Critical analysis of antibody catalysis

Antimicrobial and Anesthetic Niosomal Formulations Based on Amino Acid-Derived Surfactants

BACKGROUND

This work proposes the development of new vesicular systems based on anesthetic compounds (lidocaine (LID) and capsaicin (CA)) and antimicrobial agents (amino acid-based surfactants from phenylalanine), with a focus on physicochemical characterization and the evaluation of antimicrobial and cytotoxic properties.

METHOD

Phenylalanine surfactants were characterized via high-performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR). Different niosomal systems based on capsaicin, lidocaine, cationic phenylalanine surfactants, and dipalmitoyl phosphatidylcholine (DPPC) were characterized in terms of size, polydispersion index (PI), zeta potential, and encapsulation efficiency using dynamic light scattering (DLS), transmitted light microscopy (TEM), and small-angle X-ray scattering (SAXS). Furthermore, the interaction of the pure compounds used to prepare the niosomal formulations with DPPC monolayers was determined using a Langmuir balance. The antibacterial activity of the vesicular systems and their biocompatibility were evaluated, and molecular docking studies were carried out to obtain information about the mechanism by which these compounds interact with bacteria.

RESULTS

The stability and reduced size of the analyzed niosomal formulations demonstrate their potential in pharmaceutical applications. The nanosystems exhibit promising antimicrobial activity, marking a significant advancement in pharmaceutical delivery systems with dual therapeutic properties. The biocompatibility of some formulations underscores their viability.

CONCLUSIONS

The proposed niosomal formulations could constitute an important advance in the pharmaceutical field, offering delivery systems for combined therapies thanks to the pharmacological properties of the individual components.

ACE-2-like enzymatic activity is associated with immunoglobulin in COVID-19 patients

Many mechanisms responsible for COVID-19 pathogenesis are well-established, but COVID-19 includes features with unclear pathogenesis, such as autonomic dysregulation, coagulopathies, and high levels of inflammation. The receptor for the SARS-CoV-2 spike protein receptor-binding domain (RBD) is angiotensin-converting enzyme 2 (ACE2). We hypothesized that some COVID-19 patients may develop antibodies that have a negative molecular image of RBD sufficiently similar to ACE2 to yield ACE2-like catalytic activity-ACE2-like abzymes. To explore this hypothesis, we studied patients hospitalized with COVID-19 who had plasma samples available obtained about 7 days after admission. ACE2 is a metalloprotease that requires Zn2+ for activity. However, we found that the plasma from some patients studied could specifically cleave a synthetic ACE2 peptide substrate, even though the plasma samples were collected using disodium EDTA anticoagulant. When we spiked plasma with synthetic ACE2, no ACE2 substrate cleavage activity was observed unless Zn2+ was added or the plasma was diluted to decrease EDTA concentration. After processing samples by 100 kDa size exclusion columns and protein A/G adsorption, which depleted immunoglobulin by >99.99%, the plasma samples did not cleave the ACE2 substrate peptide. The data suggest that some patients with COVID-19 develop antibodies with abzyme-like activity capable of cleaving synthetic ACE2 substrate. Since abzymes can exhibit promiscuous substrate specificities compared to the enzyme whose active site image they resemble, and since proteolytic cascades regulate many physiologic processes, anti-RBD abzymes may contribute to some otherwise obscure COVID-19 pathogenesis.

IMPORTANCE

We provide what we believe to be the first description of angiotensin-converting enzyme 2 (ACE2)-like enzymatic activity associated with immunoglobulin in COVID-19 patients. COVID-19 includes many puzzling clinical features that have unclear pathogenesis, including a hyperinflammatory state, abnormalities of the clotting cascade, and blood pressure instability. We hypothesized that some patients with COVID-19 patients may produce antibodies against SARS-CoV-2 with enzymatic activity, or abzymes, that target important proteolytic regulatory cascades. The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein binds ACE2 on the surface of the future host cell. This means that the RBD has a negative molecular image of ACE2. We hypothesized that some antibodies produced against the RBD would have, in turn, a negative molecular image of the RBD sufficiently similar to ACE2 to have ACE2-like catalytic activity. In other words, some anti-RBD antibodies would be ACE2-like abzymes. Abzymes elicited by SARS-CoV-2 infection have the potential to affect host physiology.

Rationalizing diverse binding mechanisms to the same protein fold: insights for ligand recognition and biosensor design

The engineering of novel protein-ligand binding interactions, particularly for complex drug-like molecules, is an unsolved problem which could enable many practical applications of protein biosensors. In this work, we analyzed two engineer ed biosensors, derived from the plant hormone sensor PYR1, to recognize either the agrochemical mandipropamid or the synthetic cannabinoid WIN55,212-2. Using a combination of quantitative deep mutational scanning experiments and molecular dynamics simulations, we demonstrated that mutations at common positions can promote protein-ligand shape complementarity and revealed prominent differences in the electrostatic networks needed to complement diverse ligands. MD simulations indicate that both PYR1 protein-ligand complexes bind a single conformer of their target ligand that is close to the lowest free energy conformer. Computational design using a fixed conformer and rigid body orientation led to new WIN55,212-2 sensors with nanomolar limits of detection. This work reveals mechanisms by which the versatile PYR1 biosensor scaffold can bind diverse ligands. This work also provides computational methods to sample realistic ligand conformers and rigid body alignments that simplify the computational design of biosensors for novel ligands of interest.

