On the generation of catalytic antibodies by transition state analogues

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.

Globally Optimal Catalytic Fields - Inverse Design of Abstract Embeddings for Maximum Reaction Rate Acceleration

The search for, and understanding of, good catalysts for chemical reactions is a central issue for chemists. Here, we present first steps toward developing a general computational framework to better support this task. This framework combines efficient, unbiased global optimization techniques with an abstract representation of the catalytic environment, to shrink the search space. To analyze the resulting catalytic embeddings, we employ dimensionality reduction and clustering techniques. This not only provides an inverse design approach to new catalytic embeddings but also illuminates the actual interactions behind catalytic effects. All this is illustrated here with a strictly electrostatic model for the environment and with two versions of a selected example reaction. We close with detailed discussions of future improvements of our framework.

Thermodynamic framework for identifying free energy inventories of enzyme catalytic cycles

Pauling's suggestion that enzymes are complementary in structure to the activated complexes of the reactions they catalyze has provided the conceptual basis to explain how enzymes obtain their fantastic catalytic prowess, and has served as a guiding principle in drug design for over 50 y. However, this model by itself fails to predict the magnitude of enzymes' rate accelerations. We construct a thermodynamic framework that begins with the classic concept of differential binding but invokes additional terms that are needed to account for subtle effects in the catalytic cycle's proton inventory. Although the model presented can be applied generally, this analysis focuses on ketosteroid isomerase (KSI) as an example, where recent experiments along with a large body of kinetic and thermodynamic data have provided strong support for the noncanonical thermodynamic contribution described. The resulting analysis precisely predicts the free energy barrier of KSI's reaction as determined from transition-state theory using only empirical thermodynamic data. This agreement is suggestive that a complete free energy inventory of the KSI catalytic cycle has been identified.

Why nature really chose phosphate

Phosphoryl transfer plays key roles in signaling, energy transduction, protein synthesis, and maintaining the integrity of the genetic material. On the surface, it would appear to be a simple nucleophile displacement reaction. However, this simplicity is deceptive, as, even in aqueous solution, the low-lying d-orbitals on the phosphorus atom allow for eight distinct mechanistic possibilities, before even introducing the complexities of the enzyme catalyzed reactions. To further complicate matters, while powerful, traditional experimental techniques such as the use of linear free-energy relationships (LFER) or measuring isotope effects cannot make unique distinctions between different potential mechanisms. A quarter of a century has passed since Westheimer wrote his seminal review, 'Why Nature Chose Phosphate' (Science 235 (1987), 1173), and a lot has changed in the field since then. The present review revisits this biologically crucial issue, exploring both relevant enzymatic systems as well as the corresponding chemistry in aqueous solution, and demonstrating that the only way key questions in this field are likely to be resolved is through careful theoretical studies (which of course should be able to reproduce all relevant experimental data). Finally, we demonstrate that the reason that nature really chose phosphate is due to interplay between two counteracting effects: on the one hand, phosphates are negatively charged and the resulting charge-charge repulsion with the attacking nucleophile contributes to the very high barrier for hydrolysis, making phosphate esters among the most inert compounds known. However, biology is not only about reducing the barrier to unfavorable chemical reactions. That is, the same charge-charge repulsion that makes phosphate ester hydrolysis so unfavorable also makes it possible to regulate, by exploiting the electrostatics. This means that phosphate ester hydrolysis can not only be turned on, but also be turned off, by fine tuning the electrostatic environment and the present review demonstrates numerous examples where this is the case. Without this capacity for regulation, it would be impossible to have for instance a signaling or metabolic cascade, where the action of each participant is determined by the fine-tuned activity of the previous piece in the production line. This makes phosphate esters the ideal compounds to facilitate life as we know it.

Computational protein engineering: bridging the gap between rational design and laboratory evolution

Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation “hotspots” with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies.

Hybrid schemes based on quantum mechanics/molecular mechanics simulations goals to success, problems, and perspectives

