QM/MM simulations identify the determinants of catalytic activity differences between type II dehydroquinase enzymes

Molecular Mechanism of Labelling Functional Cysteines by Heterocyclic Thiones

Heterocyclic thiones have recently been identified as reversible covalent warheads, consistent with their mild electrophilic nature. Little is known so far about their mechanism of action in labelling nucleophilic sidechains, especially cysteines. The vast number of tractable cysteines promotes a wide range of target proteins to examine; however, our focus was put on functional cysteines. We chose the main protease of SARS-CoV-2 harboring Cys145 at the active site that is a structurally characterized and clinically validated target of covalent inhibitors. We screened an in-house, cysteine-targeting covalent inhibitor library which resulted in several covalent fragment hits with benzoxazole, benzothiazole and benzimidazole cores. Thione derivatives and Michael acceptors were selected for further investigations with the objective of exploring the mechanism of inhibition of the thiones and using the thoroughly characterized Michael acceptors for benchmarking our studies. Classical and hybrid quantum mechanical/molecular mechanical (QM/MM) molecular dynamics simulations were carried out that revealed a new mechanism of covalent cysteine labelling by thione derivatives, which was supported by QM and free energy calculations and by a wide range of experimental results. Our study shows that the molecular recognition step plays a crucial role in the overall binding of both sets of molecules.

Multiscale QM/MM Simulations Identify the Roles of Asp239 and 1-OH···Nucleophile in Transition State Stabilization in Arabidopsis thaliana Cell-Wall Invertase 1

Arabidopsis thaliana cell-wall invertase 1 (AtCWIN1), a key enzyme in sucrose metabolism in plants, catalyzes the hydrolysis of sucrose into fructose and glucose. AtCWIN1 belongs to the glycoside hydrolase GH-J clan, where two carboxylate residues (Asp23 and Glu203 in AtCWIN1) are well documented as a nucleophile and an acid/base catalyst. However, details at the atomic level about the role of neighboring residues and enzyme-substrate interactions during catalysis are not fully understood. Here, quantum mechanical/molecular mechanical (QM/MM) free-energy simulations were carried out to clarify the origin of the observed decreased rates in Asp239Ala, Asp239Asn, and Asp239Phe in AtCWIN1 compared to the wild type and delineate the role of Asp239 in catalysis. The glycosylation and deglycosylation steps were considered in both wild type and mutants. Deglycosylation is predicted to be the rate-determining step in the reaction, with a calculated overall free-energy barrier of 15.9 kcal/mol, consistent with the experimental barrier (15.3 kcal/mol). During the reaction, the -1 furanosyl ring underwent a conformational change corresponding to 3E ↔ [E2]⧧ ↔ 1E according to the nomenclature of saccharide structures along the full catalytic reaction. Asp239 was found to stabilize not only the transition state but also the fructosyl-enzyme intermediate, which explains findings from previous structural and mutagenesis experiments. The 1-OH···nucleophile interaction has been found to provide an important contribution to the transition state stabilization, with a contribution of ∼7 kcal/mol, and affected glycosylation more significantly than deglycosylation. This study provides molecular insights that improve the current understanding of sucrose binding and hydrolysis in members of clan GH-J, which may benefit protein engineering research. Finally, a rationale on the sucrose inhibitor configuration in chicory 1-FEH IIa, proposed a long time ago in the literature, is also provided based on the QM/MM calculations.

Mechanism of Chiral-Selective Aminoacylation of an RNA Minihelix Explored by QM/MM Free-Energy Simulations

