Enzymatic Flexibility and Reaction Rate: A QM/MM Study of HIV-1 Protease

The influence of model building schemes and molecular dynamics sampling on QM-cluster models: the chorismate mutase case study

Most QM-cluster models of enzymes are constructed based on X-ray crystal structures, which limits comparison to in vivo structure and mechanism. The active site of chorismate mutase from Bacillus subtilis and the enzymatic transformation of chorismate to prephenate is used as a case study to guide construction of QM-cluster models built first from the X-ray crystal structure, then from molecular dynamics (MD) simulation snapshots. The Residue Interaction Network ResidUe Selector (RINRUS) software toolkit, developed by our group to simplify and automate the construction of QM-cluster models, is expanded to handle MD to QM-cluster model workflows. Several options, some employing novel topological clustering from residue interaction network (RIN) information, are evaluated for generating conformational clustering from MD simulation. RINRUS then generates a statistical thermodynamic framework for QM-cluster modeling of the chorismate mutase mechanism via refining 250 MD frames with density functional theory (DFT). The 250 QM-cluster models sampled provide a mean ΔG‡ of 10.3 ± 2.6 kcal mol-1 compared to the experimental value of 15.4 kcal mol-1 at 25 °C. While the difference between theory and experiment is consequential, the level of theory used is modest and therefore "chemical" accuracy is unexpected. More important are the comparisons made between QM-cluster models designed from the X-ray crystal structure versus those from MD frames. The large variations in kinetic and thermodynamic properties arise from geometric changes in the ensemble of QM-cluster models, rather from the composition of the QM-cluster models or from the active site-solvent interface. The findings open the way for further quantitative and reproducible calibration in the field of computational enzymology using the model construction framework afforded with the RINRUS software toolkit.

Cooperative Conformational Transitions Underpin the Activation Heat Capacity in the Temperature Dependence of Enzyme Catalysis

Many enzymes display non-Arrhenius behavior with curved Arrhenius plots in the absence of denaturation. There has been significant debate about the origin of this behavior and recently the role of the activation heat capacity (ΔCP⧧) has been widely discussed. If enzyme-catalyzed reactions occur with appreciable negative values of ΔCP⧧ (arising from narrowing of the conformational space along the reaction coordinate), then curved Arrhenius plots are a consequence. To investigate these phenomena in detail, we have collected high precision temperature-rate data over a wide temperature interval for a model glycosidase enzyme MalL, and a series of mutants that change the temperature-dependence of the enzyme-catalyzed rate. We use these data to test a range of models including macromolecular rate theory (MMRT) and an equilibrium model. In addition, we have performed extensive molecular dynamics (MD) simulations to characterize the conformational landscape traversed by MalL in the enzyme-substrate complex and an enzyme-transition state complex. We have crystallized the enzyme in a transition state-like conformation in the absence of a ligand and determined an X-ray crystal structure at very high resolution (1.10 Å). We show (using simulation) that this enzyme-transition state conformation has a more restricted conformational landscape than the wildtype enzyme. We coin the term "transition state-like conformation (TLC)" to apply to this state of the enzyme. Together, these results imply a cooperative conformational transition between an enzyme-substrate conformation (ES) and a transition-state-like conformation (TLC) that precedes the chemical step. We present a two-state model as an extension of MMRT (MMRT-2S) that describes the data along with a convenient approximation with linear temperature dependence of the activation heat capacity (MMRT-1L) that can be used where fewer data points are available. Our model rationalizes disparate behavior seen for MalL and previous results for a thermophilic alcohol dehydrogenase and is consistent with a raft of data for other enzymes. Our model can be used to characterize the conformational changes required for enzyme catalysis and provides insights into the role of cooperative conformational changes in transition state stabilization that are accompanied by changes in heat capacity for the system along the reaction coordinate. TLCs are likely to be of wide importance in understanding the temperature dependence of enzyme activity and other aspects of enzyme catalysis.

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.