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

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

Catalytic Antibody Blunts Carfentanil-Induced Respiratory Depression

Carfentanil, the most potent of the fentanyl analogues, is at the forefront of synthetic opioid-related deaths, second to fentanyl. Moreover, the administration of the opioid receptor antagonist naloxone has proven inadequate for an increasing number of opioid-related conditions, often requiring higher/additional doses to be effective, as such interest in alternative strategies to combat more potent synthetic opioids has intensified. Increasing drug metabolism would be one strategy to detoxify carfentanil; however, carfentanil's major metabolic pathways involve N-dealkylation or monohydroxylation, which do not lend themselves readily to exogenous enzyme addition. Herein, we report, to our knowledge, the first demonstration that carfentanil's methyl ester when hydrolyzed to its acid was found to be 40,000 times less potent than carfentanil in activating the μ-opioid receptor. Physiological consequences of carfentanil and its acid were also examined through plethysmography, and carfentanil's acid was found to be incapable of inducing respiratory depression. Based upon this information, a hapten was chemically synthesized and immunized, allowing the generation of antibodies that were screened for carfentanil ester hydrolysis. From the screening campaign, three antibodies were found to accelerate the hydrolysis of carfentanil's methyl ester. From this series of catalytic antibodies, the most active underwent extensive kinetic analysis, allowing us to postulate its mechanism of hydrolysis against this synthetic opioid. In the context of potential clinical applications, the antibody, when passively administered, was able to reduce respiratory depression induced by carfentanil. The data presented supports further development of antibody catalysis as a biologic strategy to complement carfentanil overdose reversal.

Xeno interactions between MHC-I proteins and molecular chaperones enable ligand exchange on a broad repertoire of HLA allotypes

Immunological chaperones tapasin and TAP binding protein, related (TAPBPR) play key roles in antigenic peptide optimization and quality control of nascent class I major histocompatibility complex (MHC-I) molecules. The polymorphic nature of MHC-I proteins leads to a range of allelic dependencies on chaperones for assembly and cell-surface expression, limiting chaperone-mediated peptide exchange to a restricted set of human leukocyte antigen (HLA) allotypes. Here, we demonstrate and characterize xeno interactions between a chicken TAPBPR ortholog and a complementary repertoire of HLA allotypes, relative to its human counterpart. We find that TAPBPR orthologs recognize empty MHC-I with broader allele specificity and facilitate peptide exchange by maintaining a reservoir of receptive molecules. Deep mutational scanning of human TAPBPR further identifies gain-of-function mutants, resembling the chicken sequence, which can enhance HLA-A*01:01 expression in situ and promote peptide exchange in vitro. These results highlight that polymorphic sites on MHC-I and chaperone surfaces can be engineered to manipulate their interactions, enabling chaperone-mediated peptide exchange on disease-relevant HLA alleles.

Biomedical Applications of Microfluidic Devices: A Review

Both passive and active microfluidic chips are used in many biomedical and chemical applications to support fluid mixing, particle manipulations, and signal detection. Passive microfluidic devices are geometry-dependent, and their uses are rather limited. Active microfluidic devices include sensors or detectors that transduce chemical, biological, and physical changes into electrical or optical signals. Also, they are transduction devices that detect biological and chemical changes in biomedical applications, and they are highly versatile microfluidic tools for disease diagnosis and organ modeling. This review provides a comprehensive overview of the significant advances that have been made in the development of microfluidics devices. We will discuss the function of microfluidic devices as micromixers or as sorters of cells and substances (e.g., microfiltration, flow or displacement, and trapping). Microfluidic devices are fabricated using a range of techniques, including molding, etching, three-dimensional printing, and nanofabrication. Their broad utility lies in the detection of diagnostic biomarkers and organ-on-chip approaches that permit disease modeling in cancer, as well as uses in neurological, cardiovascular, hepatic, and pulmonary diseases. Biosensor applications allow for point-of-care testing, using assays based on enzymes, nanozymes, antibodies, or nucleic acids (DNA or RNA). An anticipated development in the field includes the optimization of techniques for the fabrication of microfluidic devices using biocompatible materials. These developments will increase biomedical versatility, reduce diagnostic costs, and accelerate diagnosis time of microfluidics technology.

Estimating conformational heterogeneity of tryptophan synthase with a template‐based Alphafold2 approach

The three‐dimensional structure of the enzymes provides very relevant information on the arrangement of the catalytic machinery and structural elements gating the active site pocket. The recent success of the neural network Alphafold2 in predicting the folded structure of proteins from the primary sequence with high levels of accuracy has revolutionized the protein design field. However, the application of Alphafold2 for understanding and engineering function directly from the obtained single static picture is not straightforward. Indeed, understanding enzymatic function requires the exploration of the ensemble of thermally accessible conformations that enzymes adopt in solution. In the present study, we evaluate the potential of Alphafold2 in assessing the effect of the mutations on the conformational landscape of the beta subunit of tryptophan synthase (TrpB). Specifically, we develop a template‐based Alphafold2 approach for estimating the conformational heterogeneity of several TrpB enzymes, which is needed for enhanced stand‐alone activity. Our results show the potential of Alphafold2, especially if combined with molecular dynamics simulations, for elucidating the changes induced by mutation in the conformational landscapes at a rather reduced computational cost, thus revealing its plausible application in computational enzyme design.

The road to fully programmable protein catalysis

The ability to design efficient enzymes from scratch would have a profound effect on chemistry, biotechnology and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes containing metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive laboratory evolution has been used to generate efficient enzymes. Structural analysis of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.

