/E)-Trisubstituted Enol Acetates

In nature and synthetic chemistry, stereoselective [2 + 1] cyclopropanation is the most prevalent strategy for the synthesis of chiral cyclopropanes, a class of key pharmacophores in pharmaceuticals and bioactive natural products. One of the most extensively studied reactions in the organic chemist's arsenal, stereoselective [2 + 1] cyclopropanation, largely relies on the use of stereodefined olefins, which can require elaborate laboratory synthesis or tedious separation to ensure high stereoselectivity. Here, we report engineered hemoproteins derived from a bacterial cytochrome P450 that catalyze the synthesis of chiral 1,2,3-polysubstituted cyclopropanes, regardless of the stereopurity of the olefin substrates used. Cytochrome P450BM3 variant P411-INC-5185 exclusively converts (Z)-enol acetates to enantio- and diastereoenriched cyclopropanes and in the model reaction delivers a leftover (E)-enol acetate with 98% stereopurity, using whole Escherichia coli cells. P411-INC-5185 was further engineered with a single mutation to enable the biotransformation of (E)-enol acetates to α-branched ketones with high levels of enantioselectivity while simultaneously catalyzing the cyclopropanation of (Z)-enol acetates with excellent activities and selectivities. We conducted docking studies and molecular dynamics simulations to understand how active-site residues distinguish between the substrate isomers and enable the enzyme to perform these distinct transformations with such high selectivities. Computational studies suggest the observed enantio- and diastereoselectivities are achieved through a stepwise pathway. These biotransformations streamline the synthesis of chiral 1,2,3-polysubstituted cyclopropanes from readily available mixtures of (Z/E)-olefins, adding a new dimension to classical cyclopropanation methods.

Machine Learning Methods for Small Data Challenges in Molecular Science

Small data are often used in scientific and engineering research due to the presence of various constraints, such as time, cost, ethics, privacy, security, and technical limitations in data acquisition. However, big data have been the focus for the past decade, small data and their challenges have received little attention, even though they are technically more severe in machine learning (ML) and deep learning (DL) studies. Overall, the small data challenge is often compounded by issues, such as data diversity, imputation, noise, imbalance, and high-dimensionality. Fortunately, the current big data era is characterized by technological breakthroughs in ML, DL, and artificial intelligence (AI), which enable data-driven scientific discovery, and many advanced ML and DL technologies developed for big data have inadvertently provided solutions for small data problems. As a result, significant progress has been made in ML and DL for small data challenges in the past decade. In this review, we summarize and analyze several emerging potential solutions to small data challenges in molecular science, including chemical and biological sciences. We review both basic machine learning algorithms, such as linear regression, logistic regression (LR), k-nearest neighbor (KNN), support vector machine (SVM), kernel learning (KL), random forest (RF), and gradient boosting trees (GBT), and more advanced techniques, including artificial neural network (ANN), convolutional neural network (CNN), U-Net, graph neural network (GNN), Generative Adversarial Network (GAN), long short-term memory (LSTM), autoencoder, transformer, transfer learning, active learning, graph-based semi-supervised learning, combining deep learning with traditional machine learning, and physical model-based data augmentation. We also briefly discuss the latest advances in these methods. Finally, we conclude the survey with a discussion of promising trends in small data challenges in molecular science.

Correlation of temperature dependence of hydride kinetic isotope effects with donor-acceptor distances in two solvents of different polarities

Recently observed nearly temperature (T)-independent kinetic isotope effects (KIEs) in wild-type enzymes and T-dependent KIEs in variants were used to suggest that H-tunneling in enzymes is assisted by the fast protein vibrations that help sample short donor-acceptor distances (DADs). This supports the recently proposed role of protein vibrations in DAD sampling catalysis. However, use of T-dependence of KIEs to suggest DAD sampling associated with protein vibrations is debated. We have formulated a hypothesis regarding the correlation and designed experiments in solution to investigate it. The hypothesis is, a more rigid system with shorter DADTRS's at the tunneling ready states (TRSs) gives rise to a weaker T-dependence of KIEs, i.e., a smaller ΔEa (= EaD - EaH). In a former work, the solvent effects of acetonitrile versus chloroform on the ΔEa of NADH/NAD+ model reactions were determined, and the DADPRC's of the productive reactant complexes (PRCs) were computed to substitute the DADTRS for the DADTRS-ΔEa correlation study. A smaller ΔEa was found in the more polar acetonitrile where the positively charged PRC is better solvated and has a shorter DADPRC, indirectly supporting the hypothesis. In this work, the TRS structures of different DADTRS's for the hydride tunneling reaction from 1,3-dimethyl-2-phenylimidazoline to 10-methylacridinium were computed. The N-CH3/CD3 secondary KIEs on both reactants were calculated and fitted to the observed values to find the DADTRS order in both solutions. It was found that the equilibrium DADTRS is shorter in acetonitrile than in chloroform. Results directly support the DADTRS-ΔEa correlation hypothesis as well as the explanation that links T-dependence of KIEs to DAD sampling catalysis in enzymes.