Aminoacylation of a primordial RNA minihelix composed of D-ribose shows L-amino acid preference over D-amino acid without any ribozymes or enzymes. This preference in the amino acylation reaction likely plays an important role in the establishment of homochirality in L-amino acid in modern proteins. However, molecular mechanisms of the chiral selective reaction remain unsolved mainly because of difficulty in direct observation of the reaction at the molecular scale by experiments. For seeking a possible mechanism of the chiral selectivity, quantum mechanics/molecular mechanics (QM/MM) umbrella sampling molecular dynamics (MD) simulations of the aminoacylation reactions in a modeled RNA were performed to investigate differences in their free-energy profiles along the reactions for L- and D-alanine and its physicochemical origin. The reaction is initiated by approaching a 3′-oxygen of the RNA minihelix to the carbonyl carbon of an aminoacyl phosphate oligonucleotide. The QM/MM umbrella sampling MD calculations showed that the height of the free-energy barrier for L-alanine aminoacylation reaction was 17 kcal/mol, which was 9 kcal/mol lower than that for the D-alanine system. At the transition state, the distance between the negatively charged 3′-oxygen and the positively charged amino group of L-alanine was shorter than that of D-alanine, which was caused by the chirality difference of the amino acid. These results indicate that the transition state for L-alanine is more electrostatically stabilized than that for D-alanine, which would be a plausible mechanism previously unexplained for chiral selectivity in the RNA minihelix aminoacylation.

Towards solvent regulated self-activation of N-terminal disulfide bond oxidoreductase-D

N-terminal disulfide bond oxidoreductase-D (nDsbD), an essential redox enzyme in Gram-negative bacteria, consists of a single disulfide bond (Cys₁₀₃-Cys₁₀₉) in its active site. The enzymatic functions are believed to be regulated by an electron transfer mediated redox switching of the disulfide bond, which is vital in controlling bacterial virulence factors. In light of the disulfide bond's inclination towards nucleophilic cleavage, it is also plausible that an internal nucleophile could second the existing electron transfer mechanism in nDsbD. Using QM/MM MD metadynamics simulations, we explore different possibilities of generating an internal nucleophile near the nDsbD active site, which could serve as a fail-over mechanism in cleaving the disulfide bond. The simulations show the formation of the internal nucleophile Tyr₄₂O^- (F ≈ 9 kcal mol^-1) and its stabilization through the solvent medium. The static gas-phase calculations show that Tyr₄₂O^- could be a potential nucleophile for cleaving the S-S bond. Most strikingly, it is also seen that Tyr₄₂O^- and Asp₆₈OH communicate with each other through a proton-hole like water wire (F ≈ 12 kcal mol^-1), thus modulating the nucleophile formation. Accordingly, we propose the role of a solvent in regulating the internal nucleophilic reactions and the subsequent self-activation of nDsbD. We believe that this could be deterministic while designing enzyme-targeted inhibitor compounds.

Identification of new putative inhibitors of Mycobacterium tuberculosis 3-dehydroshikimate dehydratase from a combination of ligand- and structure-based and deep learning in silico approaches

The development of new drugs against Mycobacterium tuberculosis is an essential strategy for fighting drug resistance. Although 3-dehydroquinate dehydratase (MtDHQ) is known to be a highly relevant target for M. tuberculosis, current research shows new putative inhibitors of MtDHQ selected by a large-scale ensemble-docking strategy combining ligand- and target-based chemoinformatic methods to deep learning. Initial chemical library was reduced from 216 million to approximately 460 thousand after pharmacophore, toxicity and molecular weight filters. Final library was subjected to an ensemble-docking protocol in GOLD which selected the top 300 molecules (GHITS). GHITS displayed different structures and characteristics when compared to known inhibitors (KINH). GHITS were further screened by post-docking analysis in AMMOS2 and deep learning virtual screening in DeepPurpose. DeepPurpose predicted that a number of GHITS had comparable or better affinity for the target than KINH. The best molecule was selected by consensus ranking using GOLD, AMMOS2 and DeepPurpose scores. Molecular dynamics revealed that the top hit displayed consistent and stable binding to MtDHQ, making strong interactions with active-site loop residues. Results forward new putative inhibitors of MtDHQ and reinforce the potential application of artificial intelligence methods for drug design. This work represents the first step in the validation of these molecules as inhibitors of MtDHQ.

Characterization of a highly xylose tolerant β-xylosidase isolated from high temperature horse manure compost

BACKGROUND

There is a continued need for improved enzymes for industry. β-xylosidases are enzymes employed in a variety of industries and although many wild-type and engineered variants have been described, enzymes that are highly tolerant of the products produced by catalysis are not readily available and the fundamental mechanisms of tolerance are not well understood.