Deciphering the Catalytic Mechanism of Virginiamycin B Lyase with Multiscale Methods and Molecular Dynamics Simulations

Due to the emergence of antibiotic resistance, the need to explore novel antibiotics and/or novel strategies to counter antibiotic resistance is of utmost importance. In this work, we explored the molecular and mechanistic details of the degradation of a streptogramin B antibiotic by virginiamycin B (Vgb) lyase of Staphylococcus aureus using classical molecular dynamics simulations and multiscale quantum mechanics/molecular mechanics methods. Our results were in line with available experimental kinetic information. Although we were able to identify a stepwise mechanism, in the wild-type enzyme, the intermediate is short-lived, showing a small barrier to decay to the product state. The impact of point mutations on the reaction was also assessed, showing not only the importance of active site residues to the reaction catalyzed by Vgb lyase but also of near positive and negative residues surrounding the active site. Using molecular dynamics simulations, we also predicted the most likely protonation state of the 3-hydroxypicolinic moiety of the antibiotic and the impact of mutants on antibiotic binding. All this information will expand our understanding of linearization reactions of cyclic antibiotics, which are crucial for the development of novel strategies that aim to tackle antibiotic resistance.

Distinctive Formation of a DNA-Protein Cross-Link during the Repair of DNA Oxidative Damage: Insights into Human Disease from MD Simulations and QM/MM Calculations

Reactive oxygen species damage DNA and result in health issues. The major damage product, 8-oxo-7,8-dihydroguanine (8oG), is repaired by human adenine DNA glycosylase homologue (MUTYH). Although MUTYH misfunction is associated with a genetic disorder called MUTYH-associated polyposis (MAP) and MUTYH is a potential target for cancer drugs, the catalytic mechanism required to develop disease treatments is debated in the literature. This study uses molecular dynamics simulations and quantum mechanics/molecular mechanics techniques initiated from DNA-protein complexes that represent different stages of the repair pathway to map the catalytic mechanism of the wild-type MUTYH bacterial homologue (MutY). This multipronged computational approach characterizes a DNA-protein cross-linking mechanism that is consistent with all previous experimental data and is a distinct pathway across the broad class of monofunctional glycosylase repair enzymes. In addition to clarifying how the cross-link is formed, accommodated by the enzyme, and hydrolyzed for product release, our calculations rationalize why cross-link formation is favored over immediate glycosidic bond hydrolysis, the accepted mechanism for all other monofunctional DNA glycosylases to date. Calculations on the Y126F mutant MutY highlight critical roles for active site residues throughout the reaction, while investigation of the N146S mutant rationalizes the connection between the analogous N224S MUTYH mutation and MAP. In addition to furthering our knowledge of the chemistry associated with a devastating disorder, the structural information gained about the distinctive MutY mechanism compared to other repair enzymes represents an important step for the development of specific and potent small-molecule inhibitors as cancer therapeutics.

Rational Engineering of (S)-Norcoclaurine Synthase for Efficient Benzylisoquinoline Alkaloids Biosynthesis

(S)-Norcoclaurine is synthesized in vivo through a metabolic pathway that ends with (S)-norcoclaurine synthase (NCS). The former constitutes the scaffold for the biosynthesis of all benzylisoquinoline alkaloids (BIAs), including many drugs such as the opiates morphine and codeine and the semi-synthetic opioids oxycodone, hydrocodone, and hydromorphone. Unfortunately, the only source of complex BIAs is the opium poppy, leaving the drug supply dependent on poppy crops. Therefore, the bioproduction of (S)-norcoclaurine in heterologous hosts, such as bacteria or yeast, is an intense area of research nowadays. The efficiency of (S)-norcoclaurine biosynthesis is strongly dependent on the catalytic efficiency of NCS. Therefore, we identified vital NCS rate-enhancing mutations through the rational transition-state macrodipole stabilization method at the Quantum Mechanics/Molecular Mechanics (QM/MM) level. The results are a step forward for obtaining NCS variants able to biosynthesize (S)-norcoclaurine on a large scale.

Unraveling the Reaction Mechanism of Russell's Viper Venom Factor X Activator: A Paradigm for the Reactivity of Zinc Metalloproteinases?