Second-Shell Residues Contribute to Catalysis by Predominately Preorganizing the Apo State in PafA

Residues beyond the first coordination shell are often observed to make considerable cumulative contributions in enzymes. Due to typically indirect perturbations of multiple physicochemical properties of the active site, however, their individual and specific roles in enzyme catalysis and disease-causing mutations remain difficult to predict and understand at the molecular level. Here we analyze the contributions of several second-shell residues in phosphate-irrepressible alkaline phosphatase of flavobacterium (PafA), a representative system as one of the most efficient enzymes. By adopting a multifaceted approach that integrates quantum-mechanical/molecular-mechanical free energy computations, molecular-mechanical molecular dynamics simulations, and density functional theory cluster model calculations, we probe the rate-limiting phosphoryl transfer step and structural properties of all relevant enzyme states. In combination with available experimental data, our computational results show that mutations of the studied second-shell residues impact catalytic efficiency mainly by perturbation of the apo state and therefore substrate binding, while they do not affect the ground state or alter the nature of phosphoryl transfer transition state significantly. Several second-shell mutations also modulate the active site hydration level, which in turn influences the energetics of phosphoryl transfer. These mechanistic insights also help inform strategies that may improve the efficiency of enzyme design and engineering by going beyond the current focus on the first coordination shell.

Refinement of Multiconformer Ensemble Models from Multi-temperature X-ray Diffraction Data

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

Chaotic advection mixer for capturing transient states of diverse biological macromolecular systems with time-resolved small-angle X-ray scattering

Advances in time-resolved structural techniques, mainly in macromolecular crystallography and small-angle X-ray scattering (SAXS), allow for a detailed view of the dynamics of biological macromolecules and reactions between binding partners. Of particular promise, are mix-and-inject techniques, which offer a wide range of experimental possibility as microfluidic mixers are used to rapidly combine two species just prior to data collection. Most mix-and-inject approaches rely on diffusive mixers, which have been effectively used within crystallography and SAXS for a variety of systems, but their success is dependent on a specific set of conditions to facilitate fast diffusion for mixing. The use of a new chaotic advection mixer designed for microfluidic applications helps to further broaden the types of systems compatible with time-resolved mixing experiments. The chaotic advection mixer can create ultra-thin, alternating layers of liquid, enabling faster diffusion so that even more slowly diffusing molecules, like proteins or nucleic acids, can achieve fast mixing on timescales relevant to biological reactions. This mixer was first used in UV-vis absorbance and SAXS experiments with systems of a variety of molecular weights, and thus diffusion speeds. Careful effort was also dedicated to making a loop-loading sample-delivery system that consumes as little sample as possible, enabling the study of precious, laboratory-purified samples. The combination of the versatile mixer with low sample consumption opens the door to many new applications for mix-and-inject studies.

Fully Oxygen-Tolerant Visible-Light-Induced ATRP of Acrylates in Water: Toward Synthesis of Protein-Polymer Hybrids

Over the last decade, photoinduced ATRP techniques have been developed to harness the energy of light to generate radicals. Most of these methods require the use of UV light to initiate polymerization. However, UV light has several disadvantages: it can degrade proteins, damage DNA, cause undesirable side reactions, and has low penetration depth in reaction media. Recently, we demonstrated green-light-induced ATRP with dual catalysis, where eosin Y (EYH2) was used as an organic photoredox catalyst in conjunction with a copper complex. This dual catalysis proved to be highly efficient, allowing rapid and well-controlled aqueous polymerization of oligo(ethylene oxide) methyl ether methacrylate without the need for deoxygenation. Herein, we expanded this system to synthesize polyacrylates under biologically relevant conditions using CuII/Me6TREN (Me6TREN = tris[2-(dimethylamino)ethyl]amine) and EYH2 at ppm levels. Water-soluble oligo(ethylene oxide) methyl ether acrylate (average M n = 480, OEOA480) was polymerized in open reaction vessels under green light irradiation (520 nm). Despite continuous oxygen diffusion, high monomer conversions were achieved within 40 min, yielding polymers with narrow molecular weight distributions (1.17 ≤ D̵ ≤ 1.23) for a wide targeted DP range (50-800). In situ chain extension and block copolymerization confirmed the preserved chain end functionality. In addition, polymerization was triggered/halted by turning on/off a green light, showing temporal control. The optimized conditions also enabled controlled polymerization of various hydrophilic acrylate monomers, such as 2-hydroxyethyl acrylate, 2-(methylsulfinyl)ethyl acrylate), and zwitterionic carboxy betaine acrylate. Notably, the method allowed the synthesis of well-defined acrylate-based protein-polymer hybrids using a straightforward reaction setup without rigorous deoxygenation.

