Conserved interactions required for inhibition of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The COVID-19 pandemic caused by the SARS-CoV-2 requires a fast development of antiviral drugs. SARS-CoV-2 viral main protease (Mpro, also called 3C-like protease, 3CLpro) is a potential target for drug design. Crystal and co-crystal structures of the SARS-CoV-2 Mpro have been solved, enabling the rational design of inhibitory compounds. In this study we analyzed the available SARS-CoV-2 and the highly similar SARS-CoV-1 crystal structures. We identified within the active site of the Mpro, in addition to the inhibitory ligands' interaction with the catalytic C145, two key H-bond interactions with the conserved H163 and E166 residues. Both H-bond interactions are present in almost all co-crystals and are likely to occur also during the viral polypeptide cleavage process as suggested from docking of the Mpro cleavage recognition sequence. We screened in silico a library of 6900 FDA-approved drugs (ChEMBL) and filtered using these key interactions and selected 29 non-covalent compounds predicted to bind to the protease. Additional screen, using DOCKovalent was carried out on DrugBank library (11,414 experimental and approved drugs) and resulted in 6 covalent compounds. The selected compounds from both screens were tested in vitro by a protease activity inhibition assay. Two compounds showed activity at the 50 µM concentration range. Our analysis and findings can facilitate and focus the development of highly potent inhibitors against SARS-CoV-2 infection.

Free energy simulations of active-site mutants of dihydrofolate reductase.

This study employs hybrid quantum mechanics-molecular mechanics (QM/MM) simulations to investigate the effect of mutations of the active-site residue I14 of E. coli dihydrofolate reductase (DHFR) on the hydride transfer. Recent kinetic measurements of the I14X mutants (X = V, A, and G) indicated slower hydride transfer rates and increasingly temperature-dependent kinetic isotope effects (KIEs) with systematic reduction of the I14 side chain. The QM/MM simulations show that when the original isoleucine residue is substituted in silico by valine, alanine, or glycine (I14V, I14A, and I14G DHFR, respectively), the free energy barrier height of the hydride transfer reaction increases relative to the wild-type enzyme. These trends are in line with the single-turnover rate measurements reported for these systems. In addition, extended dynamics simulations of the reactive Michaelis complex reveal enhanced flexibility in the mutants, and in particular for the I14G mutant, including considerable fluctuations of the donor-acceptor distance (DAD) and the active-site hydrogen bonding network compared with those detected in the native enzyme. These observations suggest that the perturbations induced by the mutations partly impair the active-site environment in the reactant state. On the other hand, the average DADs at the transition state of all DHFR variants are similar. Crystal structures of I14 mutants (V, A, and G) confirmed the trend of increased flexibility of the M20 and other loops.

Challenges in computational studies of enzyme structure, function and dynamics.

In this review we give an overview of the field of Computational enzymology. We start by describing the birth of the field, with emphasis on the work of the 2013 chemistry Nobel Laureates. We then present key features of the state-of-the-art in the field, showing what theory, accompanied by experiments, has taught us so far about enzymes. We also briefly describe computational methods, such as quantum mechanics-molecular mechanics approaches, reaction coordinate treatment, and free energy simulation approaches. We finalize by discussing open questions and challenges.

How Accurate Are Transition States from Simulations of Enzymatic Reactions?

The rate expression of traditional transition state theory (TST) assumes no recrossing of the transition state (TS) and thermal quasi-equilibrium between the ground state and the TS. Currently, it is not well understood to what extent these assumptions influence the nature of the activated complex obtained in traditional TST-based simulations of processes in the condensed phase in general and in enzymes in particular. Here we scrutinize these assumptions by characterizing the TSs for hydride transfer catalyzed by the enzyme Escherichia coli dihydrofolate reductase obtained using various simulation approaches. Specifically, we compare the TSs obtained with common TST-based methods and a dynamics-based method. Using a recently developed accurate hybrid quantum mechanics/molecular mechanics potential, we find that the TST-based and dynamics-based methods give considerably different TS ensembles. This discrepancy, which could be due equilibrium solvation effects and the nature of the reaction coordinate employed and its motion, raises major questions about how to interpret the TSs determined by common simulation methods. We conclude that further investigation is needed to characterize the impact of various TST assumptions on the TS phase-space ensemble and on the reaction kinetics.