Essential Protective Role of Catalytically Active Antibodies (Abzymes) with Redox Antioxidant Functions in Animals and Humans

During the life of aerobic organisms, the oxygen resulting from numerous reactions is converted into reactive oxygen species (ROS). Many ROS are dangerous due to their high reactivity; they are strong oxidants, and react with various cell components, leading to their damage. To protect against ROS overproduction, enzymatic and non-enzymatic systems are evolved in aerobic cells. Several known non-enzymatic antioxidants have a relatively low specific antioxidant activity. Superoxide dismutases, catalase, glutathione peroxidase, glutathione S-transferase, thioredoxin, and the peroxiredoxin families are the most important enzyme antioxidants. Artificial antibodies catalyzing redox reactions using different approaches have been created. During the past several decades, it has been shown that the blood and various biological fluids of humans and animals contain natural antibodies that catalyze different redox reactions, such as classical enzymes. This review, for the first time, summarizes data on existing non-enzymatic antioxidants, canonical enzymes, and artificial or natural antibodies (abzymes) with redox functions. Comparing abzymes with superoxide dismutase, catalase, peroxide-dependent peroxidase, and H₂O₂-independent oxidoreductase activities with the same activities as classical enzymes was carried out. The features of abzymes with the redox activities are described, including their exceptional diversity in the optimal pH values, dependency and independence on various metal ions, and the reaction rate constants for healthy donors and patients with different autoimmune diseases. The entire body of evidence indicates that abzymes with redox antioxidant activities existing in the blood for a long time compared to enzymes are an essential part of the protection system of humans and animals from oxidative stress.

Single-Molecule Sampling of Dihydrofolate Reductase Shows Kinetic Pauses and an Endosteric Effect Linked to Catalysis

The ability to sample multiple reactions on the same single enzyme is important to link rare intermediates with catalysis and to unravel the role of conformational changes. Despite decades of efforts, however, the single-molecule characterization of nonfluorogenic enzymes during multiple catalytic turnovers has been elusive. Here, we show that nanopore currents allow sampling the dynamic exchange between five structural intermediates during E. coli dihydrofolate reductase (DHFR) catalysis. We found that an endosteric effect promotes the binding of the substrate to the enzyme with a specific hierarchy. The chemical step then switched the enzyme from the closed to the occluded conformation, which in turn promotes the release of the reduced cofactor NADP⁺. Unexpectedly, only a few reactive complexes lead to catalysis. Furthermore, second-long catalytic pauses were observed, possibly reflecting an off-path conformation generated during the reaction. Finally, the free energy from multiple cofactor binding events were required to release the product and switch DHFR back to the reactive conformer. This catalytic fueled concerted mechanism is likely to have evolved to improve the catalytic efficiency of DHFR under the high concentrations of NADP⁺ in E. coli and might be a general feature for complex enzymatic reactions where the binding and release of the products must be tightly controlled.

Pharmacokinetic Approach to Combat the Synthetic Cannabinoid PB-22

Synthetic cannabinoids are part of a group of drugs called new psychoactive substances. Most of these cannabinoids are unregulated, and there are no therapeutic treatments for their addictive properties or reversing a potential overdose. Vaccination and catalytic antibodies strategies were investigated to assess their ability to blunt the psychoactive properties of the cannabinoid PB-22. To complement these antibody concentric investigations, we also disclose the discovery of the enzymatic degradation of this cannabinoid. Serum factors including albumin and carboxylesterase were found to catalyze the hydrolysis of PB-22. Affinity, kinetics, animal behavior, and biodistribution studies were utilized to evaluate the efficiency of these pharmacokinetic approaches. Our findings suggest simple antibody binding as the most efficacious means for altering PB-22's effect on the brain. Catalytic approaches only translated to esterases being capable of PB-22's degradation with a catalytic antibody approach providing no proclivity for PB-22's hydrolysis. Pharmacokinetic approaches provide a powerful strategy for treating substance abuse disorders and overdose for drugs where no therapeutic is available.

A QM/MM study on the origin of retro-aldolase activity of a catalytic antibody

The retro-aldolase mechanism of methodol catalysed by the catalytic antibody 33F12 is described based on the exploration of the free energy landscape obtained with QM/MM methods. The amino acids involved in the reaction have been identified, as well as their specific role played in the active site and in the flexibility of the loops. Finally, the comparison with a de novo enzyme RA95.5-8F provides a deeper understanding of catalytic differences between such different protein scaffolds.

Geometry and Flexibility of Optimal Catalysts in a Minimal Elastic Model

We have general knowledge of the principles by which catalysts accelerate the rate of chemical reactions but no precise understanding of the geometrical and physical constraints to which their design is subject. To analyze these constraints, we introduce a minimal model of catalysis based on elastic networks where the implications of the geometry and flexibility of a catalyst can be studied systematically. The model demonstrates the relevance and limitations of the principle of transition-state stabilization: optimal catalysts are found to have a geometry complementary to the transition state but a degree of flexibility that nontrivially depends on the parameters of the reaction as well as on external parameters such as the concentrations of reactants and products. The results illustrate how simple physical models can provide valuable insights into the design of catalysts.

