Recent developments of the quantum chemical cluster approach for modeling enzyme reactions

Computer Simulations of the Temperature Dependence of Enzyme Reactions

In this review we discuss the development of methodology for calculating the temperature dependence and thermodynamic activation parameters for chemical reactions in solution and in enzymes, from computer simulations. We outline how this is done by combining the empirical valence bond method with molecular dynamics free energy simulations. In favorable cases it turns out that such simulations can even capture temperature optima for the catalytic rate. The approach turns out be very useful both for addressing questions regarding the roles of enthalpic and entropic effects in specific enzymes and also for attacking evolutionary problems regarding enzyme adaptation to different temperature regimes. In the latter case, we focus on cold-adaptation of enzymes from psychrophilic species and show how computer simulations have revealed the basic mechanisms behind such adaptation. Understanding these mechanisms also opens up the possibility of designing the temperature dependence, and we highlight a recent example of this.

A Quantum Mechanical Approach to The Mechanism of Asymmetric Synthesis of Chiral Amine by Imine Reductase from Stackebrandtia Nassauensis

The asymmetric synthesis of tetrahydroisoquinolines (THIQs) has gained importance in recent years due to their significant potential in drug development studies. In this study, the conversion of 1-methyl-3,4-dihydroisoquinoline substrate to a chiral amine, 1-methyl-1,2,3,4-tetrahydroisoquinoline, under the catalysis of the stereoselective imine reductase enzyme from Stackebrandtia nassauensis (SnIR) was investigated in detail to elucidate the mechanism and explain the experimental enantioselectivity. The results were found to be in agreement with the experimental data. To elucidate the reaction mechanism, quantum mechanical calculations were performed by considering a large cluster of the active site of the enzyme. In this regard, possible reaction pathways leading to both R- and S-products with the corresponding intermediates and the transition states for the hydride transfer from the cofactor to the substrate were considered by density functional theory (DFT) calculations, and the factors contributing to the observed stereoselectivity were sought. The calculations supported a stepwise mechanism rather than the concerted protonation and the hydride transfer steps. The stereoselectivity in the hydride transfer was found to be due not only to the stability of the enzyme-subtrate complex but also to the corresponding reaction barriers. The calculations were performed at the wB97XD/6-311+G(2df,2p)//B3LYP/6-31G(d,p) level of theory using the PCM approach.

Capturing Dichotomic Solvent Behavior in Solute-Solvent Reactions with Neural Network Potentials

Simulations of chemical reactivity in condensed phase systems represent an ongoing challenge in computational chemistry, where traditional quantum chemical approaches typically struggle with both the size of the system and the potential complexity of the reaction. Here, we introduce a workflow aimed at efficiently training neural network potentials (NNPs) to explore energy barriers in solution at the hybrid density functional theory level. The computational burden associated with training at the PBE0-D3(BJ) level is bypassed through the use of active and transfer learning techniques, whereas extensive sampling of the transition state region is accelerated by well-tempered metadynamics simulations using multiple time step integration. These NNPs serve to explore a puzzling solute-solvent reactivity route involving the ring opening of N-enoxyphthalimide experimentally observed in methanol but not in 2,2,2-trifluoroethanol (TFE). This reaction represents a challenging example characterized by intricate hydrogen bonding networks and structurally ambiguous solvent-sensitive transition states. The methodology successfully delivers detailed free energy surfaces and relative energy barriers in agreement with experiment. These barriers are associated with an ensemble of transition states involving the direct participation of up to five solvent molecules. While this picture contrasts with the single transition state structure assumed by current static models, no drastic qualitative difference is observed between the formed hydrogen bonding networks and the number of participating solvent molecules in methanol or TFE. The dichotomy between the two solvents thus essentially arises from an electronic effect (i.e., distinct nucleophilicity) and from the larger conformational entropy contributions in methanol. This example underscores the critical role that dynamic simulations at the ab initio levels play in capturing the full complexity of solute-solvent interactions.

Modeling on in vivo disposition and cellular transportation of RNA lipid nanoparticles via quantum mechanics/physiologically-based pharmacokinetic approaches

The lipid nanoparticle (LNP) has been so far proven as a strongly effective delivery system for mRNA and siRNA. However, the mechanisms of LNP's distribution, metabolism, and elimination are complicated, while the transportation and pharmacokinetics (PK) of LNP are just sparsely investigated and simply described. This study aimed to build a model for the transportation of RNA-LNP in Hela cells, rats, mice, and humans by physiologically based pharmacokinetic (PBPK) and quantum mechanics (QM) models with integrated multi-source data. LNPs with different ionizable lipids, particle sizes, and doses were modeled and compared by recognizing their critical parameters dominating PK. Some interesting results were found by the models. For example, the metabolism of ionizable lipids was first limited by the LNP disassembly rate instead of the hydrolyzation of ionizable lipids; the ability of RNA release from endosomes for three ionizable lipids was quantitively derived and can predict the probability of RNA release. Moreover, the biodegradability of three ionizable lipids was estimated by the QM method and the is generally consistent with the result of PBPK result. In summary, the transportation model of RNA LNP among various species for the first time was successfully constructed. Various in vitro and in vivo pieces of evidence were integrated through QM/PBPK multi-level modeling. The resulting new understandings are related to biodegradability, safety, and RNA release ability which are highly concerned issues of the formulation. This would benefit the design and research of RNA-LNP in the future.