Simulations of remote mutants of dihydrofolate reductase reveal the nature of a network of residues coupled to hydride transfer.

Recent experimental and theoretical studies have proposed that enzymes involve networks of coupled residues throughout the protein that participate in motions accompanying chemical barrier crossing. Here, we have examined portions of a proposed network in dihydrofolate reductase (DHFR) using quantum mechanics/molecular mechanics simulations. The simulations use a hybrid quantum mechanics-molecular mechanics approach with a recently developed semiempirical AM1-SRP Hamiltonian that provides accurate results for this reaction. The simulations reproduce experimentally determined catalytic rates for the wild type and distant mutants of E. coli DHFR, underscoring the accuracy of the simulation protocol. Additionally, the simulations provide detailed insight into how residues remote from the active site affect the catalyzed chemistry, through changes in the thermally averaged properties along the reaction coordinate. The mutations do not greatly affect the structure of the transition state near the bond activation, but we observe differences somewhat removed from the point of C-H cleavage that affect the rate. The mutations have global effects on the thermally averaged structure that propagate throughout the enzyme and the current simulations highlight several interactions that appear to be particularly important.

Quantum and classical simulations of orotidine monophosphate decarboxylase: support for a direct decarboxylation mechanism.

Orotidine 5'-monophosphate (OMP) decarboxylase (ODCase) catalyzes the decarboxylation of OMP to uridine 5'-monophosphate (UMP). Numerous studies of this reaction have suggested a plethora of mechanisms including covalent addition, ylide or carbene formation, and concerted or stepwise protonation. Recent experiments and simulations present strong evidence for a direct decarboxylation mechanism, although direct comparison between experiment and theory is still lacking. In the current work we present hybrid quantum mechanics-molecular mechanics simulations that address the detailed decarboxylation mechanisms for OMP and 5-fluoro-OMP by ODCase. Multidimensional potentials of mean force are computed as functions of structural progress coordinates for the Methanobacterium thermoautotrophicum ODCase reaction: the decarboxylation reaction coordinate, an orbital rehybridization coordinate, and the proton transfer coordinate between Lys72 and the substrate. The computed free energy profiles are in accord with the available experimental data. To facilitate further direct comparison with experiment, we compute the kinetic isotope effects (KIEs) for the enzyme-catalyzed reactions using a mass-perturbation-based path-integral method. The computed KIE provide further support for a direct decarboxylation mechanism. In agreement with experiment, the data suggest a role for Lys72 in stabilizing the transition state in the catalysis of OMP and, to a somewhat lesser extent, in 5-fluoro-OMP.

Collective Reaction Coordinate for Hybrid Quantum and Molecular Mechanics Simulations: A Case Study of the Hydride Transfer in Dihydrofolate Reductase.

The optimal description of the reaction coordinate in chemical systems is of great importance in simulating condensed phase reactions. In the current work, we present a collective reaction coordinate which is composed of several geometric coordinates which represent structural progress during the course of a hydride transfer reaction: the antisymmetric reactive stretch coordinate, the donor-acceptor distance (DAD) coordinate, and an orbital rehybridization coordinate. In this approach, the former coordinate serves as a distinguished reaction coordinate, while the latter two serve as environmental, Marcus-type inner-sphere reorganization coordinates. The classical free energy surface is obtained from multidimensional quantum mechanics-molecular mechanics (QM/MM) potential of mean force (PMF) simulations in conjunction with a general and efficient multidimensional weighted histogram method implementation. The minimum free energy path, or the collective reaction coordinate, connecting the dividing hypersurface to reactants and products, is obtained using an iterative scheme. In this approach, the string method is used to find the minimum free energy path. This path guides the multidimensional sampling, while the path is adaptively refined until convergence is achieved. As a model system, we choose the hydride transfer reaction in Escherichia coli dihydrofolate reductase (ecDHFR) using a recently developed accurate semiempirical potential energy surface. To estimate the advantages of the collective reaction coordinate, we perform activated dynamics simulations to obtain the reaction transmission coefficient. The results show that the combination of a distinguished reaction coordinate and an inner-sphere reorganization coordinate considerably reduces the dividing surface recrossing.