Snake venom metalloproteinases (SVMPs) are important drug targets against snakebite envenoming, the neglected tropical disease with the highest mortality worldwide. Here, we focus on Russell's viper (Daboia russelii), one of the "big four" snakes of the Indian subcontinent that, together, are responsible for ca. 50,000 fatalities annually. The "Russell's viper venom factor X activator" (RVV-X), a highly toxic metalloproteinase, activates the blood coagulation factor X (FX), leading to the prey's abnormal blood clotting and death. Given its tremendous public health impact, the WHO recognized an urgent need to develop efficient, heat-stable, and affordable-for-all small-molecule inhibitors, for which a deep understanding of the mechanisms of action of snake's principal toxins is fundamental. In this study, we determine the catalytic mechanism of RVV-X by using a density functional theory/molecular mechanics (DFT:MM) methodology to calculate its free energy profile. The results showed that the catalytic process takes place via two steps. The first step involves a nucleophilic attack by an in situ generated hydroxide ion on the substrate carbonyl, yielding an activation barrier of 17.7 kcal·mol^-1, while the second step corresponds to protonation of the peptide nitrogen and peptide bond cleavage with an energy barrier of 23.1 kcal·mol^-1. Our study shows a unique role played by Zn²⁺ in catalysis by lowering the pK_a of the Zn²⁺-bound water molecule, enough to permit the swift formation of the hydroxide nucleophile through barrierless deprotonation by the formally much less basic Glu140. Without the Zn²⁺ cofactor, this step would be rate-limiting.

Engineering DszC Mutants from Transition State Macrodipole Considerations and Evolutionary Sequence Analysis

We describe an approach to identify enzyme mutants with increased turnover using the enzyme DszC as a case study. Our approach is based on recalculating the barriers of alanine mutants through single-point energy calculations at the hybrid QM/MM level in the wild-type reactant and transition state geometries. We analyze the difference in the electron density between the reactant and transition state to identify sites/residues where electrostatic interactions stabilize the transition state over the reactants. We also assess the insertion of a unit probe charge to identify positions in which the introduction of charged residues lowers the barrier.

Mechanistic Investigation of Lysine-Targeted Covalent Inhibition of PI3Kδ via ONIOM QM:QM Computations

Phosphoinositide 3-kinase (PI3K) enzymes are important drug targets, especially in oncology, and several inhibitors are currently under investigation in clinical trials for the treatment of lymphocytic leukemia, follicular lymphoma, breast, thyroid, colorectal, and lung cancer. Targeted covalent inhibitors hold significant promise for drug discovery research especially for kinases. Targeting the lysine residues attracts attention as a new strategy in designing targeted covalent inhibitors, since the lysine residue provides several advantages over the traditional cysteine residue. Recently, new highly selective covalent inhibitors of PI3Kδ with activated ester warheads, targeting the conserved Lys779 residue, were reported. Based on the observed kinetics, a covalent inhibition mechanism was proposed, but the atomistic details of the reaction are still not understood. Therefore, in the present work, we have conducted quantum chemical ONIOM M06-2X/6-31+G(d,p):PM6 calculations on the active site cluster structure of PI3Kδ to elucidate the microscopic details of the mechanism of the aminolysis reaction between Lys779 and the ester inhibitors. Our calculations clearly discriminate the noncovalent methyl ester inhibitor and the covalent inhibitors with activated phenolic esters. For the representative p-NO₂, p-F, p-H, and p-OCH₃ phenolic esters, the Gibbs free energy profiles of alternative mechanistic paths through either Asp782 or Asp911 demonstrate the modulatory role of active site aspartate residues. The most plausible path alters depending on the electron-withdrawing/donating nature of the p-substituted phenolate leaving group. Inhibitors with sufficiently strong electron-withdrawing group prefer direct dissociation of the leaving group from the tetrahedral zwitterion intermediate, while the ones with electron-donating group favor the formation of a neutral tetrahedral intermediate prior to the dissociation. The relative Gibbs free energy barriers of p-NO₂ < p-F < p-H < p-OCH₃ substituted phenyl esters display the same qualitative trend as the experimentally measured k_inact/K_I values. Our results provide in depth insight into the mechanism, which can pave the way for optimizing the inhibitor efficiency.

Application of Computational Biology and Artificial Intelligence in Drug Design

Traditional drug design requires a great amount of research time and developmental expense. Booming computational approaches, including computational biology, computer-aided drug design, and artificial intelligence, have the potential to expedite the efficiency of drug discovery by minimizing the time and financial cost. In recent years, computational approaches are being widely used to improve the efficacy and effectiveness of drug discovery and pipeline, leading to the approval of plenty of new drugs for marketing. The present review emphasizes on the applications of these indispensable computational approaches in aiding target identification, lead discovery, and lead optimization. Some challenges of using these approaches for drug design are also discussed. Moreover, we propose a methodology for integrating various computational techniques into new drug discovery and design.

