Light-Induced Change of Arginine Conformation Modulates the Rate of Adenosine Triphosphate to Cyclic Adenosine Monophosphate Conversion in the Optogenetic System Containing Photoactivated Adenylyl Cyclase

Computation-driven redesign of an NRPS-like carboxylic acid reductase improves activity and selectivity

Engineering nonribosomal peptide synthetases (NRPSs) has been a "holy grail" in synthetic biology due to their modular nature and limited understanding of catalytic mechanisms. Here, we reported a computational redesign of the "gate-keeper" adenylation domain of the model NRPS-like enzyme carboxylic acid reductases (CARs) by using approximate mechanism-based geometric criteria and the Rosetta energy score. Notably, MabCAR3 mutants ACA-1 and ACA-4 displayed a remarkable improvement in catalytic efficiency (kcat/KM) for 6-aminocaproic acid, up to 101-fold. Furthermore, G418K exhibited an 86-fold enhancement in substrate specificity for adipic acid compared to 6-aminocaproic acid. Our work provides not only promising biocatalysts for nylon monomer biosynthesis but also a strategy for efficient NRPSs engineering.

Systematic QM/MM Study for Predicting 31P NMR Chemical Shifts of Adenosine Nucleotides in Solution and Stages of ATP Hydrolysis in a Protein Environment

NMR (nuclear magnetic resonance) spectroscopy allows for important atomistic insights into the structure and dynamics of biological macromolecules; however, reliable assignments of experimental spectra are often difficult. Herein, quantum mechanical/molecular mechanical (QM/MM) calculations can provide crucial support. A major problem for the simulations is that experimental NMR signals are time-averaged over much longer time scales, and since computed chemical shifts are highly sensitive to local changes in the electronic and structural environment, sufficiently large averages over representative structural ensembles are essential. This entails high computational demands for reliable simulations. For NMR measurements in biological systems, a nucleus of major interest is 31P since it is both highly present (e.g., in nucleic acids) and easily observable. The focus of our present study is to develop a robust and computationally cost-efficient framework for simulating 31P NMR chemical shifts of nucleotides. We apply this scheme to study the different stages of the ATP hydrolysis reaction catalyzed by p97. Our methodology is based on MM molecular dynamics (MM-MD) sampling, followed by QM/MM structure optimizations and NMR calculations. Overall, our study is one of the most comprehensive QM-based 31P studies in a protein environment and the first to provide computed NMR chemical shifts for multiple nucleotide states in a protein environment. This study sheds light on a process that is challenging to probe experimentally and aims to bridge the gap between measured and calculated NMR spectroscopic properties.

Multiscale Simulations of the Covalent Inhibition of the SARS-CoV-2 Main Protease: Four Compounds and Three Reaction Mechanisms

We report the results of computational modeling of the reactions of the SARS-CoV-2 main protease (MPro) with four potential covalent inhibitors. Two of them, carmofur and nirmatrelvir, have shown experimentally the ability to inhibit MPro. Two other compounds, X77A and X77C, were designed computationally in this work. They were derived from the structure of X77, a non-covalent inhibitor forming a tight surface complex with MPro. We modified the X77 structure by introducing warheads capable of reacting with the catalytic cysteine residue in the MPro active site. The reaction mechanisms of the four molecules with MPro were investigated by quantum mechanics/molecular mechanics (QM/MM) simulations. The results show that all four compounds form covalent adducts with the catalytic cysteine Cys 145 of MPro. From the chemical perspective, the reactions of these four molecules with MPro follow three distinct mechanisms. The reactions are initiated by a nucleophilic attack of the thiolate group of the deprotonated cysteine residue from the catalytic dyad Cys145-His41 of MPro. In the case of carmofur and X77A, the covalent binding of the thiolate to the ligand is accompanied by the formation of the fluoro-uracil leaving group. The reaction with X77C follows the nucleophilic aromatic substitution SNAr mechanism. The reaction of MPro with nirmatrelvir (which has a reactive nitrile group) leads to the formation of a covalent thioimidate adduct with the thiolate of the Cys145 residue in the enzyme active site. Our results contribute to the ongoing search for efficient inhibitors of the SARS-CoV-2 enzymes.