The development of characterization techniques, advanced synthesis methods, as well as molecular modeling has transformed the study of systems in a well-established research field. The current research challenges in biocatalysis and biotransformation evolve around enzyme discovery, design, and optimization. How can we find or create enzymes that catalyze important synthetic reactions, even reactions that may not exist in nature? What is the source of enzyme catalytic power? To answer these and other related questions, the standard strategies have evolved from trial-and-error methodologies based on chemical knowledge, accumulated experience, and common sense into a clearly multidisciplinary science that allows one to reach the molecular design of tailor-made enzyme catalysts. This is even more so when one refers to enzyme catalysts, for which the detailed structure and composition are known and can be manipulated to introduce well-defined residues which can be implicated in the chemical rearrangements taking place in the active site. The methods and techniques of theoretical and computational chemistry are becoming more and more important in both understanding the fundamental biological roles of enzymes and facilitating their utilization in biotechnology. Improvement of the catalytic function of enzymes is important from scientific and industrial viewpoints, and to put this fact in the actual perspective as well as the potentialities, we recommend the very recent report of Sanderson [Sanderson, K. (2011). Chemistry: enzyme expertise. Nature 471, 397.]. Great fundamental advances have been made toward the ab initio design of enzyme catalysts based on molecular modeling. This has been based on the molecular mechanistic knowledge of the reactions to be catalyzed, together with the development of advanced synthesis and characterization techniques. The corresponding molecular mechanism can be studied by means of powerful quantum chemical calculations. The catalytic active site can be optimized to improve the transition state analogues (TSA) and to enhance the catalytic activity, even improve the active site to favor a desired direction of some promiscuous enzymes. In this chapter, we give a brief introduction, the state of the art, and future prospects and implications of enzyme design. Current computational tools to assist experimentalists for the design and engineering of proteins with desired catalytic properties are described. The interplay between enzyme design, molecular simulations, and experiments will be presented to emphasize the interdisciplinary nature of this research field. This text highlights the recent advances and examples selected from our laboratory are shown, of how the applications of these tools are a first attempt to de novo design of protein active sites. Identification of neutral/advantageous/deleterious mutation platforms can be exploited to penetrate some of Nature's closely guarded secrets of chemical reactivity. In this chapter, we give a brief introduction, the state of the art, and future prospects and implications of enzyme design. The first part describes briefly how the molecular modeling is carried out. Then, we discuss the requirements of hybrid quantum mechanical/molecular mechanics molecular dynamics (QM/MM MD) simulations, analyzing what are the basis of these theoretical methodologies, how we can use them with a view to its application in the study of enzyme catalysis, and what are the best methodologies for assessing its catalytic potential. In the second part, we focus on some selected examples, taking as a common guide the chorismate to prephenate rearrangement, studying the corresponding molecular mechanism in vacuo, in solution and in an enzyme environment. In addition, examples involving catalytic antibodies (CAs) and promiscuous enzymes will be presented. Finally, a special emphasis is made to provide some hints about the logical evolution that can be anticipated in this research field. Moreover, it helps in understanding the open directions in this area of knowledge and highlights the importance of computational approaches in discovering specific drugs and the impact on the rational design of tailor-made enzymes.

Converting structural information into an allosteric-energy-based picture for elongation factor Tu activation by the ribosome

The crucial process of aminoacyl-tRNA delivery to the ribosome is energized by the GTPase reaction of the elongation factor Tu (EF-Tu). Advances in the elucidation of the structure of the EF-Tu/ribosome complex provide the rare opportunity of gaining a detailed understanding of the activation process of this system. Here, we use quantitative simulation approaches and reproduce the energetics of the GTPase reaction of EF-Tu with and without the ribosome and with several key mutants. Our study provides a novel insight into the activation process. It is found that the critical H84 residue is not likely to behave as a general base but rather contributes to an allosteric effect, which includes a major transition state stabilization by the electrostatic effect of the P loop and other regions of the protein. Our findings have general relevance to GTPase activation, including the processes that control signal transduction.

Toward accurate screening in computer-aided enzyme design

The ability to design effective enzymes is one of the most fundamental challenges in biotechnology and in some respects in biochemistry. In fact, such ability would be one of the most convincing manifestations of a full understanding of the origin of enzyme catalysis. In this work, we explore the reliability of different simulation approaches, in terms of their ability to rank different possible active site constructs. This validation is done by comparing the ability of different approaches to evaluate the catalytic contributions of various residues in chorismate mutase. It is demonstrated that the empirical valence bond (EVB) model can serve as a practical yet accurate tool in the final stages of computer-aided enzyme design (CAED). Other approaches for fast screening are also examined and found to be less accurate and mainly useful for qualitative screening of ionized residues. It is pointed out that accurate ranking of different options for enzyme design cannot be accomplished by approaches that cannot capture the electrostatic preorganization effect. This is in particular true with regard to current design approaches that use gas phase or small cluster calculations and then estimate the interaction between the enzyme and the transition state (TS) model rather than the TS binding free energy or the relevant activation free energy. The ability of the EVB model to provide a tool for quantitative ranking in the final stage of CAED may help in progressing toward the design of enzymes whose catalytic power is closer to that of native enzymes than to that of the current generation of designer enzymes.