Role of Enzyme and Active Site Conformational Dynamics in the Catalysis by α-Amylase Explored with QM/MM Molecular Dynamics

We assessed enzyme:substrate conformational dynamics and the rate-limiting glycosylation step of a human pancreatic α-amylase:maltopentose complex. Microsecond molecular dynamics simulations suggested that the distance of the catalytic Asp197 nucleophile to the anomeric carbon of the buried glucoside is responsible for most of the enzyme active site fluctuations and that both Asp197 and Asp300 interact the most with the buried glucoside unit. The buried glucoside binds either in a ⁴C₁ chair or ²S_O skew conformations, both of which can change to TS-like conformations characteristic of retaining glucosidases. Starting from four distinct enzyme:substrate complexes, umbrella sampling quantum mechanics/molecular mechanics simulations (converged within less than 1 kcal·mol^-1 within a total simulation time of 1.6 ns) indicated that the reaction occurrs with a Gibbs barrier of 13.9 kcal·mol ^-1, in one asynchronous concerted step encompassing an acid-base reaction with Glu233 followed by a loose S_N2-like nucleophilic substitution by the Asp197. The transition state is characterized by a ²H₃ half-chair conformation of the buried glucoside that quickly changes to the E₃ envelope conformation preceding the attack of the anomeric carbon by the Asp197 nucleophile. Thermodynamic analysis of the reaction supported that a water molecule tightly hydrogen bonded to the glycosidic oxygen of the substrate at the reactant state (∼1.6 Å) forms a short hydrogen bond with Glu233 at the transition state (∼1.7 Å) and lowers the Gibbs barrier in over 5 kcal·mol^-1. The resulting Asp197-glycosyl was mostly found in the ⁴C₁ conformation, although the more endergonic B_3,O conformation was also observed. Altogether, the combination of short distances for the acid-base reaction with the Glu233 and for the nucleophilic attack by the Asp197 nucleophile and the availability of water within hydrogen bonding distance of the glycosidic oxygen provides a reliable criteria to identify reactive conformations of α-amylase complexes.

QM/MM Study of the Reaction Mechanism of Thermophilic Glucuronoyl Esterase for Biomass Treatment

Hydrolysis of lignocellulosic biomass, composed of a lignin-carbohydrate-complex (LCC) matrix, is critical for producing bioethanol from glucose. However, current methods for LCC processing require costly and polluting processes. The fungal Thermothelomyces thermophila glucuronoyl esterase (TtGE) is a promising thermophilic enzyme that hydrolyses LCC ester bonds. This study describes the TtGE catalytic mechanism using QM/MM methods. Two nearly-degenerate rate-determining transition states were found, with barriers of 16 and 17 kcal ⋅ mol^-1 , both with a zwitterionic nature that results from a proton interplay from His346 to either the Ser213-hydroxyl or the lignin leaving group and the rehybridisation of the ester moiety of the substrate to an alkoxide. An oxyanion hole, characteristic of esterases, was provided by the conserved Arg214 through its backbone and sidechain. Our work further suggests that a mutation of Glu267 to a non-negative residue will decrease the energetic barrier in ca. -5 kcal ⋅ mol^-1 , improving the catalytic rate of TtGE.

Transmembrane Protease Serine 2 Proteolytic Cleavage of the SARS-CoV-2 Spike Protein: A Mechanistic Quantum Mechanics/Molecular Mechanics Study to Inspire the Design of New Drugs To Fight the COVID-19 Pandemic

Despite the development of vaccines against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, there is an urgent need for efficient drugs to treat infected patients. An attractive drug target is the human transmembrane protease serine 2 (TMPRSS2) because of its vital role in the viral infection mechanism of SARS-CoV-2 by activation of the virus spike protein (S protein). Having in mind that the information derived from quantum mechanics/molecular mechanics (QM/MM) studies could be an important tool in the design of transition-state (TS) analogue inhibitors, we resorted to adiabatic QM/MM calculations to determine the mechanism of the first step (acylation) of proteolytic cleavage of the S protein with atomistic details. Acylation occurred in two stages: (i) proton transfer from Ser441 to His296 concerted with the nucleophilic attack of Ser441 to the substrate's P1-Arg and (ii) proton transfer from His296 to the P1'-Ser residue concerted with the cleavage of the ArgP1-SerP1' peptide bond, with a Gibbs activation energy of 17.1 and 15.8 kcal mol^-1, relative to the reactant. An oxyanion hole composed of two hydrogen bonds stabilized the rate-limiting TS by 8 kcal mol^-1. An analysis of the TMPRSS2 interactions with the high-energy, short-lived tetrahedral intermediate highlighted the limitations of current clinical inhibitors and pointed out specific ways to develop higher-affinity TS analogue inhibitors. The results support the development of more efficient drugs against SARS-CoV-2 using a human target, free from resistance development.