Virtual screening of carboxylic acid reductases for biocatalytic synthesis of 6-aminocaproic acid and 1,6-hexamethylenediamine

The key precursors for nylon synthesis, that is, 6-aminocaproic acid (6-ACA) and 1,6-hexamethylenediamine (HMD), are produced from petroleum-based feedstocks. A sustainable biocatalytic alternative method from bio-based adipic acid has been demonstrated recently. However, the low efficiency and specificity of carboxylic acid reductases (CARs) used in the process hampers its further application. Herein, we describe a highly accurate protein structure prediction-based virtual screening method for the discovery of new CARs, which relies on near attack conformation frequency and the Rosetta Energy Score. Through virtual screening and functional detection, five new CARs were selected, each with a broad substrate scope and the highest activities toward various di- and ω-aminated carboxylic acids. Compared with the reported CARs, KiCAR was highly specific with regard to adipic acid without detectable activity to 6-ACA, indicating a potential for 6-ACA biosynthesis. In addition, MabCAR3 had a lower K_m with regard to 6-ACA than the previously validated CAR MAB4714, resulting in twice conversion in the enzymatic cascade synthesis of HMD. The present work highlights the use of structure-based virtual screening for the rapid discovery of pertinent new biocatalysts.

How Reproducible Are QM/MM Simulations? Lessons from Computational Studies of the Covalent Inhibition of the SARS-CoV-2 Main Protease by Carmofur

This work explores the level of transparency in reporting the details of computational protocols that is required for practical reproducibility of quantum mechanics/molecular mechanics (QM/MM) simulations. Using the reaction of an essential SARS-CoV-2 enzyme (the main protease) with a covalent inhibitor (carmofur) as a test case of chemical reactions in biomolecules, we carried out QM/MM calculations to determine the structures and energies of the reactants, the product, and the transition state/intermediate using analogous QM/MM models implemented in two software packages, NWChem and Q-Chem. Our main benchmarking goal was to reproduce the key energetics computed with the two packages. Our results indicate that quantitative agreement (within the numerical thresholds used in calculations) is difficult to achieve. We show that rather minor details of QM/MM simulations must be reported in order to ensure the reproducibility of the results and offer suggestions toward developing practical guidelines for reporting the results of biosimulations.

Two Sides of Quantum-Based Modeling of Enzyme-Catalyzed Reactions: Mechanistic and Electronic Structure Aspects of the Hydrolysis by Glutamate Carboxypeptidase

We report the results of a computational study of the hydrolysis reaction mechanism of N-acetyl-l-aspartyl-l-glutamate (NAAG) catalyzed by glutamate carboxypeptidase II. Analysis of both mechanistic and electronic structure aspects of this multistep reaction is in the focus of this work. In these simulations, model systems are constructed using the relevant crystal structure of the mutated inactive enzyme. After selection of reaction coordinates, the Gibbs energy profiles of elementary steps of the reaction are computed using molecular dynamics simulations with ab initio type QM/MM potentials (QM/MM MD). Energies and forces in the large QM subsystem are estimated in the DFT(PBE0-D3/6-31G**) approximation. The established mechanism includes four elementary steps with the activation energy barriers not exceeding 7 kcal/mol. The models explain the role of point mutations in the enzyme observed in the experimental kinetic studies; namely, the Tyr552Ile substitution disturbs the "oxyanion hole", and the Glu424Gln replacement increases the distance of the nucleophilic attack. Both issues diminish the substrate activation in the enzyme active site. To quantify the substrate activation, we apply the QTAIM-based approaches and the NBO analysis of dynamic features of the corresponding enzyme-substrate complexes. Analysis of the 2D Laplacian of electron density maps allows one to define structures with the electron density deconcentration on the substrate carbon atom, i.e., at the electrophilic site of reactants. The similar electronic structure element in the NBO approach is a lone vacancy on the carbonyl carbon atom in the reactive species. The electronic structure patterns revealed in the NBO and QTAIM-based analyses consistently clarify the reactivity issues in this system.