Eliminating Imaginary Vibrational Frequencies in Quantum-Chemical Cluster Models of Enzymatic Active Sites

In constructing finite models of enzyme active sites for quantum-chemical calculations, atoms at the periphery of the model must be constrained to prevent unphysical rearrangements during geometry relaxation. A simple fixed-atom or "coordinate-lock" approach is commonly employed but leads to undesirable artifacts in the form of small imaginary frequencies. These preclude evaluation of finite-temperature free-energy corrections, limiting thermochemical calculations to enthalpies only. Full-dimensional vibrational frequency calculations are possible by replacing the fixed-atom constraints with harmonic confining potentials. Here, we compare that approach to an alternative strategy in which fixed-atom contributions to the Hessian are simply omitted. While the latter strategy does eliminate imaginary frequencies, it tends to underestimate both the zero-point energy and the vibrational entropy while introducing artificial rigidity. Harmonic confining potentials eliminate imaginary frequencies and provide a flexible means to construct active-site models that can be used in unconstrained geometry relaxations, affording better convergence of reaction energies and barrier heights with respect to the model size, as compared to models with fixed-atom constraints.

Insight into the activation mechanism of carbonic anhydrase(II) through 2-(2-aminoethyl)-pyridine: a promising pathway for enhanced enzymatic activity

Activation of human carbonic anhydrase II (hCA II) holds great promise for treating memory loss symptoms associated with Alzheimer's disease. Despite its importance, the activation mechanism of hCA II has been largely overlooked in favor of the well-studied inhibition mechanism. To address this unexplored realm, we use first-principles calculations to tease out the activation mechanism of hCA II using 2-(2-aminoethyl)-pyridine (2-2AEPy), a promising in vitro activator. We explored both stepwise and concerted mechanisms via both available nitrogen sites of 2-2AEPy: (i) aminoethyl group (Nα) and (ii) pyridine ring (Nβ). Our results show that a concerted mechanism via Nα holds the key to hCA II activation. The activation process of the concerted mechanism exhibits the characteristics of an exergonic reaction, wherein the transition state resembles the reactant with a notably low imaginary frequency of 452.4i cm-1 and barrier height of 5.2 kcal mol-1. Such meager transition barriers propel the activation of hCA II at in vivo temperatures. These findings initiate future research into hCA II activation mechanisms and the development of efficient activators, which may lead to promising therapeutic interventions for Alzheimer's disease.

Elucidation of the catalytic mechanism of a single-metal dependent homing endonuclease using QM and QM/MM approaches: the case study of I-PpoI

Homing endonucleases (HEs) are highly specific DNA cleaving enzymes, with I-PpoI having been suggested to use a single metal to accelerate phosphodiester bond cleavage. Although an I-PpoI mechanism has been proposed based on experimental structural data, no consensus has been reached regarding the roles of the metal or key active site amino acids. This study uses QM cluster and QM/MM calculations to provide atomic-level details of the I-PpoI catalytic mechanism. Minimal QM cluster and large-scale QM/MM models demonstrate that the experimentally-proposed pathway involving direct Mg2+ coordination to the substrate coupled with leaving group protonation through a metal-activated water is not feasible due to an inconducive I-PpoI active site alignment. Despite QM cluster models of varying size uncovering a pathway involving leaving group protonation by a metal-activated water, indirect (water-mediated) metal coordination to the substrate is required to afford this pathway, which renders this mechanism energetically infeasible. Instead, QM cluster models reveal that the preferred pathway involves direct Mg2+-O3' coordination to stabilize the charged substrate and assist leaving group departure, while H98 activates the water nucleophile. These calculations also underscore that both catalytic residues that directly interact with the substrate and secondary amino acids that position or stabilize these residues are required for efficient catalysis. QM/MM calculations on the solvated enzyme-DNA complex verify the preferred mechanism, which is fully consistent with experimental kinetic, structural, and mutational data. The fundamental understanding of the I-PpoI mechanism of action, gained from the present work can be used to further explore potential uses of this enzyme in biotechnology and medicine, and direct future computational investigations of other members of the understudied HE family.

Nucleolar Essential Protein 1 (Nep1): Elucidation of enzymatic catalysis mechanism by molecular dynamics simulation and quantum mechanics study

The Nep1 protein is essential for the formation of eukaryotic and archaeal small ribosomal subunits, and it catalyzes the site-directed SAM-dependent methylation of pseudouridine (Ψ) during pre-rRNA processing. It possesses a non-trivial topology, namely, a 31 knot in the active site. Here, we address the issue of seemingly unfeasible deprotonation of Ψ in Nep1 active site by a distant aspartate residue (D101 in S. cerevisiae), using a combination of bioinformatics, computational, and experimental methods. We identified a conserved hydroxyl-containing amino acid (S233 in S. cerevisiae, T198 in A. fulgidus) that may act as a proton-transfer mediator. Molecular dynamics simulations, based on the crystal structure of S. cerevisiae, and on a complex generated by molecular docking in A. fulgidus, confirmed that this amino acid can shuttle protons, however, a water molecule in the active site may also serve this role. Quantum-chemical calculations based on density functional theory and the cluster approach showed that the water-mediated pathway is the most favorable for catalysis. Experimental kinetic and mutational studies reinforce the requirement for the aspartate D101, but not S233. These findings provide insight into the catalytic mechanisms underlying proton transfer over extended distances and comprehensively elucidate the mode of action of Nep1.

Understanding the Structure-Activity Relationship through Density Functional Theory: A Simple Method Predicts Relative Binding Free Energies of Metalloenzyme Fragment-like Inhibitors

Despite being involved in several human diseases, metalloenzymes are targeted by a small percentage of FDA-approved drugs. Development of novel and efficient inhibitors is required, as the chemical space of metal binding groups (MBGs) is currently limited to four main classes. The use of computational chemistry methods in drug discovery has gained momentum thanks to accurate estimates of binding modes and binding free energies of ligands to receptors. However, exact predictions of binding free energies in metalloenzymes are challenging due to the occurrence of nonclassical phenomena and interactions that common force field-based methods are unable to correctly describe. In this regard, we applied density functional theory (DFT) to predict the binding free energies and to understand the structure-activity relationship of metalloenzyme fragment-like inhibitors. We tested this method on a set of small-molecule inhibitors with different electronic properties and coordinating two Mn²⁺ ions in the binding site of the influenza RNA polymerase PA_N endonuclease. We modeled the binding site using only atoms from the first coordination shell, hence reducing the computational cost. Thanks to the explicit treatment of electrons by DFT, we highlighted the main contributions to the binding free energies and the electronic features differentiating strong and weak inhibitors, achieving good qualitative correlation with the experimentally determined affinities. By introducing automated docking, we explored alternative ways to coordinate the metal centers and we identified 70% of the highest affinity inhibitors. This methodology provides a fast and predictive tool for the identification of key features of metalloenzyme MBGs, which can be useful for the design of new and efficient drugs targeting these ubiquitous proteins.