Towards the Accurate Thermodynamic Characterization of Enzyme Reaction Mechanisms

We employed QM/MM molecular dynamics (MD) simulations to characterize the rate-limiting step of the glycosylation reaction of pancreatic α-amylase with combined DFT/molecular dynamics methods (PBE/def2-SVP:AMBER). Upon careful choice of four starting active site conformations based on thorough reactivity criteria, Gibbs energy profiles were calculated with umbrella sampling simulations within a statistical convergence of 1-2 kcal⋅mol -1 . Nevertheless, Gibbs activation barriers and reaction energies still varied from 11.0 to 16.8 kcal⋅mol -1 and -6.3 to +3.8 kcal⋅mol -1 depending on the starting conformations, showing that despite significant state-of-the-art QM/MM MD sampling (0.5 ns/profile) the result still depends on the starting structure. The results supported the one step dissociative mechanism of Asp197 glycosylation preceded by an acid-base reaction by the Glu233, which are qualitatively similar to those from multi-PES QM/MM studies, and thus support the use of the latter to determine enzyme reaction mechanisms.

Predicting Effects of Site-Directed Mutagenesis on Enzyme Kinetics by QM/MM and QM Calculations: A Case of Glutamate Carboxypeptidase II

Quantum and molecular mechanics (QM/MM) and QM-only (cluster model) modeling techniques represent the two workhorses in mechanistic understanding of enzyme catalysis. One of the stringent tests for QM/MM and/or QM approaches is to provide quantitative answers to real-world biochemical questions, such as the effect of single-point mutations on enzyme kinetics. This translates into predicting the relative activation energies to 1-2 kcal·mol^-1 accuracy; such predictions can be used for the rational design of novel enzyme variants with desired/improved characteristics. Herein, we employ glutamate carboxypeptidase II (GCPII), a dizinc metallopeptidase, also known as the prostate specific membrane antigen, as a model system. The structure and activity of this major cancer antigen have been thoroughly studied, both experimentally and computationally, which makes it an ideal model system for method development. Its reaction mechanism is quite well understood: the reaction coordinate comprises a "tetrahedral intermediate" and two transition states and experimental activation Gibbs free energy of ∼17.5 kcal·mol^-1 can be inferred for the known k_cat ≈ 1 s^-1. We correlate experimental kinetic data (including the E424H variant, newly characterized in this work) for various GCPII mutants (k_cat = 8.6 × 10^-5 s^-1 to 2.7 s^-1) with the energy profiles calculated by QM/MM and QM-only (cluster model) approaches. We show that the near-quantitative agreement between the experimental values and the calculated activation energies (ΔH^⧧) can be obtained and recommend the combination of the two protocols: QM/MM optimized structures and cluster model (QM) energetics. The trend in relative activation energies is mostly independent of the QM method (DFT functional) used. Last but not least, a satisfactory correlation between experimental and theoretical data allows us to provide qualitative and fairly simple explanations of the observed kinetic effects which are thus based on a rigorous footing.

Modern strategies for the diversification of the supply of natural compounds - the case of alkaloid painkillers

Plant-derived natural compounds are used for treating diseases since the beginning of humankind. The supply of many plant-derived natural compounds for medicinal purposes, such as thebaine, morphine, and codeine, is, nowadays, majorly dependent on opium poppy crop harvesting. This dependency puts an extra risk factor in ensuring the supply chain because crops are highly susceptible to environmental factors. Emerging technologies, such as biocatalysis, might help to solve this problem, by diversifying the sources of supply of these compounds. Here we review the first committed step in the production of alkaloid painkillers, the production of S-norcoclaurine, and the enzymes involved. The improvement of these enzymes can be carried out by experimental directed evolution and rational design strategies, supported by computational methods, to create variants that produce the S-norcoclaurine precursor for alkaloid painkillers in heterologous organisms, meeting the pharmaceutical industry standards and needs without depending on opium poppy crops.