Non-active Site Residue in Loop L4 Alters Substrate Capture and Product Release in d-Arginine Dehydrogenase

Numerous studies demonstrate that enzymes undergo multiple conformational changes during catalysis. The malleability of enzymes forms the basis for allosteric regulation: residues located far from the active site can exert long-range dynamical effects on the active site residues to modulate catalysis. The structure of Pseudomonas aeruginosa d-arginine dehydrogenase (PaDADH) shows four loops (L1, L2, L3, and L4) that span the substrate and the FAD-binding domains. Loop L4 comprises residues 329-336, spanning over the flavin cofactor. The I335 residue on loop L4 is ∼10 Å away from the active site and ∼3.8 Å from N(1)-C(2)═O atoms of the flavin. In this study, we used molecular dynamics and biochemical techniques to investigate the effect of the mutation of I335 to histidine on the catalytic function of PaDADH. Molecular dynamics showed that the conformational dynamics of PaDADH are shifted to a more closed conformation in the I335H variant. In agreement with an enzyme that samples more in a closed conformation, the kinetic data of the I335H variant showed a 40-fold decrease in the rate constant of substrate association (k₁), a 340-fold reduction in the rate constant of substrate dissociation from the enzyme-substrate complex (k₂), and a 24-fold decrease in the rate constant of product release (k₅), compared to that of the wild-type. Surprisingly, the kinetic data are consistent with the mutation having a negligible effect on the reactivity of the flavin. Altogether, the data indicate that the residue at position 335 has a long-range dynamical effect on the catalytic function in PaDADH.

Biomimetic mineralization based on self-assembling peptides

Biomimetic science has attracted great interest in the fields of chemistry, biology, materials science, and energy. Biomimetic mineralization is the process of synthesizing inorganic minerals under the control of organic molecules or biomolecules under mild conditions. Peptides are the motifs that constitute proteins, and can self-assemble into various hierarchical structures and show a high affinity for inorganic substances. Therefore, peptides can be used as building blocks for the synthesis of functional biomimetic materials. With the participation of peptides, the morphology, size, and composition of mineralized materials can be controlled precisely. Peptides not only provide well-defined templates for the nucleation and growth of inorganic nanomaterials but also have the potential to confer inorganic nanomaterials with high catalytic efficiency, selectivity, and biotherapeutic functions. In this review, we systematically summarize research progress in the formation mechanism, nanostructural manipulation, and applications of peptide-templated mineralized materials. These can further inspire researchers to design structurally complex and functionalized biomimetic materials with great promising applications.

Activation of mouse Otop3 proton channels by Zn2+

Otopetrins (Otop1-Otop3) belong to a newly identified family of proton (H⁺) channels activated by extracellular acidification. Here, we found that Zn²⁺ activates the mouse Otop3 (mOtop3) proton channels by using electrophysiological patch-clamp techniques. In mOtop3-expressing human embryonic kidney HEK293T cells, a biphasic inward mOtop3 H⁺ current comprising a fast transient current followed by a sustained current was observed upon extracellular acidification at pH 5.0. No significant activation of the mOtop3 channel was observed at pH 6.5 and 7.4, but interestingly, Zn²⁺ dose-dependently induced a sustained activation of mOtop3 under these pH conditions. Increasing the Zn²⁺ concentration had no effect on the reversal potential of the channel currents, suggesting that Zn²⁺ does not permeate through the mOtop3. The activation of the mOtop3 channel was specific to Zn²⁺ among divalent metal cations. Our findings reveal a novel modulatory mechanism of mOtop3 proton channels by Zn²⁺.