Evaluating the active site-substrate interplay between x-ray crystal structure and molecular dynamics in chorismate mutase

Designing realistic quantum mechanical (QM) models of enzymes is dependent on reliably discerning and modeling residues, solvents, and cofactors important in crafting the active site microenvironment. Interatomic van der Waals contacts have previously demonstrated usefulness toward designing QM-models, but their measured values (and subsequent residue importance rankings) are expected to be influenceable by subtle changes in protein structure. Using chorismate mutase as a case study, this work examines the differences in ligand-residue interatomic contacts between an x-ray crystal structure and structures from a molecular dynamics simulation. Select structures are further analyzed using symmetry adapted perturbation theory to compute ab initio ligand-residue interaction energies. The findings of this study show that ligand-residue interatomic contacts measured for an x-ray crystal structure are not predictive of active site contacts from a sampling of molecular dynamics frames. In addition, the variability in interatomic contacts among structures is not correlated with variability in interaction energies. However, the results spotlight using interaction energies to characterize and rank residue importance in future computational enzymology workflows.

Sequential C-H Methylation Catalyzed by the B12 -Dependent SAM Enzyme TokK: Comprehensive Theoretical Study of Selectivities

TokK is a B₁₂ -dependent radical SAM enzyme involved in the biosynthesis of the β-lactam antibiotic asparenomycin A. It can catalyze three methylations on different sp³ -hybridized carbon positions to introduce an isopropyl side chain at the β-lactam ring of pantetheinylated carbapenem. Herein, we report a quantum chemical study of the reaction mechanism of TokK. A stepwise ''push-pull'' radical relay mechanism is proposed for each methylation: a 5'-deoxyadenosine radical first abstracts a hydrogen atom from the substrate in the active site, then methylcobalamin directionally donates a methyl group to the substrate. More importantly, calculations were able to uncover the origin of observed chemoselectivity and stereoselectivity for the first methylation and regioselectivity for the following two methylations. Further detailed distortion/interaction analysis can help to unravel the main factors controlling the selectivities. Our findings of sequential methylations by TokK could have profound implications for studying other B₁₂ -dependent radical SAM enzymes.

The Impact of DFT Functional, Cluster Model Size, and Implicit Solvation on the Structural Description of Single-Metal-Mediated DNA Phosphodiester Bond Cleavage: The Case Study of APE1

Phosphodiester bond hydrolysis in nucleic acids is a ubiquitous reaction that can be facilitated by enzymes called nucleases, which often use metal ions to achieve catalytic function. While a two-metal-mediated pathway has been well established for many enzymes, there is growing support that some enzymes require only one metal for the catalytic step. Using human apurinic/apyrimidinic endonuclease (APE1) as a prototypical example and cluster models, this study clarifies the impact of DFT functional, cluster model size, and implicit solvation on single-metal-mediated phosphodiester bond cleavage and provides insight into how to efficiently model this chemistry. Initially, a model containing 69 atoms built from a high-resolution X-ray crystal structure is used to explore the reaction pathway mapped by a range of DFT functionals and basis sets, which provides support for the use of standard functionals (M06-2X and B3LYP-D3) to study this reaction. Subsequently, systematically increasing the model size to 185 atoms by including additional amino acids and altering residue truncation points highlights that small models containing only a few amino acids or β carbon truncation points introduce model strains and lead to incorrect metal coordination. Indeed, a model that contains all key residues (general base and acid, residues that stabilize the substrate, and amino acids that maintain the metal coordination) is required for an accurate structural depiction of the one-metal-mediated phosphodiester bond hydrolysis by APE1, which results in 185 atoms. The additional inclusion of the broader enzyme environment through continuum solvation models has negligible effects. The insights gained in the present work can be used to direct future computational studies of other one-metal-dependent nucleases to provide a greater understanding of how nature achieves this difficult chemistry.

Inhibition of the carnitine acylcarnitine carrier by carbon monoxide reveals a novel mechanism of action with non-metal-containing proteins

Both toxic and physiological effects of CO are mostly caused by well described interactions with heme-groups of proteins. Interactions of CO with non-heme proteins have also been unveiled. Besides interaction of CO with mitochondrial heme containing respiratory complexes, a BK channel and the phosphate carrier which do not contain metal cofactors, have been identified as CO targets. However, the molecular mechanisms of interaction with non-metal-containing proteins are not understood. We show in this work the effect of CO on the mitochondrial carnitine carrier (SLC25A20) using CORM-3, a widely recognized CO releasing compound. CO exerts an inhibitory effect at the micromolar concentration on the transport function of the transporter extracted from treated mitochondria. The effect is due to a single Cys residue, C136 as revealed by mass spectrometry analysis. A computational approach predicted the need for vicinal Asp and Lys residues for the C136 carbonylation to occur. These data demonstrate a novel mechanism of interaction of CO with a protein not containing metal atoms and will enable the prediction of CO targets.