Mechanism of Guanosine Triphosphate Hydrolysis by the Visual Proteins Arl3-RP2: Free Energy Reaction Profiles Computed with Ab Initio Type QM/MM Potentials

We report the results of calculations of the Gibbs energy profiles of the guanosine triphosphate (GTP) hydrolysis by the Arl3-RP2 protein complex using molecular dynamics (MD) simulations with ab initio type QM/MM potentials. The chemical reaction of GTP hydrolysis to guanosine diphosphate (GDP) and inorganic phosphate (Pi) is catalyzed by GTPases, the enzymes, which are responsible for signal transduction in live cells. A small GTPase Arl3, catalyzing the GTP → GDP reaction in complex with the activating protein RP2, constitute an essential part of the human vision cycle. To simulate the reaction mechanism, a model system is constructed by motifs of the crystal structure of the Arl3-RP2 complexed with a substrate analog. After selection of reaction coordinates, energy profiles for elementary steps along the reaction pathway GTP + H2O → GDP + Pi are computed using the umbrella sampling and umbrella integration procedures. QM/MM MD calculations are carried out, interfacing the molecular dynamics program NAMD and the quantum chemistry program TeraChem. Ab initio type QM(DFT)/MM potentials are computed with atom-centered basis sets 6-31G** and two hybrid functionals (PBE0-D3 and ωB97x-D3) of the density functional theory, describing a large QM subsystem. Results of these simulations of the reaction mechanism are compared to those obtained with QM/MM calculations on the potential energy surface using a similar description of the QM part. We find that both approaches, QM/MM and QM/MM MD, support the mechanism of GTP hydrolysis by GTPases, according to which the catalytic glutamine side chain (Gln71, in this system) actively participates in the reaction. Both approaches distinguish two parts of the reaction: the cleavage of the phosphorus-oxygen bond in GTP coupled with the formation of Pi, and the enzyme regeneration. Newly performed QM/MM MD simulations confirmed the profile predicted in the QM/MM minimum energy calculations, called here the pathway-I, and corrected its relief at the first elementary step from the enzyme-substrate complex. The QM/MM MD simulations also revealed another mechanism at the part of enzyme regeneration leading to pathway-II. Pathway-II is more consistent with the experimental kinetic data of the wild-type complex Arl3-RP2, whereas pathway-I explains the role of the mutation Glu138Gly in RP2 slowing down the hydrolysis rate.

Boronic Acids as Prospective Inhibitors of Metallo-β-Lactamases: Efficient Chemical Reaction in the Enzymatic Active Site Revealed by Molecular Modeling

Boronic acids are prospective compounds in inhibition of metallo-β-lactamases as they form covalent adducts with the catalytic hydroxide anion in the enzymatic active site upon binding. We compare this chemical reaction in the active site of the New Delhi metallo-β-lactamase (NDM-1) with the hydrolysis of the antibacterial drug imipenem. The nucleophilic attack occurs with the energy barrier of 14 kcal/mol for imipenem and simultaneously upon binding a boronic acid inhibitor. A boron atom of an inhibitor exhibits stronger electrophilic properties than the carbonyl carbon atom of imipenem in a solution that is quantified by atomic Fukui indices. Upon forming the prereaction complex between NDM-1 and inhibitor, the lone electron pair of the nucleophile interacts with the vacant p-orbital of boron that facilitates the chemical reaction. We analyze a set of boronic acid compounds with the benzo[b]thiophene core complexed with the NDM-1 and propose quantitative structure-sroperty relationship (QSPR) equations that can predict IC50 values from the calculated descriptors of electron density. These relations are applied to classify other boronic acids with the same core found in the database of chemical compounds, PubChem, and proposed ourselves. We demonstrate that the IC50 values for all considered benzo[b]thiophene-containing boronic acid inhibitors are 30-70 μM.