RESULTS

Screening of a metagenomic library constructed of mDNA isolated from horse manure compost for β-xylosidase activity identified 26 positive hits. The fosmid clones were sequenced and bioinformatic analysis performed to identity putative β-xylosidases. Based on the novelty of its amino acid sequence and potential thermostability one enzyme (XylP81) was selected for expression and further characterization. XylP81 belongs to the family 39 β-xylosidases, a comparatively rarely found and characterized GH family. The enzyme displayed biochemical characteristics (K_M-5.3 mM; V_max-122 U/mg; k_cat-107; T_opt-50 °C; pH_opt-6) comparable to previously characterized glycoside hydrolase family 39 (GH39) β-xylosidases and despite nucleotide identity to thermophilic species, the enzyme displayed only moderate thermostability with a half-life of 32 min at 60 °C. Apart from acting on substrates predicted for β-xylosidase (xylobiose and 4-nitrophenyl-β-D-xylopyranoside) the enzyme also displayed measurable α-L-arabainofuranosidase, β-galactosidase and β-glucosidase activity. A remarkable feature of this enzyme is its ability to tolerate high concentrations of xylose with a K_i of 1.33 M, a feature that is highly desirable for commercial applications.

CONCLUSIONS

Here we describe a novel β-xylosidase from a poorly studied glycosyl hydrolase family (GH39) which despite having overall kinetic properties similar to other bacterial GH39 β-xylosidases, displays unusually high product tolerance. This trait is shared with only one other member of the GH39 family, the recently described β-xylosidases from Dictyoglomus thermophilum. This feature should allow its use as starting material for engineering of an enzyme that may prove useful to industry and should assist in the fundamental understanding of the mechanism by which glycosyl hydrolases evolve product tolerance.

Mechanistic and thermodynamic characterization of oxathiazolones as potent and selective covalent immunoproteasome inhibitors

The ubiquitin–proteasome system is responsible for the degradation of proteins and plays a critical role in key cellular processes. While the constitutive proteasome (cPS) is expressed in all eukaryotic cells, the immunoproteasome (iPS) is primarily induced during disease processes, and its inhibition is beneficial in the treatment of cancer, autoimmune disorders and neurodegenerative diseases. Oxathiazolones were reported to selectively inhibit iPS over cPS, and the inhibitory activity of several oxathiazolones against iPS was experimentally determined. However, the detailed mechanism of the chemical reaction leading to irreversible iPS inhibition and the key selectivity drivers are unknown, and separate characterization of the noncovalent and covalent inhibition steps is not available for several compounds. Here, we investigate the chemical reaction between oxathiazolones and the Thr1 residue of iPS by quantum mechanics/molecular mechanics (QM/MM) simulations to establish a plausible reaction mechanism and to determine the rate-determining step of covalent complex formation. The modelled binding mode and reaction mechanism are in line with the selective inhibition of iPS versus cPS by oxathiazolones. The k_inact value of several ligands was estimated by constructing the potential of mean force of the rate-determining step by QM/MM simulations coupled with umbrella sampling. The equilibrium constant K_i of the noncovalent complex formation was evaluated by classical force field-based thermodynamic integration. The calculated K_i and k_inact values made it possible to analyse the contribution of the noncovalent and covalent steps to the overall inhibitory activity. Compounds with similar intrinsic reactivities exhibit varying selectivities for iPS versus cPS owing to subtle differences in the binding modes that slightly affect K_i, the noncovalent affinity, and importantly alter k_inact, the covalent reactivity of the bound compounds. A detailed understanding of the inhibitory mechanism of oxathiazolones is useful in designing iPS selective inhibitors with improved drug-like properties.