Broad-Spectrum Antidote Discovery by Untangling the Reactivation Mechanism of Nerve-Agent-Inhibited Acetylcholinesterase

Reactivators are vital for the treatment of organophosphorus nerve agent (OPNA) intoxication but new alternatives are needed due to their limited clinical applicability. The toxicity of OPNAs stems from covalent inhibition of the essential enzyme acetylcholinesterase (AChE), which reactivators relieve via a chemical reaction with the inactivated enzyme. Here, we present new strategies and tools for developing reactivators. We discover suitable inhibitor scaffolds by using an activity-independent competition assay to study non-covalent interactions with OPNA-AChEs and transform these inhibitors into broad-spectrum reactivators. Moreover, we identify determinants of reactivation efficiency by analysing reactivation and pre-reactivation kinetics together with structural data. Our results show that new OPNA reactivators can be discovered rationally by exploiting detailed knowledge of the reactivation mechanism of OPNA-inhibited AChE.

Role of water coordination at zinc binding site and its catalytic pathway of dizinc creatininase: insights from quantum cluster approach

Creatininase is a key enzyme of creatinine-metabolizing pathway in mammals, and has a great potential for diagnostic application. It catalyzes the reversible conversion of creatinine to creatine. Here, we investigated its reaction mechanism with density functional theory in conjunction with the quantum cluster approach. Three reaction pathways in which several possible proton transfers assisted by either His178 or a water ligand to Zn1 (Wat2) or both were considered. DFT calculations reveal, depending on Wat2 coordination mode at Zn1, two competitive ring-opening pathways where His178 playing a central role as a proton shuttle or both His178 and Wat2 serving as a dual catalytic role as a base and an acid, respectively. Three elementary steps were proposed for the reaction: the first involves nucleophilic attack by a bridging hydroxide to the substrate and forms a gem-diolate intermediate, followed by a proton transfer from the gem-diolate to His178 (His178 protonation is a required step for efficient proton transfers). Finally, the second proton transfer from the protonated His178 or Wat2 to the amide of substrate leads to the ring opening. The first proton transfer is the rate-limiting step of the whole reaction, in consistent with previous experimental and computational studies. A detailed understanding of the reaction mechanism of the creatininase enzyme family will also be helpful for developing a biosensor for kidney function.

Theoretical Modeling of Redox Potentials of Biomolecules

The estimation of the redox potentials of biologically relevant systems by means of theoretical-computational approaches still represents a challenge. In fact, the size of these systems typically does not allow a full quantum-mechanical treatment needed to describe electron loss/gain in such a complex environment, where the redox process takes place. Therefore, a number of different theoretical strategies have been developed so far to make the calculation of the redox free energy feasible with current computational resources. In this review, we provide a survey of such theoretical-computational approaches used in this context, highlighting their physical principles and discussing their advantages and limitations. Several examples of these approaches applied to the estimation of the redox potentials of both proteins and nucleic acids are described and critically discussed. Finally, general considerations on the most promising strategies are reported.

Investigation of iron release from the N- and C-lobes of human serum transferrin by quantum chemical calculations

Cluster models of iron binding sites of the N- and C-lobes highlights the inequivalence of each lobe in iron release.

Metalloprotein catalysis: structural and mechanistic insights into oxidoreductases from neutron protein crystallography

Metalloproteins catalyze a range of reactions, with enhanced chemical functionality due to their metal cofactor. The reaction mechanisms of metalloproteins have been experimentally characterized by spectroscopy, macromolecular crystallography and cryo-electron microscopy. An important caveat in structural studies of metalloproteins remains the artefacts that can be introduced by radiation damage. Photoreduction, radiolysis and ionization deriving from the electromagnetic beam used to probe the structure complicate structural and mechanistic interpretation. Neutron protein diffraction remains the only structural probe that leaves protein samples devoid of radiation damage, even when data are collected at room temperature. Additionally, neutron protein crystallography provides information on the positions of light atoms such as hydrogen and deuterium, allowing the characterization of protonation states and hydrogen-bonding networks. Neutron protein crystallography has further been used in conjunction with experimental and computational techniques to gain insight into the structures and reaction mechanisms of several transition-state metal oxidoreductases with iron, copper and manganese cofactors. Here, the contribution of neutron protein crystallography towards elucidating the reaction mechanism of metalloproteins is reviewed.

The Se-S Bond Formation in the Covalent Inhibition Mechanism of SARS-CoV-2 Main Protease by Ebselen-like Inhibitors: A Computational Study

The inhibition mechanism of the main protease (Mpro) of SARS-CoV-2 by ebselen (EBS) and its analog with a hydroxyl group at position 2 of the benzisoselenazol-3(2H)-one ring (EBS-OH) was studied by using a density functional level of theory. Preliminary molecular dynamics simulations on the apo form of Mpro were performed taking into account both the hydrogen donor and acceptor natures of the Nδ and Nε of His41, a member of the catalytic dyad. The potential energy surfaces for the formation of the Se-S covalent bond mediated by EBS and EBS-OH on Mpro are discussed in detail. The EBS-OH shows a distinctive behavior with respect to EBS in the formation of the noncovalent complex. Due to the presence of canonical H-bonds and noncanonical ones involving less electronegative atoms, such as sulfur and selenium, the influence on the energy barriers and reaction energy of the Minnesota hybrid meta-GGA functionals M06, M06-2X and M08HX, and the more recent range-separated hybrid functional wB97X were also considered. The knowledge of the inhibition mechanism of Mpro by the small protease inhibitors EBS or EBS-OH can enlarge the possibilities for designing more potent and selective inhibitor-based drugs to be used in combination with other antiviral therapies.

Mechanistic Insight into SARS-CoV-2 Mpro Inhibition by Organoselenides: The Ebselen Case Study

The main protease (Mpro) of SARS-CoV-2 is a current target for the inhibition of viral replication. Through a combined Docking and Density Functional Theory (DFT) approach, we investigated in-silico the molecular mechanism by which ebselen (IUPAC: 2-phenyl-1,2-benzoselenazol-3-one), the most famous and pharmacologically active organoselenide, inhibits Mpro. For the first time, we report on a mechanistic investigation in an enzyme for the formation of the covalent -S-Se- bond between ebselen and a key enzymatic cysteine. The results highlight the strengths and weaknesses of ebselen and provide hints for a rational drug design of bioorganic selenium-based inhibitors.