Chemical Synthesis of an Enzyme Containing an Artificial Catalytic Apparatus

With the goal of investigating electronic aspects of the catalysis of peptide bond hydrolysis, an analogue of HIV-1 protease was designed in which a non-peptide hydroxy-isoquinolinone artificial catalytic apparatus replaced the conserved Asp25–Thr26–Gly27 sequence in each 99-residue polypeptide chain of the homodimeric enzyme molecule. The enzyme analogue was prepared by total chemical synthesis and had detectable catalytic activity on known HIV-1 protease peptide substrates. Compared with uncatalyzed hydrolysis, the analogue enzyme increased the rate of peptide bond hydrolysis by ∼108-fold. Extensions of this unique approach to the study of enzyme catalysis in HIV-1 protease are discussed.

Heavy Enzymes and the Rational Redesign of Protein Catalysts

An unsolved mystery in biology concerns the link between enzyme catalysis and protein motions. Comparison between isotopically labelled "heavy" dihydrofolate reductases and their natural-abundance counterparts has suggested that the coupling of protein motions to the chemistry of the catalysed reaction is minimised in the case of hydride transfer. In alcohol dehydrogenases, unnatural, bulky substrates that induce additional electrostatic rearrangements of the active site enhance coupled motions. This finding could provide a new route to engineering enzymes with altered substrate specificity, because amino acid residues responsible for dynamic coupling with a given substrate present as hotspots for mutagenesis. Detailed understanding of the biophysics of enzyme catalysis based on insights gained from analysis of "heavy" enzymes might eventually allow routine engineering of enzymes to catalyse reactions of choice.

The Intrinsically Disordered Loop in the USF1 bHLHZ Domain Modulates Its DNA-Binding Sequence Specificity in Hereditary Asthma

USF1, a basic region/helix-loop-helix/leucine zipper (bHLHZ) transcription factor, binds to the E-box in the PAI-1 (plasminogen activator inhibitor) promoter. Two alleles containing the E-box control PAI-1 transcription; these alleles are termed "4G" and "5G" based on the G tract flanking E-box. USF1-governed transcription of PAI-1 is elevated in heritable asthma sufferers: the 4G/4G genotype has the highest plasma levels of PAI-1. While USF1 uses its basic region to bind E-box, we found that it uses its 12 amino-acid loop to recognize the flanking sequence and discern the single-nucleotide difference between the alleles. We used the bacterial one-hybrid and electrophoretic mobility shift assays to assess protein-DNA recognition, and circular dichroism to examine protein secondary structure. We mutated Ser233 and Thr234 in the USF1 bHLHZ loop to Ala to generate S233A and T234A. Interestingly, USF1 bHLHZ, S233A, and T234A prefer the 5G sequence (USF1 bHLHZ K_d values 4.1 ± 0.3 nM and 7.0 ± 0.4 nM for 5G and 4G, respectively), whereas studies in stimulated human mast cells showed a preference for 4G. We replaced the 8 amino-acid loop of transcription factor Max bHLHZ with the 12 amino-acid USF1 loop: this mutant now distinguishes the 4G/5G polymorphism-while Max bHLHZ does not-confirming that USF1 differentiation of the 4G/5G is driven by the loop.

An Ab Initio QM/MM Study of the Electrostatic Contribution to Catalysis in the Active Site of Ketosteroid Isomerase

The electric field in the hydrogen-bond network of the active site of ketosteroid isomerase (KSI) has been experimentally measured using vibrational Stark effect (VSE) spectroscopy, and utilized to study the electrostatic contribution to catalysis. A large gap was found in the electric field between the computational simulation based on the Amber force field and the experimental measurement. In this work, quantum mechanical (QM) calculations of the electric field were performed using an ab initio QM/MM molecular dynamics (MD) simulation and electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method. Our results demonstrate that the QM-derived electric field based on the snapshots from QM/MM MD simulation could give quantitative agreement with the experiment. The accurate calculation of the electric field inside the protein requires both the rigorous sampling of configurations, and a QM description of the electrostatic field. Based on the direct QM calculation of the electric field, we theoretically confirmed that there is a linear correlation relationship between the activation free energy and the electric field in the active site of wild-type KSI and its mutants (namely, D103N, Y16S, and D103L). Our study presents a computational protocol for the accurate simulation of the electric field in the active site of the protein, and provides a theoretical foundation that supports the link between electric fields and enzyme catalysis.

A designer enzyme for hydrazone and oxime formation featuring an unnatural catalytic aniline residue

Creating designer enzymes with the ability to catalyse abiological transformations is a formidable challenge. Efforts toward this goal typically consider only canonical amino acids in the initial design process. However, incorporating unnatural amino acids that feature uniquely reactive side chains could significantly expand the catalytic repertoire of designer enzymes. To explore the potential of such artificial building blocks for enzyme design, here we selected p-aminophenylalanine as a potentially novel catalytic residue. We demonstrate that the catalytic activity of the aniline side chain for hydrazone and oxime formation reactions is increased by embedding p-aminophenylalanine into the hydrophobic pore of the multidrug transcriptional regulator from Lactococcus lactis. Both the recruitment of reactants by the promiscuous binding pocket and a judiciously placed aniline that functions as a catalytic residue contribute to the success of the identified artificial enzyme. We anticipate that our design strategy will prove rewarding to significantly expand the catalytic repertoire of designer enzymes in the future.

