QM/MM Study Into the Mechanism of Oxidative C=C Double Bond Cleavage by Lignostilbene-α,ß-Dioxygenase.

The enzymatic biosynthesis of fragrance molecules from lignin fragments is an important reaction in biotechnology for the sustainable production of fine chemicals. In this work we investigated the biosynthesis of vanillin from lignostilbene by a nonheme iron dioxygenase using QM/MM and tested several suggested proposals via either an epoxide or dioxetane intermediate. Binding of dioxygen to the active site of the protein results in the formation of an iron(II)-superoxo species with lignostilbene cation radical. The dioxygenase mechanism starts with electrophilic attack of the terminal oxygen atom of the superoxo group on the central C=C bond of lignostilbene, and the second-coordination sphere effects in the substrate binding pocket guide the reaction towards dioxetane formation. The computed mechanism is rationalized with thermochemical cycles and valence bond schemes that explain the electron transfer processes during the reaction mechanism. Particularly, the polarity of the protein and the local electric field and dipole moments enable a facile electron transfer and an exergonic dioxetane formation pathway.

Local Charge Distributions, Electric Dipole Moments, and Local Electric Fields Influence Reactivity Patterns and Guide Regioselectivities in α-Ketoglutarate-Dependent Non-heme Iron Dioxygenases.

Non-heme iron dioxygenases catalyze vital processes for human health related to the biosynthesis of essential products and the biodegradation of toxic metabolites. Often the natural product biosyntheses by these non-heme iron dioxygenases is highly regio- and chemoselective, which are commonly assigned to tight substrate-binding and positioning. However, recent high-level computational modeling has shown that substrate-binding and positioning is only part of the story and long-range electrostatic interactions can play a major additional role.In this Account, we review and summarize computational viewpoints on the high regio- and chemoselectivity of α-ketoglutarate-dependent non-heme iron dioxygenases and how external perturbations affect the catalysis. In particular, studies from our groups have shown that often a regioselectivity in enzymes can be accomplished by stabilization of the rate-determining transition state for the reaction through external charges, electric dipole moments, or local electric field effects. Furthermore, bond dissociation energies in molecules are shown to be influenced by an electric field effect, and through targeting a specific bond in an electric field, this can lead to an unusually specific reaction. For instance, in the carbon-induced starvation protein, we studied two substrate-bound conformations and showed that regardless of what C-H bond of the substrate is closest to the iron(IV)-oxo oxidant, the lowest hydrogen atom abstraction barrier is always for the pro-S C2-H abstraction due to an induced dipole moment of the protein that weakens this bond. In another example of the hygromycin biosynthesis enzyme, an oxidative ring-closure reaction in the substrate forms an ortho-δ-ester ring. Calculations on this enzyme show that the selectivity is guided by a protonated lysine residue in the active site that, through its positive charge, triggers a low energy hydrogen atom abstraction barrier. A final set of examples in this Account discuss the viomycin biosynthesis enzyme and the 2-(trimethylammonio)ethylphosphonate dioxygenase (TmpA) enzyme. Both of these enzymes are shown to possess a significant local dipole moment and local electric field effect due to charged residues surrounding the substrate and oxidant binding pockets. The protein dipole moment and local electric field strength changes the C-H bond strengths of the substrate as compared to the gas-phase triggers the regioselectivity of substrate activation. In particular, we show that in the gas phase and in a protein environment C-H bond strengths are different due to local electric dipole moments and electric field strengths. These examples show that enzymes have an intricately designed structure that enables a chemical reaction under ambient conditions through the positioning of positively and negatively charged residues that influence and enhance reaction mechanisms. These computational insights create huge possibilities in bioengineering to apply local electric field and dipole moments in proteins to achieve an unusual selectivity and specificity and trigger a fit-for-purpose biocatalyst for unique biotransformations.

Energy-entropy multiscale cell correlation method to predict toluene-water log P in the SAMPL9 challenge.

The energy-entropy multiscale cell correlation (EE-MCC) method is used to calculate toluene-water log P values of 16 drug molecules in the SAMPL9 physical properties challenge. EE-MCC calculates the free energy, energy and entropy from molecular dynamics (MD) simulations of the water and toluene solutions. Specifically, MCC evaluates entropy by partitioning the system into cells of correlated atoms at multiple length scales and further partitioning the local coordinates into energy wells, yielding vibrational and topographical terms from the energy-well sizes and probabilities. The log P values calculated by EE-MCC using three 200 ns MD simulations have a mean average error of 0.82 and standard error of the mean of 0.97 versus experiment, which is comparable with the best methods entered in SAMPL9. The main contribution to log P is from energy. Less polar drugs have more favourable energies of transfer. The entropy of transfer consists of increased solute vibrational and conformational terms in toluene due to weaker interactions, fewer solute positions in the larger-molecule solvent, reduced water vibrational entropy, negligible change in toluene vibrational entropy, and gains in solvent orientational entropy. The solvent entropy contributions here may be slightly underestimated because software limitations and statistical fluctuations meant that only the first shell could be included while averaged over the whole solution. Nonetheless, such issues will be addressed in future software to offer a general method to calculate entropy directly from MD simulation and to provide molecular understanding or guide system design.