Ocean Acidification Amplifies the Olfactory Response to 2-Phenylethylamine: Altered Cue Reception as a Mechanistic Pathway?

With carbon dioxide (CO₂) levels rising dramatically, climate change threatens marine environments. Due to increasing CO₂ concentrations in the ocean, pH levels are expected to drop by 0.4 units by the end of the century. There is an urgent need to understand the impact of ocean acidification on chemical-ecological processes. To date, the extent and mechanisms by which the decreasing ocean pH influences chemical communication are unclear. Combining behaviour assays with computational chemistry, we explore the function of the predator related cue 2-phenylethylamine (PEA) for hermit crabs (Pagurus bernhardus) in current and end-of-the-century oceanic pH. Living in intertidal environments, hermit crabs face large pH fluctuations in their current habitat in addition to climate-change related ocean acidification. We demonstrate that the dietary predator cue PEA for mammals and sea lampreys is an attractant for hermit crabs, with the potency of the cue increasing with decreasing pH levels. In order to explain this increased potency, we assess changes to PEA’s conformational and charge-related properties as one potential mechanistic pathway. Using quantum chemical calculations validated by NMR spectroscopy, we characterise the different protonation states of PEA in water. We show how protonation of PEA could affect receptor-ligand binding, using a possible model receptor for PEA (human TAAR1). Investigating potential mechanisms of pH-dependent effects on olfactory perception of PEA and the respective behavioural response, our study advances the understanding of how ocean acidification interferes with the sense of smell and thereby might impact essential ecological interactions in marine ecosystems.

Thermochemical and Quantum Descriptor Calculations for Gaining Insight into Ricin Toxin A (RTA) Inhibitors

In this work, we performed a study to assess the interactions between the ricin toxin A (RTA) subunit of ricin and some of its inhibitors using modern semiempirical quantum chemistry and ONIOM quantum mechanics/molecular mechanics (QM/MM) methods. Two approaches were followed (calculation of binding enthalpies, ΔH _bind, and reactivity quantum chemical descriptors) and compared with the respective half-maximal inhibitory concentration (IC₅₀) experimental data, to gain insight into RTA inhibitors and verify which quantum chemical method would better describe RTA-ligand interactions. The geometries for all RTA-ligand complexes were obtained after running classical molecular dynamics simulations in aqueous media. We found that single-point energy calculations of ΔH _bind with the PM6-DH+, PM6-D3H4, and PM7 semiempirical methods and ONIOM QM/MM presented a good correlation with the IC₅₀ data. We also observed, however, that the correlation decreased significantly when we calculated ΔH _bind after full-atom geometry optimization with all semiempirical methods. Based on the results from reactivity descriptors calculations for the cases studied, we noted that both types of interactions, molecular overlap and electrostatic interactions, play significant roles in the overall affinity of these ligands for the RTA binding pocket.

Structure and mechanism of a phage-encoded SAM lyase revises catalytic function of enzyme family

The first S-adenosyl methionine (SAM) degrading enzyme (SAMase) was discovered in bacteriophage T3, as a counter-defense against the bacterial restriction-modification system, and annotated as a SAM hydrolase forming 5’-methyl-thioadenosine (MTA) and L-homoserine. From environmental phages, we recently discovered three SAMases with barely detectable sequence similarity to T3 SAMase and without homology to proteins of known structure. Here, we present the very first phage SAMase structures, in complex with a substrate analogue and the product MTA. The structure shows a trimer of alpha–beta sandwiches similar to the GlnB-like superfamily, with active sites formed at the trimer interfaces. Quantum-mechanical calculations, thin-layer chromatography, and nuclear magnetic resonance spectroscopy demonstrate that this family of enzymes are not hydrolases but lyases forming MTA and L-homoserine lactone in a unimolecular reaction mechanism. Sequence analysis and in vitro and in vivo mutagenesis support that T3 SAMase belongs to the same structural family and utilizes the same reaction mechanism.

Bacteria can be infected by viruses known as bacteriophages. These viruses inject their genetic material into bacterial cells and use the bacteria’s own machinery to build the proteins they need to survive and infect other cells. To protect themselves, bacteria produce a molecule called S-adenosyl methionine, or SAM for short, which deposits marks on the bacteria’s DNA. These marks help the bacteria distinguish their own genetic material from the genetic material of foreign invaders: any DNA not bearing the mark from SAM will be immediately broken down by the bacterial cell. This system helps to block many types of bacteriophage infections, but not all. Some bacteriophages carry genes that code for enzymes called SAMases, which can break down SAM, switching off the bacteria’s defenses.

The most well-known SAMase was first discovered in the 1960s in a bacteriophage called T3. Chemical studies of this SAMase suggested that it works as a 'hydrolase', meaning that it uses water to break SAM apart. New SAMases have since been discovered in bacteriophages from environmental water samples, which, despite being able to degrade SAM, are genetically dissimilar to one another and the SAMase in T3. This brings into question whether these enzymes all use the same mechanism to break SAM down.

To gain a better understanding of how these SAMases work, Guo, Söderholm, Kanchugal, Isaksen et al. solved the crystal structure of one of the newly discovered enzymes called Svi3-3. This revealed three copies of the Svi3-3 enzyme join together to form a unit that SAM binds to at the border between two of the enzymes. Computer simulations of this structure suggested that Svi3-3 holds SAM in a position where it cannot interact with water, and that once in the grip of the SAMase, SAM instead reacts with itself and splits into two.

Experiments confirmed these predictions for Svi3-3 and the other tested SAMases. Furthermore, the SAMase from bacteriophage T3 was also found to degrade SAM using the same mechanism. This shows that this group of SAMases are not hydrolases as originally thought, but in fact ‘lyases’: enzymes that break molecules apart without using water.