Predictive methods for computational metalloenzyme redesign - a test case with carboxypeptidase A

Computational metalloenzyme design is a multi-scale problem. It requires treating the metal coordination quantum mechanically, extensive sampling of the protein backbone, and additionally accounting for the polarization of the active site by both the metal cation and the surrounding protein (a phenomenon called electrostatic preorganization). We bring together a combination of theoretical methods that jointly offer these desired qualities: QM/DMD for mixed quantum-classical dynamic sampling, quantum theory of atoms in molecules (QTAIM) for the assessment of electrostatic preorganization, and Density Functional Theory (DFT) for mechanistic studies. Within this suite of principally different methods, there are both complementarity of capabilities and cross-validation. Using these methods, predictions can be made regarding the relative activities of related enzymes, as we show on the native Zn²⁺-dependent carboxypeptidase A (CPA), and its mutant proteins, which are hypothesized to hydrolyze modified substrates. For the native CPA, we replicated the catalytic mechanism and the rate in close agreement with the experiment, giving validity to the QM/DMD predicted structure, the DFT mechanism, and the QTAIM assessment of catalytic activity. For most sequences of the modified substrate and tried CPA mutants, substantially worsened activity is predicted. However, for the substrate mutant that contains Asp instead of Phe at the C-terminus, one CPA mutant exhibits a reasonable activity, as predicted across the theoretical methods. CPA is a well-studied system, and here it serves as a testing ground for the offered methods.

Antibody-Mediated Catalysis in Infection and Immunity

The existence of catalytic antibodies has been known for decades. Natural antibodies capable of cleaving nucleic acid, protein, and polysaccharide substrates have been described. Although the discovery of catalytic antibodies initially aroused great interest because of their promise for the development of new catalysts, their enzymatic performance has been disappointing due to low reaction rates. However, in the areas of infection and immunity, where processes often occur over much longer times and involve high antibody concentrations, even low catalytic rates have the potential to influence biological outcomes. In this regard, the presence of catalytic antibodies recognizing host antigens has been associated with several autoimmune diseases. Furthermore, naturally occurring catalytic antibodies to microbial determinants have been correlated with resistance to infection. Recently, there has been substantial interest in harnessing the power of antibody-mediated catalysis against microbial antigens for host defense. Additional work is needed, however, to better understand the prevalence, function, and structural basis of catalytic activity in antibodies. Here we review the available information and suggest that antibody-mediated catalysis is a fertile area for study with broad applications in infection and immunity.

Artificial Metalloenzymes: Reaction Scope and Optimization Strategies

The incorporation of a synthetic, catalytically competent metallocofactor into a protein scaffold to generate an artificial metalloenzyme (ArM) has been explored since the late 1970's. Progress in the ensuing years was limited by the tools available for both organometallic synthesis and protein engineering. Advances in both of these areas, combined with increased appreciation of the potential benefits of combining attractive features of both homogeneous catalysis and enzymatic catalysis, led to a resurgence of interest in ArMs starting in the early 2000's. Perhaps the most intriguing of potential ArM properties is their ability to endow homogeneous catalysts with a genetic memory. Indeed, incorporating a homogeneous catalyst into a genetically encoded scaffold offers the opportunity to improve ArM performance by directed evolution. This capability could, in turn, lead to improvements in ArM efficiency similar to those obtained for natural enzymes, providing systems suitable for practical applications and greater insight into the role of second coordination sphere interactions in organometallic catalysis. Since its renaissance in the early 2000's, different aspects of artificial metalloenzymes have been extensively reviewed and highlighted. Our intent is to provide a comprehensive overview of all work in the field up to December 2016, organized according to reaction class. Because of the wide range of non-natural reactions catalyzed by ArMs, this was done using a functional-group transformation classification. The review begins with a summary of the proteins and the anchoring strategies used to date for the creation of ArMs, followed by a historical perspective. Then follows a summary of the reactions catalyzed by ArMs and a concluding critical outlook. This analysis allows for comparison of similar reactions catalyzed by ArMs constructed using different metallocofactor anchoring strategies, cofactors, protein scaffolds, and mutagenesis strategies. These data will be used to construct a searchable Web site on ArMs that will be updated regularly by the authors.

Synthetic, Switchable Enzymes

The construction of switchable, radiation-controlled, aptameric enzymes - "swenzymes" - is, in principle, feasible. We propose a strategy to make such catalysts from 2 (or more) aptamers each selected to bind specifically to one of the substrates in, for example, a 2-substrate reaction. Construction of a combinatorial library of candidate swenzymes entails selecting a set of a million aptamers that bind one substrate and a second set of a million aptamers that bind the second substrate; the aptamers in these sets are then linked pairwise by a linker, thus bringing together the substrates. In the presence of the substrates, some linked aptamer pairs catalyze the reaction when exposed to external energy in the form of a specific frequency of low-intensity, nonionizing electromagnetic or acoustic radiation. Such swenzymes are detected via a separate product-capturing aptamer that changes conformation on capturing the product; this altered conformation allows it (1) to bind to every potential swenzyme in its vicinity (thereby giving a higher probability of capture to the swenzymes that generate the product) and (2) to bind to a sequence on a magnetic bead (thereby permitting purification of the swenzyme plus product-capturing aptamer by precipitation). Attempts to implement the swenzyme strategy may help elucidate fundamental problems in enzyme catalysis.

Multitarget selection of catalytic antibodies with β-lactamase activity using phage display

β-lactamase enzymes responsible for bacterial resistance to antibiotics are among the most important health threats to the human population today. Understanding the increasingly vast structural motifs responsible for the catalytic mechanism of β-lactamases will help improve the future design of new generation antibiotics and mechanism-based inhibitors of these enzymes. Here we report the construction of a large murine single chain fragment variable (scFv) phage display library of size 2.7 × 10⁹ with extended diversity by combining different mouse models. We have used two molecularly different inhibitors of the R-TEM β-lactamase as targets for selection of catalytic antibodies with β-lactamase activity. This novel methodology has led to the isolation of five antibody fragments, which are all capable of hydrolyzing the β-lactam ring. Structural modeling of the selected scFv has revealed the presence of different motifs in each of the antibody fragments potentially responsible for their catalytic activity. Our results confirm (a) the validity of using our two target inhibitors for the in vitro selection of catalytic antibodies endowed with β-lactamase activity, and (b) the plasticity of the β-lactamase active site responsible for the wide resistance of these enzymes to clinically available inhibitors and antibiotics.