Pyrimidine-morpholine hybrids as potent druggable therapeutics for Alzheimer's disease: Synthesis, biochemical and in silico analyses.

The identification of effective and druggable cholinesterase inhibitors to treat progressive neurodegenerative Alzheimer's disorder remains a continuous drug discovery hunt. In this perspective, the present study investigates the design and discovery of pyrimidine-morpholine hybrids (5a-l) as potent cholinesterase inhibitors. Palladium-catalyzed Suzuki-Miyaura cross-coupling reaction was employed to introduce the structural diversity on the pyrimidine heterocyclic core. A range of commercially available boronic acids was successfully coupled showing a high functional group tolerance. In vitro cholinesterase inhibitory potential using Ellman's method revealed significantly strong potency. Compound 5h bearing a meta-tolyl substituent at 2-position of pyrimidine ring emerged as a lead candidate against AChE with an inhibitory potency of 0.43 ± 0.42 µM, ∼38-fold stronger value than neostigmine (IC50 = 16.3 ± 1.12 µM). Compound 5h also showed the lead inhibition against BuChE with an IC50 value of 2.5 ± 0.04 µM. The kinetics analysis of 5h revealed the non-competitive mode of inhibition against AChE whereas computational modelling results of potent leads depicted diverse contacts with the binding site amino acid residues. Molecular dynamics simulations revealed the stability of biomolecular system, while, ADME analysis demonstrated druglikeness behaviour of potent compounds. Overall, the investigated pyrimidine-morpholine scaffold presented a remarkable potential to be developed as efficacious anti-Alzheimer's drugs.

Electrostatic Perturbations in the Substrate-Binding Pocket of Taurine/α-Ketoglutarate Dioxygenase Determine its Selectivity.

Taurine/α-ketoglutarate dioxygenase is an important enzyme that takes part in the cysteine catabolism process in the human body and selectively hydroxylates taurine at the C1 -position. Recent computational studies showed that in the gas-phase the C2 -H bond of taurine is substantially weaker than the C1 -H bond, yet no evidence exists of 2-hydroxytaurine products. To this end, a detailed computational study on the selectivity patterns in TauD was performed. The calculations show that the second-coordination sphere and the protonation states of residues play a major role in guiding the enzyme to the right selectivity. Specifically, a single proton on an active site histidine residue can change the regioselectivity of the reaction through its electrostatic perturbations in the active site and effectively changes the C1 -H and C2 -H bond strengths of taurine. This is further emphasized by many polar and hydrogen bonding interactions of the protein cage in TauD with the substrate and the oxidant that weaken the pro-R C1 -H bond and triggers a chemoselective reaction process. The large cluster models reproduce the experimental free energy of activation excellently.

What Determines the Selectivity of Arginine Dihydroxylation by the Nonheme Iron Enzyme OrfP?

The nonheme iron enzyme OrfP reacts with l-Arg selectively to form the 3R,4R-dihydroxyarginine product, which in mammals can inhibit the nitric oxide synthase enzymes involved in blood pressure control. To understand the mechanisms of dioxygen activation of l-Arg by OrfP and how it enables two sequential oxidation cycles on the same substrate, we performed a density functional theory study on a large active site cluster model. We show that substrate binding and positioning in the active site guides a highly selective reaction through C3 -H hydrogen atom abstraction. This happens despite the fact that the C3 -H and C4 -H bond strengths of l-Arg are very similar. Electronic differences in the two hydrogen atom abstraction pathways drive the reaction with an initial C3 -H activation to a low-energy 5 σ-pathway, while substrate positioning destabilizes the C4 -H abstraction and sends it over the higher-lying 5 π-pathway. We show that substrate and monohydroxylated products are strongly bound in the substrate binding pocket and hence product release is difficult and consequently its lifetime will be long enough to trigger a second oxygenation cycle.

Electrostatic Perturbations from the Protein Affect C-H Bond Strengths of the Substrate and Enable Negative Catalysis in the TmpA Biosynthesis Enzyme.