Interrogating the mechanism of a tight binding inhibitor of AIR carboxylase

The enzyme aminoimidazole ribonucleotide (AIR) carboxylase catalyzes the synthesis of the purine intermediate, 4-carboxy-5-aminoimidazole ribonucleotide (CAIR). Previously, we have shown that the compound 4-nitro-5-aminoimidazole ribonucleotide (NAIR) is a slow, tight binding inhibitor of the enzyme with a Ki of 0.34 nM. The structural attributes and the slow, tight binding characteristics of NAIR implicated this compound as a transition state or reactive intermediate analog. However, it is unclear what molecular features of NAIR contribute to the mimetic properties for either of the two proposed mechanisms of AIR carboxylase. In order to gain additional information regarding the mechanism for the potent inhibition of AIR carboxylase by NAIR, a series of heterocyclic analogs were prepared and evaluated. We find that all compounds are weaker inhibitors than NAIR and that CAIR analogs are not alternative substrates for the enzyme. Surprisingly, rather subtle changes in the structure of NAIR can lead to profound changes in binding affinity. Computational investigations of enzyme intermediates and these inhibitors reveal that NAIR displays an electrostatic potential surface similar to a proposed reaction intermediate. The result indicates that AIR carboxylase is likely sensitive to the electrostatic surface of reaction intermediates and thus compounds which mimic these surfaces should possess tight binding characteristics. Given the evolutionary relationship between AIR carboxylase and N(5)-CAIR mutase, we believe that this concept extends to the mutase enzyme as well. The implications of this hypothesis for the design of selective inhibitors of the N(5)-CAIR mutase are discussed.

Selection and characterization of lipase abzyme from phage displayed antibody libraries

Antibodies with enzymatic activity were named abzymes or catalytic antibodies. In the present study, the lipolytic abzymes were selected from the phage displayed antibody libraries against a transition state analog (TSA) of lipases/esterases. After three rounds of selection, four monoclonal phage particles capable of binding significantly with the TSA were obtained. The soluble scFv antibody fragments were further expressed and obtained using Escherichia coli strain HB2151. The binding capabilities and the apparent enzymatic activities of the purified antibody proteins were measured. The 3D structures of the expressed antibodies were also predicted through homology modeling and binding-site prediction algorithm. The present method demonstrates that selection from phage displayed antibody libraries is an efficient and convenient means to find new abzymes.

An unusual functional group interaction and its potential to reproduce steric and electrostatic features of the transition states of peptidolysis

The donor-acceptor interaction between a tertiary amine and an aldehyde, first observed among a select class of alkaloids, was deliberately established in a peptidomimetic (1a-c) to mimic features of the two principal transition states of peptide hydrolysis. Compounds 1a-c show preferential adoption in methanol and water of a 'folded' conformation displaying the interaction. Proportions of the folded form in MeOH range from 45% to 70% and can reach 84% in buffer. Significantly, three tendencies for the folded/unfolded equilibrium are observed: increasing solubility and polarity of the medium and decreasing temperature results in a higher extent of folding. In the absence of any parameter set available for this weak bond, no modeling studies were conducted to aid in the design of 1a-c. The successful straightforward synthesis of 1 and its folding and inhibition results with HIV-1 peptidase using FRET technology encourage studies to further pre-organize candidate molecules and to screen the structure space by modeling and parallel combinatorial chemistry.

Active site identification through geometry-based and sequence profile-based calculations: burial of catalytic clefts

Electrostatics calculations with proteins that are uniformly charged over volume can aid enzyme/non-enzyme discrimination. For known enzymes, such methods locate active sites to within 5% on the enzyme surface, in 77% of a test set. We now report that removing the dielectric boundary improves active site location to 80%, with optimal discrimination between enzymes and non-enzymes of around 80% specificity and 80% sensitivity. This calculation quantifies burial of solvent-accessible regions. Many of the true enzymes incorrectly assigned as non-enzymes have active sites at subunit boundaries. These are missed in monomer-based calculations. Catalytic and non-catalytic antibodies are studied in this context of active/binding site burial. Whilst catalytic antibodies, on average, have marginally higher active site burial than non-catalytic antibodies, these values are generally smaller than for non-antibody enzymes, possibly contributing to their relatively low turnover. Prediction of active site location improves further when sequence profile-based weights replace the uniform charge distribution, so that a combination of burial and amino acid conservation is assessed. Accuracy rises to 93% of active sites to within 5%, in the test set, for the optimal profile weights scheme. The equivalent value in a separate validation set is 89% to within 5%. Enzyme/non-enzyme and enzyme functional site predictions are made for structural genomics proteins, suggesting that a substantial majority of these are non-enzymes.