Robotic QM/MM-driven maturation of antibody combining sites

In vitro selection of antibodies from large repertoires of immunoglobulin (Ig) combining sites using combinatorial libraries is a powerful tool, with great potential for generating in vivo scavengers for toxins. However, addition of a maturation function is necessary to enable these selected antibodies to more closely mimic the full mammalian immune response. We approached this goal using quantum mechanics/molecular mechanics (QM/MM) calculations to achieve maturation in silico. We preselected A17, an Ig template, from a naïve library for its ability to disarm a toxic pesticide related to organophosphorus nerve agents. Virtual screening of 167,538 robotically generated mutants identified an optimum single point mutation, which experimentally boosted wild-type Ig scavenger performance by 170-fold. We validated the QM/MM predictions via kinetic analysis and crystal structures of mutant apo-A17 and covalently modified Ig, thereby identifying the displacement of one water molecule by an arginine as delivering this catalysis.

Quantum mechanical calculation of electric fields and vibrational Stark shifts at active site of human aldose reductase

Recent advance in biophysics has made it possible to directly measure site-specific electric field at internal sites of proteins using molecular probes with C = O or C≡N groups in the context of vibrational Stark effect. These measurements directly probe changes of electric field at specific protein sites due to, e.g., mutation and are very useful in protein design. Computational simulation of the Stark effect based on force fields such as AMBER and OPLS, while providing good insight, shows large errors in comparison to experimental measurement due to inherent difficulties associated with point charge based representation of force fields. In this study, quantum mechanical calculation of protein's internal electrostatic properties and vibrational Stark shifts was carried out by using electrostatically embedded generalized molecular fractionation with conjugate caps method. Quantum calculated change of mutation-induced electric field and vibrational Stark shift is reported at the internal probing site of enzyme human aldose reductase. The quantum result is in much better agreement with experimental data than those predicted by force fields, underscoring the deficiency of traditional point charge models describing intra-protein electrostatic properties.

Use of an Improved Matching Algorithm to Select Scaffolds for Enzyme Design Based on a Complex Active Site Model

Active site preorganization helps native enzymes electrostatically stabilize the transition state better than the ground state for their primary substrates and achieve significant rate enhancement. In this report, we hypothesize that a complex active site model for active site preorganization modeling should help to create preorganized active site design and afford higher starting activities towards target reactions. Our matching algorithm ProdaMatch was improved by invoking effective pruning strategies and the native active sites for ten scaffolds in a benchmark test set were reproduced. The root-mean squared deviations between the matched transition states and those in the crystal structures were < 1.0 Å for the ten scaffolds, and the repacking calculation results showed that 91% of the hydrogen bonds within the active sites are recovered, indicating that the active sites can be preorganized based on the predicted positions of transition states. The application of the complex active site model for de novo enzyme design was evaluated by scaffold selection using a classic catalytic triad motif for the hydrolysis of p-nitrophenyl acetate. Eighty scaffolds were identified from a scaffold library with 1,491 proteins and four scaffolds were native esterase. Furthermore, enzyme design for complicated substrates was investigated for the hydrolysis of cephalexin using scaffold selection based on two different catalytic motifs. Only three scaffolds were identified from the scaffold library by virtue of the classic catalytic triad-based motif. In contrast, 40 scaffolds were identified using a more flexible, but still preorganized catalytic motif, where one scaffold corresponded to the α-amino acid ester hydrolase that catalyzes the hydrolysis and synthesis of cephalexin. Thus, the complex active site modeling approach for de novo enzyme design with the aid of the improved ProdaMatch program is a promising approach for the creation of active sites with high catalytic efficiencies towards target reactions.

Fast, cheap and out of control--Insights into thermodynamic and informatic constraints on natural protein sequences from de novo protein design

The accumulated results of thirty years of rational and computational de novo protein design have taught us important lessons about the stability, information content, and evolution of natural proteins. First, de novo protein design has complicated the assertion that biological function is equivalent to biological structure - demonstrating the capacity to abstract active sites from natural contexts and paste them into non-native topologies without loss of function. The structure-function relationship has thus been revealed to be either a generality or strictly true only in a local sense. Second, the simplification to "maquette" topologies carried out by rational protein design also has demonstrated that even sophisticated functions such as conformational switching, cooperative ligand binding, and light-activated electron transfer can be achieved with low-information design approaches. This is because for simple topologies the functional footprint in sequence space is enormous and easily exceeds the number of structures which could have possibly existed in the history of life on Earth. Finally, the pervasiveness of extraordinary stability in designed proteins challenges accepted models for the "marginal stability" of natural proteins, suggesting that there must be a selection pressure against highly stable proteins. This can be explained using recent theories which relate non-equilibrium thermodynamics and self-replication. This article is part of a Special Issue entitled Biodesign for Bioenergetics--The design and engineering of electronc transfer cofactors, proteins and protein networks, edited by Ronald L. Koder and J.L. Ross Anderson.