The nonheme iron dioxygenase 2-(trimethylammonio)-ethylphosphonate dioxygenase (TmpA) is an enzyme involved in the regio- and chemoselective hydroxylation at the C1 -position of the substrate as part of the biosynthesis of glycine betaine in bacteria and carnitine in humans. To understand how the enzyme avoids breaking the weak C2 -H bond in favor of C1 -hydroxylation, we set up a cluster model of 242 atoms representing the first and second coordination sphere of the metal center and substrate binding pocket, and investigated possible reaction mechanisms of substrate activation by an iron(IV)-oxo species by density functional theory methods. In agreement with experimental product distributions, the calculations predict a favorable C1 -hydroxylation pathway. The calculations show that the selectivity is guided through electrostatic perturbations inside the protein from charged residues, external electric fields and electric dipole moments. In particular, charged residues influence and perturb the homolytic bond strength of the C1 -H and C2 -H bonds of the substrate, and strongly strengthens the C2 -H bond in the substrate-bound orientation.

Glutarate Hydroxylation by the Carbon Starvation-Induced Protein D: A Computational Study into the Stereo- and Regioselectivities of the Reaction.

The carbon starvation-induced protein D (CsiD) is a recently characterized iron(II)/α-ketoglutarate-dependent oxygenase that activates a glutarate molecule as substrate at the C2 position to exclusively produce (S)-2-hydroxyglutarate products. This selective hydroxylation reaction by CsiD is an important component of the lysine biodegradation pathway in Escherichia coli; however, little is known on the details and the origin of the selectivity of the reaction. So far, experimental studies failed to trap and characterize any short-lived catalytic cycle intermediates. As no computational studies have been reported on this enzyme either, we decided to investigate the chemical reaction mechanism of glutarate activation by an iron(IV)-oxo model of the CsiD enzyme. In this work, we present a density functional theory study on a large active site cluster model of CsiD and investigate the glutarate hydroxylation pathways by a high-valent iron(IV)-oxo species leading to (S)-2-hydroxyglutarate, (R)-2-hydroxyglutarate, and 3-hydroxyglutarate. In agreement with experimental observation, the favorable product channel leads to pro-S C2-H hydrogen atom abstraction to form (S)-2-hydroxyglutarate. The reaction is stepwise with a hydrogen atom abstraction by an iron(IV)-oxo species followed by OH rebound from a radical intermediate. The work presented in this paper shows that despite the fact that the C-H bond strengths at the C2 and C3 positions of glutarate are similar in the gas phase, substrate binding and positioning guide the reaction to an enantioselective reaction process by destabilizing the hydrogen atom abstraction pathways for the pro-R C2-H and C3-H positions. Our studies predict the chemical properties of the iron(IV)-oxo species and its rate constants with glutarate and deuterated-glutarate. Moreover, the work shows little protein motions during the catalytic process, while the substrate entrance into the substrate binding pocket appears to be guided by three active site arginine residues that position the substrate for pro-S C2-H hydrogen atom abstraction. Finally, the calculations show that irrespective of the position of the substrate and what C-H bond is closest to the metal center, the lowest energy pathway is for a selective pro-S C2-H hydrogen atom abstraction.

Energy-entropy method using multiscale cell correlation to calculate binding free energies in the SAMPL8 host-guest challenge.

Free energy drives a wide range of molecular processes such as solvation, binding, chemical reactions and conformational change. Given the central importance of binding, a wide range of methods exist to calculate it, whether based on scoring functions, machine-learning, classical or electronic structure methods, alchemy, or explicit evaluation of energy and entropy. Here we present a new energy-entropy (EE) method to calculate the host-guest binding free energy directly from molecular dynamics (MD) simulation. Entropy is evaluated using Multiscale Cell Correlation (MCC) which uses force and torque covariance and contacts at two different length scales. The method is tested on a series of seven host-guest complexes in the SAMPL8 (Statistical Assessment of the Modeling of Proteins and Ligands) "Drugs of Abuse" Blind Challenge. The EE-MCC binding free energies are found to agree with experiment with an average error of 0.9 kcal mol-1. MCC makes clear the origin of the entropy changes, showing that the large loss of positional, orientational, and to a lesser extent conformational entropy of each binding guest is compensated for by a gain in orientational entropy of water released to bulk, combined with smaller decreases in vibrational entropy of the host, guest and contacting water.

How Do Electrostatic Perturbations of the Protein Affect the Bifurcation Pathways of Substrate Hydroxylation versus Desaturation in the Nonheme Iron-Dependent Viomycin Biosynthesis Enzyme?