Exploring Covalent Docking Mechanisms of Boron-Based Inhibitors to Class A, C and D β-Lactamases Using Time-dependent Hybrid QM/MM Simulations

Recently, molecular covalent docking has been extensively developed to design new classes of inhibitors that form chemical bonds with their biological targets. This strategy for the design of such inhibitors, in particular boron-based inhibitors, holds great promise for the vast family of β-lactamases produced, inter alia, by Gram-negative antibiotic-resistant bacteria. However, the description of covalent docking processes requires a quantum-mechanical approach, and so far, only a few studies of this type have been presented. This study accurately describes the covalent docking process between two model inhibitors - representing two large families of inhibitors based on boronic-acid and bicyclic boronate scaffolds, and three β-lactamases which belong to the A, C, and D classes. Molecular fragments containing boron can be converted from a neutral, trigonal, planar state with sp2 hybridization to the anionic, tetrahedral sp3 state in a process sometimes referred to as morphing. This study applies multi-scale modeling methods, in particular, the hybrid QM/MM approach which has predictive power reaching well beyond conventional molecular modeling. Time-dependent QM/MM simulations indicated several structural changes and geometric preferences, ultimately leading to covalent docking processes. With current computing technologies, this approach is not computationally expensive, can be used in standard molecular modeling and molecular design works, and can effectively support experimental research which should allow for a detailed understanding of complex processes important to molecular medicine. In particular, it can support the rational design of covalent boron-based inhibitors for β-lactamases as well as for many other enzyme systems of clinical relevance, including SARS-CoV-2 proteins.

A Review of Recent Developments in Molecular Dynamics Simulations of the Photoelectrochemical Water Splitting Process

In this review, we provide a short overview of the Molecular Dynamics (MD) method and how it can be used to model the water splitting process in photoelectrochemical hydrogen production. We cover classical non-reactive and reactive MD techniques as well as multiscale extensions combining classical MD with quantum chemical and continuum methods. Selected examples of MD investigations of various aqueous semiconductor interfaces with a special focus on TiO2 are discussed. Finally, we identify gaps in the current state-of-the-art where further developments will be needed for better utilization of MD techniques in the field of water splitting.

Exploring the Minimum-Energy Pathways and Free-Energy Profiles of Enzymatic Reactions with QM/MM Calculations

Understanding molecular mechanisms of enzymatic reactions is of vital importance in biochemistry and biophysics. Here, we introduce new functions of hybrid quantum mechanical/molecular mechanical (QM/MM) calculations in the GENESIS program to compute the minimum-energy pathways (MEPs) and free-energy profiles of enzymatic reactions. For this purpose, an interface in GENESIS is developed to utilize a highly parallel electronic structure program, QSimulate-QM (https://qsimulate.com), calling it as a shared library from GENESIS. Second, algorithms to search the MEP are implemented, combining the string method (E et al. J. Chem. Phys. 2007, 126, 164103) with the energy minimization of the buffer MM region. The method implemented in GENESIS is applied to an enzyme, triosephosphate isomerase, which converts dihyroxyacetone phosphate to glyceraldehyde 3-phosphate in four proton-transfer processes. QM/MM-molecular dynamics simulations show performances of greater than 1 ns/day with the density functional tight binding (DFTB), and 10-30 ps/day with the hybrid density functional theory, B3LYP-D3. These performances allow us to compute not only MEP but also the potential of mean force (PMF) of the enzymatic reactions using the QM/MM calculations. The barrier height obtained as 13 kcal mol-1 with B3LYP-D3 in the QM/MM calculation is in agreement with the experimental results. The impact of conformational sampling in PMF calculations and the level of electronic structure calculations (DFTB vs B3LYP-D3) suggests reliable computational protocols for enzymatic reactions without high computational costs.

Active site dynamics and catalytic mechanism in arabinan hydrolysis catalyzed by GH43 endo-arabinanase from QM/MM molecular dynamics simulation and potential energy surface

The endo-1,5-α-L-arabinanases, belonging to glycoside hydrolase family 43 (GH43), catalyse the hydrolysis of α-1,5-arabinofuranosidic bonds in arabinose-containing polysaccharides. These enzymes are proposed targets for industrial and medical applications. Here, molecular dynamics (MD), potential energy surface and free energy (potential of mean force) simulations are undertaken using hybrid quantum mechanical/molecular mechanical (QM/MM) potentials to understand the active site dynamics, catalytic mechanism and the electrostatic influence of active site residues of the GH43 endo-arabinanase from G. stearothermophilus. The calculated results give support to the single-displacement mechanism proposed for the inverting GH43 enzymes: first a proton is transferred from the general acid E201 to the substrate, followed by a nucleophilic attack by water, activated by the general base D27, on the anomer carbon. A conformational change (²E ↔E₃ ↔ ⁴E) in the -1 sugar ring is observed involving a transition state featuring an oxocarbenium ion character. Residues D87, K106, H271 are highlighted as potential targets for future mutation experiments in order to increase the efficiency of the reaction. To our knowledge, this is the first QM/MM study providing molecular insights into the glycosidic bond hydrolysis of a furanoside substrate by an inverting GH in solution.Communicated by Ramaswamy H. Sarma.