Nonequilibrium Relaxation of Conformational Dynamics Facilitates Catalytic Reaction in an Elastic Network Model of T7 DNA Polymerase

Nucleotide-induced conformational closing of the finger domain of DNA polymerase is crucial for its catalytic action during DNA replication. Such large-amplitude molecular motion is often not fully accessible to either direct experimental monitoring or molecular dynamics simulations. However, a coarse-grained model can offer an informative alternative, especially for probing the relationship between conformational dynamics and catalysis. Here we investigate the dynamics of T7 DNA polymerase catalysis using a Langevin-type elastic network model incorporating detailed structural information on the open conformation without the substrate bound. Such a single-parameter model remarkably captures the induced conformational dynamics of DNA polymerase upon dNTP binding, and reveals its close coupling to the advancement toward transition state along the coordinate of the target reaction, which contributes to significant lowering of the activation energy barrier. Furthermore, analysis of stochastic catalytic rates suggests that when the activation energy barrier has already been significantly lowered and nonequilibrium relaxation toward the closed form dominates the catalytic rate, one must appeal to a picture of two-dimensional free energy surface in order to account for the full spectrum of catalytic modes. Our semiquantitative study illustrates the general role of conformational dynamics in achieving transition-state stabilization, and suggests that such an elastic network model, albeit simplified, possesses the potential to furnish significant mechanistic insights into the functioning of a variety of enzymatic systems.

Computational Tools Applied to Enzyme Design − a review

The protein design toolbox has been greatly improved by the addition of enzyme computational simulations. Not only do they warrant a more ambitious and thorough exploration of sequence space, but a much higher number of variants and protein-ligand systems can be analyzed in silico compared to experimental engineering methods. Modern computational tools are being used to redesign and also for de novo generation of enzymes. These approaches are contingent on a deep understanding of the reaction mechanism and the enzyme’s three-dimensional structure coordinates, but the wealth of information produced by these analyses leads to greatly improved or even totally new types of catalysis.

Computational Studies of Candida Antarctica Lipase B to Test Its Capability as a Starting Point To Redesign New Diels-Alderases

The design of new biocatalysts is a target that is receiving increasing attention. One of the most popular reactions in this regard is the Diels-Alder cycloaddition because of its applications in organic synthesis and the absence of efficient natural enzymes that catalyze it. In this paper, the possibilities of using the highly promiscuous Candida Antarctica lipase B as a protein scaffold to redesign a Diels-Alderase has been explored by means of theoretical quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulations. Free energy surfaces have been computed for two reactions in the wild-type and in several mutants with hybrid AM1/MM potentials with corrections at M06-2X/MM level. The study of the counterpart reactions in solution has allowed performing comparative analysis that render interesting conclusions. Since the dienophile anchors very well in the oxyanion hole of all tested protein variants, the slight electronic changes from reactant complex to the transition state suggest that mutations should be focused in favoring the formation of reactive conformations of a reactant complex that, in turn, would reduce the energy barrier.

Microfluidics Integrated Biosensors: A Leading Technology towards Lab-on-a-Chip and Sensing Applications

A biosensor can be defined as a compact analytical device or unit incorporating a biological or biologically derived sensitive recognition element immobilized on a physicochemical transducer to measure one or more analytes. Microfluidic systems, on the other hand, provide throughput processing, enhance transport for controlling the flow conditions, increase the mixing rate of different reagents, reduce sample and reagents volume (down to nanoliter), increase sensitivity of detection, and utilize the same platform for both sample preparation and detection. In view of these advantages, the integration of microfluidic and biosensor technologies provides the ability to merge chemical and biological components into a single platform and offers new opportunities for future biosensing applications including portability, disposability, real-time detection, unprecedented accuracies, and simultaneous analysis of different analytes in a single device. This review aims at representing advances and achievements in the field of microfluidic-based biosensing. The review also presents examples extracted from the literature to demonstrate the advantages of merging microfluidic and biosensing technologies and illustrate the versatility that such integration promises in the future biosensing for emerging areas of biological engineering, biomedical studies, point-of-care diagnostics, environmental monitoring, and precision agriculture.

Chemomimetic biocatalysis: exploiting the synthetic potential of cofactor-dependent enzymes to create new catalysts

Despite the astonishing breadth of enzymes in nature, no enzymes are known for many of the valuable catalytic transformations discovered by chemists. Recent work in enzyme design and evolution, however, gives us good reason to think that this will change. We describe a chemomimetic biocatalysis approach that draws from small-molecule catalysis and synthetic chemistry, enzymology, and molecular evolution to discover or create enzymes with non-natural reactivities. We illustrate how cofactor-dependent enzymes can be exploited to promote reactions first established with related chemical catalysts. The cofactors can be biological, or they can be non-biological to further expand catalytic possibilities. The ability of enzymes to amplify and precisely control the reactivity of their cofactors together with the ability to optimize non-natural reactivity by directed evolution promises to yield exceptional catalysts for challenging transformations that have no biological counterparts.

Various strategies for obtaining oxidative artificial hemoproteins with a catalytic oxidative activity: from "Hemoabzymes" to "Hemozymes"?