These findings form a starting point for further investigations into how SAM lyases help bacteriophages evade detection. SAM has various different functions in other living organisms, and these lyases could be used to modulate the levels of SAM in future studies investigating its role.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

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.

First-Principles Calculations on Ni,Fe-Containing Carbon Monoxide Dehydrogenases Reveal Key Stereoelectronic Features for Binding and Release of CO2 to/from the C-Cluster

In view of the depletion of fossil fuel reserves and climatic effects of greenhouse gas emissions, Ni,Fe-containing carbon monoxide dehydrogenase (Ni-CODH) enzymes have attracted increasing interest in recent years for their capability to selectively catalyze the reversible reduction of CO₂ to CO (CO₂ + 2H⁺ + 2e^– CO + H₂O). The possibility of converting the greenhouse gas CO₂ into useful materials that can be used as synthetic building blocks or, remarkably, as carbon fuels makes Ni-CODH a very promising target for reverse-engineering studies. In this context, in order to provide insights into the chemical principles underlying the biological catalysis of CO₂ activation and reduction, quantum mechanics calculations have been carried out in the framework of density functional theory (DFT) on different-sized models of the Ni-CODH active site. With the aim of uncovering which stereoelectronic properties of the active site (known as the C-cluster) are crucial for the efficient binding and release of CO₂, different coordination modes of CO₂ to different forms and redox states of the C-cluster have been investigated. The results obtained from this study highlight the key role of the protein environment in tuning the reactivity and the geometry of the C-cluster. In particular, the protonation state of His93 is found to be crucial for promoting the binding or the dissociation of CO₂. The oxidation state of the C-cluster is also shown to be critical. CO₂ binds to C_red2 according to a dissociative mechanism (i.e., CO₂ binds to the C-cluster after the release of possible ligands from Fe_u) when His93 is doubly protonated. CO₂ can also bind noncatalytically to C_red1 according to an associative mechanism (i.e., CO₂ binding is preceded by the binding of H₂O to Fe_u). Conversely, CO₂ dissociates when His93 is singly protonated and the C-cluster is oxidized at least to the C_int redox state.

Density functional theory was used to investigate Ni,Fe-containing carbon monoxide dehydrogenase enzymes. Different coordination modes of the substrate CO₂ to several forms and redox states of the C-cluster—the enzyme active site—were considered. The obtained results highlight the key role of the protein environment in tuning the reactivity and the geometry of the C-cluster. This helps to uncover which stereoelectronic properties of the active site are crucial for the efficient binding and release of CO₂.

Alkaline Phosphatases: in Silico Study on the Catalytic Effect of Conserved Active Site Residues Using Human Placental Alkaline Phosphatase (PLAP) As a Model Protein

The metalloenzymes from the alkaline phosphatase (AP) superfamily catalyze the hydrolysis and transphosphorylation of phosphate monoesters. The role of several amino acids highly conserved in the active site of this family of enzymes was examined, using human placental AP (PLAP) as a model protein. By employing an active-site model based on the X-ray crystal structure of PLAP, mutations of several key residues were modeled by quantum mechanical methods in order to determine their impact on the catalytic activity. Kinetic and thermodynamic estimations were achieved for each reaction step of the catalytic mechanism by characterization of the intermediates and transition states on the reaction pathway, and the effects of mutations on the activation barriers were analyzed. A good accordance was observed between the present computational results and experimental measurements reported in the literature.

Computational analysis of the metal selectivity of matrix metalloproteinase 8

Matrix metalloproteinase (MMP) is a class of metalloenzyme that cleaves peptide bonds in extracellular matrices. Their functions are important in both health and disease of animals. Here using quantum mechanics simulations of the MMP8 protein, the coordination chemistry of different metal cofactors is examined. Structural comparisons reveal that Jhan-Teller effects induced by Cu(II) coordination distorts the wild-type MMP8 active site corresponding to a significant reduction in activity observed in previous experiments. In addition, further analysis suggests that a histidine to glutamine mutation at residue number 197 can potentially allow the MMP8 protein to utilize Cu(II) in reactions. Simulations also demonstrates the requirement of a conformational change in the ligand before enzymatic cleavage. The insights provided here will assist future protein engineering efforts utilizing the MMP8 protein.

What Does the Brønsted Slope Measure in the Phosphoryl Transfer Transition State?

The structural and energetic features of phosphate and phosphonate hydrolysis in Protein Phosphatase-1 (PP1) and water are studied using quantum mechanical (QM) cluster models. The calculations are able to reproduce observed kinetic isotope effects and capture several key trends in the experimental Brønsted plots: the β l g values are rather different for phosphate and phosphonate ester hydrolysis in solution but are similar in PP1. Detailed analyses of structure, charge distribution and bond order of computed transition states support the general conclusion from experimental study that phosphoryl transfer transition states are different for the two classes of substrates in solution but similar in PP1. On the other hand, the microscopic models also highlight notable differences between the phosphate and phosphonate transition states, which are manifested in not only structure but also kinetic isotope effects. Overall, we find that while β l g / β E Q , l g generally correlates with the partial charge on leaving group oxygen and the fractional bond order of the breaking P- O l g bond, the precise mapping between β l g / β E Q , l g and P- O l g bond order in the transition state is difficult due largely to the cross talk between breaking and forming P-O bonds. Therefore, further supporting previous analyses of limitations of free energy relations, our results suggest that while free energy relation is a valuable tool for probing the nature of transition state, a quantitative mapping of β l g and β l g / β E Q , l g values to structure or charge in the transition state should be conducted with great care.