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.

Benchmarking quantum mechanical methods for calculating reaction energies of reactions catalyzed by enzymes

To assess the accuracy of different quantum mechanical methods for biochemical modeling, the reaction energies of 20 small model reactions (chosen to represent chemical steps catalyzed by commonly studied enzymes) were calculated. The methods tested included several popular Density Functional Theory (DFT) functionals, second-order Møller Plesset perturbation theory (MP2) and its spin-component scaled variant (SCS-MP2), and coupled cluster singles and doubles and perturbative triples (CCSD(T)). Different basis sets were tested. CCSD(T)/aug-cc-pVTZ results for all 20 reactions were used to benchmark the other methods. It was found that MP2 and SCS-MP2 reaction energy calculation results are similar in quality to CCSD(T) (mean absolute error (MAE) of 1.2 and 1.3 kcal mol−1, respectively). MP2 calculations gave a large error in one case, and are more subject to basis set effects, so in general SCS-MP2 calculations are a good choice when CCSD(T) calculations are not feasible. Results with different DFT functionals were of reasonably good quality (MAEs of 2.5–5.1 kcal mol−1), whereas popular semi-empirical methods (AM1, PM3, SCC-DFTB) gave much larger errors (MAEs of 11.6–14.6 kcal mol−1). These results should be useful in guiding methodological choices and assessing the accuracy of QM/MM calculations on enzyme-catalyzed reactions.

Enhanced sampling and free energy calculations for protein simulations

Molecular dynamics simulation is a powerful computational technique to study biomolecular systems, which complements experiments by providing insights into the structural dynamics relevant to biological functions at atomic scale. It can also be used to calculate the free energy landscapes of the conformational transitions to better understand the functions of the biomolecules. However, the sampling of biomolecular configurations is limited by the free energy barriers that need to be overcome, leading to considerable gaps between the timescales reached by MD simulation and those governing biological processes. To address this issue, many enhanced sampling methodologies have been developed to increase the sampling efficiency of molecular dynamics simulations and free energy calculations. Usually, enhanced sampling algorithms can be classified into methods based on collective variables (CV-based) and approaches which do not require predefined CVs (CV-free). In this chapter, the theoretical basis of free energy estimation is briefly reviewed first, followed by the reviews of the most common CV-based and CV-free methods including the presentation of some examples and recent developments. Finally, the combination of different enhanced sampling methods is discussed.

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.

Photogeneration of Quinone Methides as Latent Electrophiles for Lysine Targeting

Latent electrophiles are nowadays very attractive chemical entities for drug discovery, as they are unreactive unless activated upon binding with the specific target. In this work, the utility of 4-trifluoromethyl phenols as precursors of latent electrophiles, quinone methides (QM), for lysine-targeting is demonstrated. These Michael acceptors were photogenerated for specific covalent modification of lysine residues using human serum albumin (HSA) as a model target. The reactive QM-type intermediates I or II, generated upon irradiation of 4-trifluoromethyl-1-naphthol (1)@HSA or 4-(4-trifluorometylphenyl)phenol (2)@HSA complexes, exhibited chemoselective reactivity toward lysine residues leading to amide adducts, which was confirmed by proteomic analysis. For ligand 1, the covalent modification of residues Lys106 and Lys414 (located in subdomains IA and IIIA, respectively) was observed, whereas for ligand 2, the modification of Lys195 (in subdomain IIA) took place. Docking and molecular dynamics simulation studies provided an insight into the molecular basis of the selectivity of 1 and 2 for these HSA subdomains and the covalent modification mechanism. These studies open the opportunity of performing protein silencing by generating reactive ligands under very mild conditions (irradiation) for specific covalent modification of hidden lysine residues.