The design of artificial hemoproteins that could lead to new biocatalysts for selective oxidation reactions using clean oxidants such as O 2 or H 2 O 2 under ecocompatible conditions constitutes a really promising challenge for a wide range of industrial applications. In vivo, such reactions are performed by heme-thiolate proteins, cytochromes P450, that catalyze the oxidation of drugs by dioxygen in the presence of electrons delivered from NADPH by cytochrome P450 reductase. Several strategies were used to design new artificial hemoproteins to mimic these enzymes, that associate synthetic metalloporphyrin derivatives to a protein that is supposed to induce a selectivity in the catalyzed reaction. A first generation of artificial hemoproteins or "hemoabzymes" was obtained by the non-covalent association of synthetic hemes such as N-methyl-mesoporphyrin IX, Fe(III) -α3β-tetra-o-carboxyphenylporphyrin or microperoxidase 8 with monoclonal antibodies raised against these cofactors. The obtained antibody-metalloporphyrin complexes displayed a peroxidase activity and some of them catalyzed the regio-selective nitration of phenols by H 2 O 2/ NO 2 and the stereo-selective oxidation of sulphides by H 2 O 2. A second generation of artificial hemoproteins or "hemozymes", was obtained by the non-covalent association of non-relevant proteins with metalloporphyrin derivatives. Several strategies were used, the most successful of which, named "host-guest" strategy involved the non-covalent incorporation of metalloporphyrin derivatives into easily affordable proteins. The artificial hemoproteins obtained were found to be able to perform efficiently the stereoselective oxidation of organic compounds such as sulphides and alkenes by H 2 O 2 and KHSO 5.

Design of an allosterically regulated retroaldolase

We employed a minimalist approach for design of an allosterically controlled retroaldolase. Introduction of a single lysine residue into the nonenzymatic protein calmodulin led to a 15,000-fold increase in the second order rate constant for retroaldol reaction with methodol as a substrate. The resulting catalyst AlleyCatR is active enough for subsequent directed evolution in crude cell bacterial lysates. AlleyCatR's activity is allosterically regulated by Ca(2+) ions. No catalysis is observed in the absence of the metal ion. The increase in catalytic activity originates from the hydrophobic interaction of the substrate (∼2000-fold) and the change in the apparent pKa of the active lysine residue.

From “hemoabzymes” to “hemozymes”: towards new biocatalysts for selective oxidations

Two generations of artificial hemoproteins have been obtained: “hemoabzymes”, by non-covalent association of synthetic hemes with monoclonal antibodies raised against these cofactors and “hemozymes”, by non-covalent association of non-relevant proteins with metalloporphyrin derivatives. A review of the different strategies employed as well as their structural and catalytic properties is presented here.

Enzyme immunoassays as screening tools for catalysts and reaction discovery

This feature article summarizes the development and use of immunoassay techniques (ELISA) as screening tools for fast identification of efficient catalysts in libraries and for the discovery of new chemical reactions.

Electrostatic transition state stabilization rather than reactant destabilization provides the chemical basis for efficient chorismate mutase catalysis

For more than half a century, transition state theory has provided a useful framework for understanding the origins of enzyme catalysis. As proposed by Pauling, enzymes accelerate chemical reactions by binding transition states tighter than substrates, thereby lowering the activation energy compared with that of the corresponding uncatalyzed process. This paradigm has been challenged for chorismate mutase (CM), a well-characterized metabolic enzyme that catalyzes the rearrangement of chorismate to prephenate. Calculations have predicted the decisive factor in CM catalysis to be ground state destabilization rather than transition state stabilization. Using X-ray crystallography, we show, in contrast, that a sluggish variant of Bacillus subtilis CM, in which a cationic active-site arginine was replaced by a neutral citrulline, is a poor catalyst even though it effectively preorganizes chorismate for the reaction. A series of high-resolution molecular snapshots of the reaction coordinate, including the apo enzyme, and complexes with substrate, transition state analog and product, demonstrate that an active site, which is only complementary in shape to a reactive substrate conformer, is insufficient for effective catalysis. Instead, as with other enzymes, electrostatic stabilization of the CM transition state appears to be crucial for achieving high reaction rates.

Transient substrate-induced catalyst formation in a dynamic molecular network

In biology enzyme concentrations are continuously regulated, yet for synthetic catalytic systems such regulatory mechanisms are underdeveloped. We now report how a substrate of a chemical reaction induces the formation of its own catalyst from a dynamic molecular network. After complete conversion of the substrate, the network disassembles the catalyst. These results open up new opportunities for controlling catalysis in synthetic chemical systems.

Computer aided enzyme design and catalytic concepts

Gaining a deeper understanding of enzyme catalysis is of great practical and fundamental importance. Over the years it has become clear that despite advances made in experimental mutational studies, a quantitative understanding of enzyme catalysis will not be possible without the use of computer modeling approaches. While we believe that electrostatic preorganization is by far the most important catalytic factor, convincing the wider scientific community of this may require the demonstration of effective rational enzyme design. Here we make the point that the main current advances in enzyme design are basically advances in directed evolution and that computer aided enzyme design must involve approaches that can reproduce catalysis in well-defined test cases. Such an approach is provided by the empirical valence bond method.

Catalytic efficiency of designed catalytic proteins

The de novo design of catalysts that mimic the affinity and specificity of natural enzymes remains one of the Holy Grails of chemistry. Despite decades of concerted effort we are still unable to design catalysts as efficient as enzymes. Here we critically evaluate approaches to (re)design of novel catalytic function in proteins using two test cases: Kemp elimination and ester hydrolysis. We show that the degree of success thus far has been modest when the rate enhancements seen for the designed proteins are compared with the rate enhancements by small molecule catalysts in solvents with properties similar to the active site. Nevertheless, there are reasons for optimism: the design methods are ever improving and the resulting catalyst can be efficiently improved using directed evolution.