Accounting for the instantaneous disorder in the enzyme-substrate Michaelis complex to calculate the Gibbs free energy barrier of an enzyme reaction

Many enzyme reactions present instantaneous disorder. These dynamic fluctuations in the enzyme-substrate Michaelis complexes generate a wide range of energy barriers that cannot be experimentally observed, but that determine the measured kinetics of the reaction. These individual energy barriers can be calculated using QM/MM methods, but then the problem is how to deal with this dispersion of energy barriers to provide kinetic information. So far, the most usual procedure has implied the so-called exponential average of the energy barriers. In this paper, we discuss the foundations of this method, and we use the free energy perturbation theory to derive an alternative equation to get the Gibbs free energy barrier of the enzyme reaction. In addition, we propose a practical way to implement it. We have chosen four enzyme reactions as examples. In particular, we have studied the hydrolysis of a glycosidic bond catalyzed by the enzyme Thermus thermophilus β-glycosidase, and the mutant Y284P Ttb-gly, and the hydrogen abstraction reactions from C13 and C7 of arachidonic acid catalyzed by the enzyme rabbit 15-lipoxygenase-1.

Mechanisms of Proteolytic Enzymes and Their Inhibition in QM/MM Studies

Experimental evidence for enzymatic mechanisms is often scarce, and in many cases inadvertently biased by the employed methods. Thus, apparently contradictory model mechanisms can result in decade long discussions about the correct interpretation of data and the true theory behind it. However, often such opposing views turn out to be special cases of a more comprehensive and superior concept. Molecular dynamics (MD) and the more advanced molecular mechanical and quantum mechanical approach (QM/MM) provide a relatively consistent framework to treat enzymatic mechanisms, in particular, the activity of proteolytic enzymes. In line with this, computational chemistry based on experimental structures came up with studies on all major protease classes in recent years; examples of aspartic, metallo-, cysteine, serine, and threonine protease mechanisms are well founded on corresponding standards. In addition, experimental evidence from enzyme kinetics, structural research, and various other methods supports the described calculated mechanisms. One step beyond is the application of this information to the design of new and powerful inhibitors of disease-related enzymes, such as the HIV protease. In this overview, a few examples demonstrate the high potential of the QM/MM approach for sophisticated pharmaceutical compound design and supporting functions in the analysis of biomolecular structures.

Hydrogen bonding catalysis by water in epoxide ring opening reaction

Water can act as catalyst is perhaps the most intriguing property reported of this molecule in the last decade. However, despite being an integral part of many enzyme structures, the role of water in catalyzing enzymatic reactions remains sparsely studied. In a recent study, we have shown that the epoxide ring opening in aspartate proteases follows a two-step process involving water. In this work, we attempt to unravel the electronic basis of the co-catalytic role of water in the epoxide ring opening reaction by employing high-level quantum mechanical calculations at M06-2X/6-31+G(d,p) level of accuracy. Our computed electron density and its reduced gradient show that water anchor the reactant molecules through strong H-bond bridges. In addition, the strong ionizing power of water allows better charge delocalization to stabilize the transition states and oxyanion intermediate. Electrostatic analyses suggest greater charge transfer from the aspartates to the epoxide in the transition state, which is found to be exergonic in nature rendering a low-barrier reaction compared to a control system where water was omitted in the reaction field. This elucidated mechanism at electronic level could promote further research to search for the co-catalytic role of water in other enzymes.

The platination mechanism of RNase A by arsenoplatin: insight from the theoretical study

A detailed metalation process of the bovine pancreatic ribonuclease (RNase A) by a novel multitarget anti-cancer agent arsenoplatin-1, ([Pt(μ-NHC(CH₃)O)₂ClAs(OH)₂]), performed at DFT level and using different models size is provided.

A Computational and Modeling Study of the Reaction Mechanism of Staphylococcus aureus Monoglycosyltransferase Reveals New Insights on the GT51 Family of Enzymes

Bacterial glycosyltransferases of the GT51 family are key enzymes in bacterial cell wall synthesis. Inhibiting cell wall synthesis is a very effective approach for development of antibiotics, as this can lead to either bacteriostatic or bactericidal effects. Even though the existence of this family has been known for over 50 years, only one potent inhibitor exists, which is an analog of the lipid IV product and derived from a natural product. Drug development focused on bacterial transglycosylase has been hampered due to little being know about its structure and reaction mechanism. In this study, Staphylococcus aureus monoglycosyltransferase was investigated at an atomistic level using computational methods. Classical molecular dynamics simulations were used to reveal information about the large-scale dynamics of the enzyme-substrate complex and the importance of magnesium in structure and function of the protein, while mixed mode quantum mechanics/molecular mechanics calculations unveiled a novel hypothesis for the reaction mechanism. From these results, we present a new model for the binding mode of lipid II and the reaction mechanism of the GT51 glycosyltransferases. A metal-bound hydroxide catalyzed reaction mechanism yields an estimated free energy barrier of 16.1 ± 1.0 kcal/mol, which is in line with experimental values. The importance of divalent cations is also further discussed. These findings could significantly aid targeted drug design, particularly the efficient development of transition state analogues as potential inhibitors for the GT51 glycosyltransferases.