Momentum Distribution as a Fingerprint of Quantum Delocalization in Enzymatic Reactions: Open-Chain Path-Integral Simulations of Model Systems and the Hydride Transfer in Dihydrofolate Reductase.

The inclusion of nuclear quantum effects such as zero-point energy and tunneling is of great importance in studying condensed phase chemical reactions involving the transfer of protons, hydrogen atoms, and hydride ions. In the current work, we derive an efficient quantum simulation approach for the computation of the momentum distribution in condensed phase chemical reactions. The method is based on a quantum-classical approach wherein quantum and classical simulations are performed separately. The classical simulations use standard sampling techniques, whereas the quantum simulations employ an open polymer chain path integral formulation which is computed using an efficient Monte Carlo staging algorithm. The approach is validated by applying it to a one-dimensional harmonic oscillator and symmetric double-well potential. Subsequently, the method is applied to the dihydrofolate reductase (DHFR) catalyzed reduction of 7,8-dihydrofolate by nicotinamide adenine dinucleotide phosphate hydride (NADPH) to yield S-5,6,7,8-tetrahydrofolate and NADP(+). The key chemical step in the catalytic cycle of DHFR involves a stereospecific hydride transfer. In order to estimate the amount of quantum delocalization, we compute the position and momentum distributions for the transferring hydride ion in the reactant state (RS) and transition state (TS) using a recently developed hybrid semiempirical quantum mechanics-molecular mechanics potential energy surface. Additionally, we examine the effect of compression of the donor-acceptor distance (DAD) in the TS on the momentum distribution. The present results suggest differential quantum delocalization in the RS and TS, as well as reduced tunneling upon DAD compression.

Hybrid Quantum and Classical Simulations of the Formate Dehydrogenase Catalyzed Hydride Transfer Reaction on an Accurate Semiempirical Potential Energy Surface.

Formate dehydrogenase (FDH) catalyzes the oxidation of formic acid to carbon dioxide using nicotinamide adenine dinucleotide (NAD(+)) as a cofactor. In the current work we present extensive benchmark calculations for several model reactions in the gas phase that are relevant to the FDH catalyzed hydride transfer. To this end we employ G4MP2 and CBS-QB3 ab initio calculations as well as density functional theory methods. Using these results we develop a specific reaction parameter (SRP) Hamiltonian based on the semiempirical AM1 method. The SRP semiempirical Hamiltonian is subsequently used in hybrid quantum mechanics/molecular mechanics simulations of the FDH catalyzed reaction in Pseudomonas sp. 101 (PseFDH). The classical potential of mean force (PMF) is computed as a function of structural progress coordinates during the course of the hydride transfer reaction: The antisymmetric reactive stretch, the donor-acceptor distance, and an orbital rehybridization coordinate. The quantum PMF is computed using a centroid Feynman path-integral (PI) approach. Subsequently, kinetic isotope effects are computed using a mass-perturbation based PI method. Finally, the antisymmetric stretch vibrational frequency is computed for an azide ion in FDH and in aqueous solution.

Hybrid Quantum and Classical Simulations of the Dihydrofolate Reductase Catalyzed Hydride Transfer Reaction on an Accurate Semi-Empirical Potential Energy Surface.