Modulating the local coordination environment of cobalt single-atomic nanozymes for enhanced catalytic therapy against bacteria

Single-atomic nanozymes (SANZs) characterized by atomically dispersed single metal atoms have recently contributed to breakthroughs in biomedicine due to their satisfactory catalytic activity and superior selectivity compared to their nanoscale counterparts. The catalytic performance of SANZs can be improved by modulating their coordination structure. Therefore, adjusting the coordination number of the metal atoms in the active center is a potential method for enhancing the catalytic therapy effect. In this study, we synthesized various atomically dispersed Co nanozymes with different nitrogen coordination numbers for peroxidase (POD)-mimicking single-atomic catalytic antibacterial therapy. Among the single-atomic Co nanozymes with nitrogen coordination numbers of 3 (SACNZs-N₃-C) and 4 (SACNZs-N₄-C), single-atomic Co nanozymes with a coordination number of 2 (SACNZs-N₂-C) had the highest POD-like catalytic activity. Kinetic assays and Density functional theory (DFT) calculations indicated that reducing the coordination number can lower the reaction energy barrier of single-atomic Co nanozymes (SACNZs-N_x-C), thereby increasing their catalytic performance. In vitro and in vivo antibacterial assays demonstrated that SACNZs-N₂-C had the best antibacterial effect. This study provides proof of concept for enhancing single-atomic catalytic therapy by regulating the coordination number for various biomedical applications, such as tumor therapy and wound disinfection. STATEMENT OF SIGNIFICANCE: The use of nanozymes that contain single-atomic catalytic sites has been shown to effectively promote the healing of bacteria-infected wounds by exhibiting peroxidase-like activity. The homogeneous coordination environment of the catalytic site has been associated with high antimicrobial activity, which provides insight into designing new active structures and understanding their mechanisms of action. In this study, we designed a series of cobalt single-atomic nanozymes (PSACNZs-N_x-C) with different coordination environments by shearing the Co-N bond and modifying polyvinylpyrrolidone (PVP). The synthesized PSACNZs-N_x-C demonstrated enhanced antibacterial activity against both Gram-positive and Gram-negative bacterial strains, and showed good biocompatibility in both in vivo and in vitro experiments.

Evolutionary conservation of protein dynamics: insights from all-atom molecular dynamics simulations of 'peptidase' domain of Spt16

Protein function is encoded in its sequence, manifested in its three-dimensional structure, and facilitated by its dynamics. Studies have suggested that protein structures with higher sequence similarity could have more similar patterns of dynamics. However, such studies of protein dynamics within and across protein families typically rely on coarse-grained models, or approximate metrics like crystallographic B-factors. This study uses µs scale molecular dynamics (MD) simulations to explore the conservation of dynamics among homologs of ∼50 kDa N-terminal module of Spt16 (Spt16N). Spt16N from Saccharomyces cerevisiae (Sc-Spt16N) and three of its homologs with 30-40% sequence identities were available in the PDB. To make our data-set more comprehensive, the crystal structure of an additional homolog (62% sequence identity with Sc-Spt16N) was solved at 1.7 Å resolution. Cumulative MD simulations of 6 µs were carried out on these Spt16N structures and on two additional protein structures with varying degrees of similarity to it. The simulations revealed that correlation in patterns of backbone fluctuations vary linearly with sequence identity. This trend could not be inferred using crystallographic B-factors. Further, normal mode analysis suggested a similar pattern of inter-domain (inter-lobe) motions not only among Spt16N homologs, but also in the M24 peptidase structure. On the other hand, MD simulation results highlighted conserved motions that were found unique for Spt16N protein, this along with electrostatics trends shed light on functional aspects of Spt16N.Communicated by Ramaswamy H. Sarma.

Construction of Covalent Organic Framework Capsule-Based Nanoreactor for Sensitive Glucose Detection

Enzyme immobilization is critical to boosting its application in various areas. Covalent organic frameworks (COFs) are ideal hosts for enzyme immobilization due to their porous and predesignable structures. Nevertheless, the construction of COFs-based enzyme immobilization systems with high activity via existing immobilization methods (including covalent linkages and channel entrapment) remains a considerable challenge. Herein, a versatile approach was introduced to encapsulate enzymes within hollow COF capsule (named enzyme@COF) using metal-organic frameworks (including ZPF-1(C8H11N4O4.5Zn), ZIF-8(C8H10N4Zn), and ZIF-90(C8H6N4O2Zn)) as sacrificial templates. The obtained porous COF capsule could not only facilitate the efficient mass transfer of enzymatic reactions but also protect enzymes against the incompatible conditions, resulting in enhanced activity and stability of the encapsulated enzymes. Moreover, this approach offered an opportunity to spatially organize multienzymes in COF capsule to construct enzyme cascade system. For instance, glucose oxidase (GOx) and cytochrome c (Cyt c) were coencapsulated within COF capsule to construct GOx-Cyt c cascade. The integration of GOx and Cyt c within COF capsule achieved ∼1.6-fold improvement in catalytic activity than that of free enzymes and the resultant GOx-Cyt c@COF was successfully adopted as a nanoreactor for the sensitive determination of glucose in serum. This work provided a new insight into the design of COFs-based enzyme immobilization systems.