Visualizing Tetrahedral Oxyanion Bound in HIV-1 Protease Using Neutrons: Implications for the Catalytic Mechanism and Drug Design

HIV-1 protease is indispensable for virus propagation and an important therapeutic target for antiviral inhibitors to treat AIDS. As such inhibitors are transition-state mimics, a detailed understanding of the enzyme mechanism is crucial for the development of better anti-HIV drugs. Here, we used room-temperature joint X-ray/neutron crystallography to directly visualize hydrogen atoms and map hydrogen bonding interactions in a protease complex with peptidomimetic inhibitor KVS-1 containing a reactive nonhydrolyzable ketomethylene isostere, which, upon reacting with the catalytic water molecule, is converted into a tetrahedral intermediate state, KVS-1_TI. We unambiguously determined that the resulting tetrahedral intermediate is an oxyanion, rather than the gem-diol, and both catalytic aspartic acid residues are protonated. The oxyanion tetrahedral intermediate appears to be unstable, even though the negative charge on the oxyanion is delocalized through a strong n → π* hyperconjugative interaction into the nearby peptidic carbonyl group of the inhibitor. To better understand the influence of the ketomethylene isostere as a protease inhibitor, we have also examined the protease structure and binding affinity with keto-darunavir (keto-DRV), which similar to KVS-1 includes the ketomethylene isostere. We show that keto-DRV is a significantly less potent protease inhibitor than DRV. These findings shed light on the reaction mechanism of peptide hydrolysis catalyzed by HIV-1 protease and provide valuable insights into further improvements in the design of protease inhibitors.

Concerted hydrolysis mechanism of HIV-1 natural substrate against subtypes B and C-SA PR: insight through molecular dynamics and hybrid QM/MM studies

It is well known that understanding the catalytic mechanism of HIV-1 PR is the rationale on which its inhibitors were developed; therefore, a better understanding of the mechanism of natural substrate hydrolysis is important. Herein, the reaction mechanism of HIV-1 natural substrates with subtypes B and common mutant in South Africa (subtype C-SA) protease were studied through transition state modelling, using a general acid-general base (GA-GB) one-step concerted process. The activation free energies of enzyme-substrate complexes were compared based on their rate of hydrolysis using a two-layered ONIOM (B3LYP/6-31++G(d,p):AMBER) method. We expanded our computational model to obtain a better understanding of the mechanism of hydrolysis as well as how the enzyme recognises or chooses the cleavage site of the scissile bonds. Using this model, a potential substrate-based inhibitor could be developed with better potency. The calculated activation energies of natural substrates in our previous study correlated well with experimental data. A similar trend was observed for the Gag and Gag-Pol natural substrates in the present work for both enzyme complexes except for the PR-RT substrate. Natural bond orbital (NBO) analysis was also applied to determine the extent of charge transfer within the QM part of both enzymes considered and the PR-RT natural substrate. The result of this study shows that the method can be utilized as a dependable computational technique to rationalize lead compounds against specific targets.

User-Friendly Quantum Mechanics: Applications for Drug Discovery

Quantum mechanics (QM) methods provide a fine description of receptor-ligand interactions and of chemical reactions. Their use in drug design and drug discovery is increasing, especially for complex systems including metal ions in the binding sites, for the design of highly selective inhibitors, for the optimization of bi-specific compounds, to understand enzymatic reactions, and for the study of covalent ligands and prodrugs. They are also used for generating molecular descriptors for predictive QSAR/QSPR models and for the parameterization of force fields. Thanks to the continuous increase of computational power offered by GPUs and to the development of sophisticated algorithms, QM methods are becoming part of the standard tools used in computer-aided drug design (CADD). We present the most used QM methods and software packages, and we discuss recent representative applications in drug design and drug discovery.