Dihydrofolate reductase (DHFR) catalyzes the reduction of 7,8-dihydrofolate by nicotinamide adenine dinucleotide phosphate hydride (NADPH) to form 5,6,7,8-tetrahydrofolate and oxidized nicotinamide. DHFR is a small, flexible, monomeric protein with no metals or SS bonds and serves as one of the enzymes commonly used to examine basic aspects in enzymology. In the current work, we present extensive benchmark calculations for several model reactions in the gas phase that are relevant to the DHFR catalyzed hydride transfer. To this end, we employ G4MP2 and CBS-QB3 ab initio calculations as well as numerous density functional theory methods. Using these results, we develop two specific reaction parameter (SRP) Hamiltonians based on the semiempirical AM1 method. The first generation SRP Hamiltonian does not account for dispersion, while the second generation SRP accounts for dispersion implicitly via the AM1 core-repulsion functions. These SRP semiempirical Hamiltonians are subsequently used in hybrid quantum mechanics/molecular mechanics simulations of the DHFR catalyzed reaction. Finally, kinetic isotope effects are computed using a mass-perturbation-based path-integral approach.

Path-Integral Calculations of Nuclear Quantum Effects in Model Systems, Small Molecules, and Enzymes via Gradient-Based Forward Corrector Algorithms.

A practical approach to treat nuclear quantum mechanical (QM) effects in simulations of condensed phases, such as enzymes, is via Feynman path integral (PI) formulations. Typically, the standard primitive approximation (PA) is employed in enzymatic PI simulations. Nonetheless, these PI simulations are computationally demanding due to the large number of discretizations, or beads, required to obtain converged results. The efficiency of PI simulations may be greatly improved if higher order factorizations of the density matrix operator are employed. Herein, we compare the results of model calculations obtained employing the standard PA, the improved operator of Takahashi and Imada (TI), and several gradient-based forward corrector algorithms due to Chin (CH). The quantum partition function is computed for the harmonic oscillator, Morse, symmetric, and asymmetric double well potentials. These potentials are simple models for nuclear quantum effects, such as zero-point energy and tunneling. It is shown that a unique set of CH parameters may be employed for a variety of systems. Additionally, the nuclear QM effects of a water molecule, treated with density functional theory, are computed. Finally, we derive a practical perturbation expression for efficient computation of isotope effects in chemical systems using the staging algorithm. This new isotope effect approach is tested in conjunction with the PA, TI, and CH methods to compute the equilibrium isotope effect in the Schiff base-oxyanion keto-enol tautomerism in the cofactor pyridoxal-5'-phosphate in the enzyme alanine racemase. The study of the different factorization methods reveals that the higher-order actions converge substantially faster than the PA approach, at a moderate computational cost.

Novel multifunctional acyloxyalkyl ester prodrugs of 5-aminolevulinic acid display improved anticancer activity independent and dependent on photoactivation.

Multifunctional acyloxyalkyl ester prodrugs of 5-aminolevulinic acid in cancer cell lines inhibited the proteasome and induced apoptosis and heme synthesis. The most potent prodrug was butyryloxymethyl 5-amino-4-oxopentanoate (1a). The metabolically released formaldehyde from the prodrugs was the dominant factor affecting cell viability by a ROS-dependent mechanism and was responsible for rapid phosphorylation of H2AX, suppression of the cell survival protein c-myc, and transient elevation in the expression of p21. 1a, which differs from 2a by releasing butyric instead of pivalic acid, was a more potent inducer of heme and acetylated H4 expression and induced apoptosis through activation of caspase 9. 1a and 1b specifically increased the level of the photosensitizer protoporphyrin 9, leading to enhancement of cell death by photodynamic therapy (PDT). The advantage of these multifunctional prodrugs over 5-ALA is their greater potency in the non-PDT mechanism of cancer cell killing and their ability to also augment PDT.