Catalytic antibodies: hapten design strategies and screening methods

Catalytic antibodies have emerged as powerful tools for the efficient and specific catalysis of a wide range of chemical transformations. Generating antibody catalysts that achieve enzymatic efficiency remains a challenging task, which has long been the source of great interest both in the design of more effective haptens for immunization and in the development of more direct and efficient screening methods for the selection of antibodies with desired catalytic capacities. In this review, we describe the development of different hapten design strategies, including a transition state analog (TSA) approach, 'bait-and-switch' catalysis, and reactive immunization. We also comment on recent developments in the screening process that allow for a more efficient identification of antibody catalysts.

Nonspecific Medium Effects versus Specific Group Positioning in the Antibody and Albumin Catalysis of the Base-Promoted Ring-Opening Reactions of Benzisoxazoles

The mechanisms by which solvents, antibodies, and albumins influence the rates of base-catalyzed reactions of benzisoxazoles have been explored theoretically. New experimental data on substituent effects and rates of reactions in several solvents, in an antibody, and in an albumin are reported. Quantum mechanical calculations were carried out for the reactions in water and acetonitrile, and docking of the transition state into a homology model of antibody 34E4 and an X-ray structure of human serum albumin was accomplished. A microenvironment made up of catalytic polar groups (glutamate in antibody 34E4 and lysine in human serum albumin) surrounded by relatively nonpolar groups is present in both catalytic proteins.

Towards a MIP-based alignment and docking in computer-aided drug design

Structural alignment of ligands in their biological conformation is a crucial step in the building of pharmacophoric models in structure-based drug design. In addition, docking algorithms are limited in some cases by the quality of the scoring functions and the limited flexibility of the environment that the different programs allow. On the other hand, GRID molecular interaction potentials (MIPs) have been used for a long time in 3D-QSAR studies. However, in most of these studies the alignment of the molecules is performed on the basis of geometrical or physico-chemical criteria that differ from the MIPs used in the partial least squares statistical analysis. We have previously developed a method to use the same scoring function for the molecular alignment and for 3D-QSAR studies. This methodology, based on the use of GRID potentials, consists in the weighted averaging of similarities of the relevant MIPs of the molecules to be aligned. Here we present a method to obtain the weights for the different GRID probes in the average based on the structural information on protein-ligand complexes for relevant systems. The method, implemented in MIPSIM, is shown to yield good accuracy in the prediction of the alignments for two systems: a set of three inhibitors of dihydrofolate reductase and a set of fifteen non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs). The smooth GRID potentials are shown to capture the flexible character of the active site, as opposed to traditional docking scoring energy functions.

Theoretical insights in enzyme catalysis

In this tutorial review we show how the methods and techniques of computational chemistry have been applied to the understanding of the physical basis of the rate enhancement of chemical reactions by enzymes. This is to answer the question: Why is the activation free energy in enzyme catalysed reactions smaller than the activation free energy observed in solution? Two important points of view are presented: Transition State (TS) theories and Michaelis Complex (MC) theories. After reviewing some of the most popular computational methods employed, we analyse two particular enzymatic reactions: the conversion of chorismate to prephenate catalysed by Bacillus subtilis chorismate mutase, and a methyl transfer from S-adenosylmethionine to catecholate catalysed by catechol O-methyltransferase. The results and conclusions obtained by different authors on these two systems, supporting either TS stabilisation or substrate preorganization, are presented and compared. Finally we try to give a unified view, where a preorganized enzyme active site, prepared to stabilise the TS, also favours those reactive conformations geometrically closer to the TS.

Apparent NAC effect in chorismate mutase reflects electrostatic transition state stabilization

The catalytic reaction of chorismate mutase (CM) has been the subject of major current attention. Nevertheless, the origin of the catalytic power of CM remains an open question. In particular, it has not been clear whether the enzyme works by providing electrostatic transition state stabilization (TSS), by applying steric strain, or by populating near attack conformation (NAC). The present work explores this issue by a systematic quantitative analysis. The overall catalytic effect is reproduced by the empirical valence bond (EVB) method. In addition, the binding free energy of the ground state and the transition state is evaluated, demonstrating that the enzyme works by TSS. Furthermore, the evaluation of the electrostatic contribution to the reduction of the activation energy establishes that the TSS results from electrostatic effects. It is also found that the apparent NAC effect is not the reason for the catalytic effect but the result of the TSS. It is concluded that in CM as in other enzymes the key catalytic effect is electrostatic TSS. However, since the charge distribution of the transition state and the reactant state is similar, the stabilization of the transition state leads to reduction in the distance between the reacting atoms in the reactant state.