A protocol to obtain multidimensional quantum tunneling corrections derived from QM(DFT)/MM calculations for an enzyme reaction

The multidimensional small-curvature tunneling (SCT) method with Electrostatic Embedding calculations is a compromise between an accessible computational cost and the attainment of an accurate enough estimation of tunneling for an enzyme reaction.

Conformational diversity induces nanosecond-timescale chemical disorder in the HIV-1 protease reaction pathway

The role of conformational diversity in enzyme catalysis has been a matter of analysis in recent studies. Pre-organization of the active site has been pointed out as the major source for enzymes' catalytic power. Following this line of thought, it is becoming clear that specific, instantaneous, non-rare enzyme conformations that make the active site perfectly pre-organized for the reaction lead to the lowest activation barriers that mostly contribute to the macroscopically observed reaction rate. The present work is focused on exploring the relationship between structure and catalysis in HIV-1 protease (PR) with an adiabatic mapping method, starting from different initial structures, collected from a classical MD simulation. The first, rate-limiting step of the HIV-1 PR catalytic mechanism was studied with the ONIOM QM/MM methodology (B3LYP/6-31G(d):ff99SB), with activation and reaction energies calculated at the M06-2X/6-311++G(2d,2p):ff99SB level of theory, in 19 different enzyme:substrate conformations. The results showed that the instantaneous enzyme conformations have two independent consequences on the enzyme's chemistry: they influence the barrier height, something also observed in the past in other enzymes, and they also influence the specific reaction pathway, which is something unusual and unexpected, challenging the "one enzyme-one substrate-one reaction mechanism" paradigm. Two different reaction mechanisms, with similar reactant probabilities and barrier heights, lead to the same gem-diol intermediate. Subtle nanosecond-timescale rearrangements in the active site hydrogen bonding network were shown to determine which reaction the enzyme follows. We named this phenomenon chemical disorder. The results make us realize the unexpected mechanistic consequences of conformational diversity in enzymatic reactivity.

An n→π* Interaction in the Bound Substrate of Aspartic Proteases Replicates the Oxyanion Hole

Aspartic proteases regulate many biological processes and are prominent targets for therapeutic intervention. Structural studies have captured intermediates along the reaction pathway, including the Michaelis complex and tetrahedral intermediate. Using a Ramachandran analysis of these structures, we discovered that residues occupying the P1 and P1' positions (which flank the scissile peptide bond) adopt the dihedral angle of an inverse γ-turn and polyproline type-II helix, respectively. Computational analyses reveal that the polyproline type-II helix engenders an n→π* interaction in which the oxygen of the scissile peptide bond is the donor. This interaction stabilizes the negative charge that develops in the tetrahedral intermediate, much like the oxyanion hole of serine proteases. The inverse γ-turn serves to twist the scissile peptide bond, vacating the carbonyl π* orbital and facilitating its hydration. These previously unappreciated interactions entail a form of substrate-assisted catalysis and offer opportunities for drug design.

Quantum Mechanics/Molecular Mechanics Simulations Identify the Ring-Opening Mechanism of Creatininase

Creatininase catalyzes the conversion of creatinine (a biosensor for kidney function) to creatine via a two-step mechanism: water addition followed by ring opening. Water addition is common to other known cyclic amidohydrolases, but the precise mechanism for ring opening is still under debate. The proton donor in this step is either His178 or a water molecule bound to one of the metal ions, and the roles of His178 and Glu122 are unclear. Here, the two possible reaction pathways have been fully examined by means of combined quantum mechanics/molecular mechanics simulations at the SCC-DFTB/CHARMM22 level of theory. The results indicate that His178 is the main catalytic residue for the whole reaction and explain its role as proton shuttle during the ring-opening step. In the first step, His178 provides electrostatic stabilization to the gem-diolate tetrahedral intermediate. In the second step, His178 abstracts the hydroxyl proton of the intermediate and delivers it to the cyclic amide nitrogen, leading to ring opening. The latter is the rate-limiting step with a free energy barrier of 18.5 kcal/mol, in agreement with the experiment. We find that Glu122 must be protonated during the enzyme reaction, so that it can form a stable hydrogen bond with its neighboring water molecule. Simulations of the E122Q mutant showed that this replacement disrupts the H-bond network formed by three conserved residues (Glu34, Ser78, and Glu122) and water, increasing the energy barrier. Our computational studies provide a comprehensive explanation for previous structural and kinetic observations, including why the H178A mutation causes a complete loss of activity but the E122Q mutation does not.