Differences in the Nature of the Phosphoryl Transfer Transition State in Protein Phosphatase 1 and Alkaline Phosphatase: Insights from QM Cluster Models

Quantum mechanical (QM) cluster models are used to probe effects on the catalytic properties of protein phosphatase 1 (PP1) and alkaline phosphatase (AP) due to metal ions and active site residues. The calculations suggest that the phosphoryl transfer transition states in PP1 are synchronous in nature with a significant degree of P-Olg cleavage, while those in AP are tighter with a modest degree of P-Olg cleavage and a range of P-Onuc formation. Similar to observations made in our recent work, a significant degree of cross talk between the forming and breaking P-O bonds complicates the interpretation of the Brønsted relation, especially in regard to AP for which the computed βlg/βEQ,lg value does not correlate with the degree of P-Olg cleavage regardless of the metal ions in the active site. By comparison, the correlation between βlg/βEQ,lg and the P-Olg bond order is more applicable to PP1, which generally exhibits less variation in the transition state than AP. Results for computational models with swapped metal ions between PP1 and AP suggest that the metal ions modulate both the nature of the transition state and the degrees of sensitivity of the transition state to the leaving group. In the reactant state, the degree of the scissile bond polarization is also different in the two enzymes, although this difference appears to be largely determined by the active site residues rather than the metal ions. Therefore, both the identity of the metal ion and the positioning of polar or charged residues in the active site contribute to the distinct catalytic characteristics of these enzymes. Several discrepancies observed between the QM cluster results and the available experimental data highlight the need for further QM/MM method developments for the quantitative analysis of metalloenzymes that contain open-shell transition metal ions.

Hydride Abstraction as the Rate-Limiting Step of the Irreversible Inhibition of Monoamine Oxidase B by Rasagiline and Selegiline: A Computational Empirical Valence Bond Study

Monoamine oxidases (MAOs) catalyze the degradation of a very broad range of biogenic and dietary amines including many neurotransmitters in the brain, whose imbalance is extensively linked with the biochemical pathology of various neurological disorders, and are, accordingly, used as primary pharmacological targets to treat these debilitating cognitive diseases. Still, despite this practical significance, the precise molecular mechanism underlying the irreversible MAO inhibition with clinically used propargylamine inhibitors rasagiline and selegiline is still not unambiguously determined, which hinders the rational design of improved inhibitors devoid of side effects current drugs are experiencing. To address this challenge, we present empirical valence bond QM/MM simulations of the rate-limiting step of the MAO inhibition involving the hydride anion transfer from the inhibitor α-carbon onto the N5 atom of the flavin adenin dinucleotide (FAD) cofactor. The proposed mechanism is strongly supported by the obtained free energy profiles, which confirm a higher reactivity of selegiline over rasagiline, while the calculated difference in the activation Gibbs energies of ΔΔG^‡ = 3.1 kcal mol^-1 is found to be in very good agreement with that from the measured literature k_inact values that predict a 1.7 kcal mol^-1 higher selegiline reactivity. Given the similarity with the hydride transfer mechanism during the MAO catalytic activity, these results verify that both rasagiline and selegiline are mechanism-based irreversible inhibitors and offer guidelines in designing new and improved inhibitors, which are all clinically employed in treating a variety of neuropsychiatric and neurodegenerative conditions.

Mg2+-Dependent Methyl Transfer by a Knotted Protein: A Molecular Dynamics Simulation and Quantum Mechanics Study

Mg²⁺ is required for the catalytic activity of TrmD, a bacteria-specific methyltransferase that is made up of a protein topological knot-fold, to synthesize methylated m¹G37-tRNA to support life. However, neither the location of Mg²⁺ in the structure of TrmD nor its role in the catalytic mechanism is known. Using molecular dynamics (MD) simulations, we identify a plausible Mg²⁺ binding pocket within the active site of the enzyme, wherein the ion is coordinated by two aspartates and a glutamate. In this position, Mg²⁺ additionally interacts with the carboxylate of a methyl donor cofactor S-adenosylmethionine (SAM). The computational results are validated by experimental mutation studies, which demonstrate the importance of the Mg²⁺-binding residues for the catalytic activity. The presence of Mg²⁺ in the binding pocket induces SAM to adopt a unique bent shape required for the methyl transfer activity and causes a structural reorganization of the active site. Quantum mechanical calculations show that the methyl transfer is energetically feasible only when Mg²⁺ is bound in the position revealed by the MD simulations, demonstrating that its function is to align the active site residues within the topological knot-fold in a geometry optimal for catalysis. The obtained insights provide the opportunity for developing a strategy of antibacterial drug discovery based on targeting of Mg²⁺-binding to TrmD.

Physical Mechanisms Governing Substituent Effects on Arene-Arene Interactions in a Protein Milieu

Arene-arene interactions play important roles in protein-ligand complex formation. Here, we investigate the characteristics of arene-arene interactions between small organic molecules and aromatic amino acids in protein interiors. The study is based on X-ray crystallographic data and quantum mechanical calculations using the enzyme acetylcholinesterase and selected inhibitory ligands as a model system. It is shown that the arene substituents of the inhibitors dictate the strength of the interaction and the geometry of the resulting complexes. Importantly, the calculated interaction energies correlate well with the measured inhibitor potency. Non-hydrogen substituents strengthened all interaction types in the protein milieu, in keeping with results for benzene dimer model systems. The interaction energies were dispersion-dominated, but substituents that induced local dipole moments increased the electrostatic contribution and thus yielded more strongly bound complexes. These findings provide fundamental insights into the physical mechanisms governing arene-arene interactions in the protein milieu and thus into molecular recognition between proteins and small molecules.

Quantum Chemical and QM/MM Models in Biochemistry

Quantum chemical (QC) calculations provide a basis for deriving a microscopic understanding of enzymes and photobiological systems. Here we describe how QC models can be used to explore the electronic structure, dynamics, and energetics of biomolecules. We introduce the hybrid quantum mechanics/classical mechanics (QM/MM) approach, where a quantum mechanically described system of interest is embedded in a classically described force field representation of the biochemical surroundings. We also discuss the QM cluster model approach, as well as embedding theories, that provide complementary methodologies to model quantum mechanical effects in biomolecules. The chapter also provides some practical guides for building quantum biochemical models using the quinone reduction catalysis in respiratory complex I and a model reaction in solution as examples.

Using Atomic Confining Potentials for Geometry Optimization and Vibrational Frequency Calculations in Quantum-Chemical Models of Enzyme Active Sites

Quantum-chemical studies of enzymatic reaction mechanisms sometimes use truncated active-site models as simplified alternatives to mixed quantum mechanics molecular mechanics (QM/MM) procedures. Eliminating the MM degrees of freedom reduces the complexity of the sampling problem, but the trade-off is the need to introduce geometric constraints in order to prevent structural collapse of the model system during geometry optimizations that do not contain a full protein backbone. These constraints may impair the efficiency of the optimization, and care must be taken to avoid artifacts such as imaginary vibrational frequencies. We introduce a simple alternative in which terminal atoms of the model system are placed in soft harmonic confining potentials rather than being rigidly constrained. This modification is simple to implement and straightforward to use in vibrational frequency calculations, unlike iterative constraint-satisfaction algorithms, and allows the optimization to proceed without constraint even though the practical result is to fix the anchor atoms in space. The new approach is more efficient for optimizing minima and transition states, as compared to the use of fixed-atom constraints, and also more robust against unwanted imaginary frequencies. We illustrate the method by application to several enzymatic reaction pathways where entropy makes a significant contribution to the relevant reaction barriers. The use of confining potentials correctly describes reaction paths and facilitates calculation of both vibrational zero-point and finite-temperature entropic corrections to barrier heights.

Computational Insight into the Mechanism of the Irreversible Inhibition of Monoamine Oxidase Enzymes by the Antiparkinsonian Propargylamine Inhibitors Rasagiline and Selegiline

Monoamine oxidases (MAOs) are flavin adenine dinucleotide containing flavoenzymes that catalyze the degradation of a range of brain neurotransmitters, whose imbalance is extensively linked with the pathology of various neurological disorders. This is why MAOs have been the central pharmacological targets in treating neurodegeneration for more than 60 years. Still, despite this practical importance, the precise chemical mechanisms underlying the irreversible inhibition of the MAO B isoform with clinical drugs rasagiline (RAS) and selegiline (SEL) remained unknown. Here we employed a combination of MD simulations, MM-GBSA binding free energy evaluations, and QM cluster calculations to show the MAO inactivation proceeds in three steps, where, in the rate-limiting first step, FAD utilizes its N5 atom to abstracts a hydride anion from the inhibitor α-CH₂ group to ultimately give the final inhibitor-FAD adduct matching crystallographic data. The obtained free energy profiles reveal a lower activation energy for SEL by 1.2 kcal mol^-1 and a higher reaction exergonicity by 0.8 kcal mol^-1, with the former being in excellent agreement with experimental ΔΔG^‡_EXP = 1.7 kcal mol^-1, thus rationalizing its higher in vivo reactivity over RAS. The calculated ΔG_BIND energies confirm SEL binds better due to its bigger size and flexibility allowing it to optimize hydrophobic C-H···π and π···π interactions with residues throughout both of enzyme's cavities, particularly with FAD, Gln206 and four active site tyrosines, thus overcoming a larger ability of RAS to form hydrogen bonds that only position it in less reactive orientations for the hydride abstraction. Offered results elucidate structural determinants affecting the affinity and rates of the inhibition reaction that should be considered to cooperate when designing more effective compounds devoid of untoward effects, which are of utmost significance and urgency with the growing prevalence of brain diseases.

Theoretical Studies of Nickel-Dependent Enzymes

The advancements of quantum chemical methods and computer power allow detailed mechanistic investigations of metalloenzymes. In particular, both quantum chemical cluster and combined QM/MM approaches have been used, which have been proven to successfully complement experimental studies. This review starts with a brief introduction of nickel-dependent enzymes and then summarizes theoretical studies on the reaction mechanisms of these enzymes, including NiFe hydrogenase, methyl-coenzyme M reductase, nickel CO dehydrogenase, acetyl CoA synthase, acireductone dioxygenase, quercetin 2,4-dioxygenase, urease, lactate racemase, and superoxide dismutase.

Computational Protocol to Understand P450 Mechanisms and Design of Efficient and Selective Biocatalysts

Cytochrome P450 enzymes have gained significant interest as selective oxidants in late-stage chemical synthesis. Their broad substrate scope enables them to be good candidates for their use in non-natural reactivity. Directed evolution evolves new enzyme biocatalysts that promote alternative reactivity for chemical synthesis. While directed evolution has proven useful in developing biocatalysts for specific purposes, this process is very time and labor intensive, and therefore not easily repurposed. Computational analysis of these P450 enzymes provides great insights into the broad substrate scope, the variety of reactions catalyzed, the binding specificity and the study of novel biosynthetic reaction mechanisms. By discovering new P450s and studying their reactivities, we uncover new insights into how this reactivity can be harnessed. We discuss a standard protocol using both DFT calculations and MD simulations to study a variety of cytochrome P450 enzymes. The approach entails theozyme models to study the mechanism and transition states via DFT calculations and subsequent MD simulations to understand the conformational poses and binding mechanisms within the enzyme. We discuss a few examples done in collaboration with the Tang and Sherman/Montgomery groups toward elucidating enzyme mechanisms and rationally designing new enzyme mutants as tools for selective C-H functionalization methods.

How does Mo-dependent perchlorate reductase work in the decomposition of oxyanions?

The mechanisms of Mo-dependent perchlorate reductase (PcrAB)-catalyzed decomposition of perchlorate, bromate, iodate, and nitrate were revealed by density functional calculations.