The viomycin biosynthesis enzyme VioC is a nonheme iron and α-ketoglutarate-dependent dioxygenase involved in the selective hydroxylation of l-arginine at the C3-position for antibiotics biosynthesis. Interestingly, experimental studies showed that using the substrate analogue, namely, l-homo-arginine, a mixture of products was obtained originating from C3-hydroxylation, C4-hydroxylation, and C3-C4-desaturation. To understand how the addition of one CH2 group to a substrate can lead to such a dramatic change in selectivity and activity, we decided to perform a computational study using quantum mechanical (QM) cluster models. We set up a large active-site cluster model of 245 atoms that includes the oxidant with its first- and second-coordination sphere influences as well as the substrate binding pocket. The model was validated against experimental work from the literature on related enzymes and previous computational studies. Thereafter, possible pathways leading to products and byproducts were investigated for a model containing l-Arg and one for l-homo-Arg as substrate. The calculated free energies of activation predict product distributions that match the experimental observation and give a low-energy C3-hydroxylation pathway for l-Arg, while for l-homo-Arg, several barriers are found to be close in energy leading to a mixture of products. We then analyzed the origins of the differences in product distributions using thermochemical, valence bond, and electrostatic models. Our studies show that the C3-H and C4-H bond strengths of l-Arg and l-homo-Arg are similar; however, external perturbations from an induced electric field of the protein affect the relative C-H bond strengths of l-Arg dramatically and make the C3-H bond the weakest and guide the reaction to a selective C3-hydroxylation channel. Therefore, the charge distribution in the protein and the induced electric dipole field of the active site of VioC guides the l-Arg substrate activation to C3-hydroxylation and disfavors the C4-hydroxylation pathway, while this does not occur for l-homo-Arg. Tight substrate positioning and electrostatic perturbations from the second-coordination sphere residues in VioC also result in a slower overall reaction for l-Arg; however, they enable a high substrate selectivity. Our studies highlight the importance of the second-coordination sphere in proteins that position the substrate and oxidant, perturb charge distributions, and enable substrate selectivity.

Catalytic Mechanism of Aromatic Nitration by Cytochrome P450 TxtE: Involvement of a Ferric-Peroxynitrite Intermediate.

The cytochromes P450 are heme-dependent enzymes that catalyze many vital reaction processes in the human body related to biodegradation and biosynthesis. They typically act as mono-oxygenases; however, the recently discovered P450 subfamily TxtE utilizes O2 and NO to nitrate aromatic substrates such as L-tryptophan. A direct and selective aromatic nitration reaction may be useful in biotechnology for the synthesis of drugs or small molecules. Details of the catalytic mechanism are unknown, and it has been suggested that the reaction should proceed through either an iron(III)-superoxo or an iron(II)-nitrosyl intermediate. To resolve this controversy, we used stopped-flow kinetics to provide evidence for a catalytic cycle where dioxygen binds prior to NO to generate an active iron(III)-peroxynitrite species that is able to nitrate l-Trp efficiently. We show that the rate of binding of O2 is faster than that of NO and also leads to l-Trp nitration, while little evidence of product formation is observed from the iron(II)-nitrosyl complex. To support the experimental studies, we performed density functional theory studies on large active site cluster models. The studies suggest a mechanism involving an iron(III)-peroxynitrite that splits homolytically to form an iron(IV)-oxo heme (Compound II) and a free NO2 radical via a small free energy of activation. The latter activates the substrate on the aromatic ring, while compound II picks up the ipso-hydrogen to form the product. The calculations give small reaction barriers for most steps in the catalytic cycle and, therefore, predict fast product formation from the iron(III)-peroxynitrite complex. These findings provide the first detailed insight into the mechanism of nitration by a member of the TxtE subfamily and highlight how the enzyme facilitates this novel reaction chemistry.

Lignin Biodegradation by a Cytochrome P450 Enzyme: A Computational Study into Syringol Activation by GcoA.

A recently characterized cytochrome P450 isozyme GcoA activates lignin components through a selective O-demethylation or alternatively an acetal formation reaction. These are important reactions in biotechnology and, because lignin is readily available; it being the main component in plant cell walls. In this work we present a density functional theory study on a large active site model of GcoA to investigate syringol activation by an iron(IV)-oxo heme cation radical oxidant (Compound I) leading to hemiacetal and acetal products. Several substrate-binding positions were tested and full energy landscapes calculated. The study shows that substrate positioning determines the product distributions. Thus, with the phenol group pointing away from the heme, an O-demethylation is predicted, whereas an initial hydrogen-atom abstraction of the weak phenolic O-H group would trigger a pathway leading to ring-closure to form acetal products. Predictions on how to engineer P450 GcoA to get more selective product distributions are given.

Cross-linking of aromatic phenolate groups by cytochrome P450 enzymes: a model for the biosynthesis of vancomycin by OxyB.

The cytochromes P450 are a versatile class of enzymes involved in many chemical reactions in biosystems and as such they take part in biodegradation as well as biosynthesis pathways in many organisms. These enzymes use molecular oxygen on a heme centre and often react as mono-oxygenases. Lesser known reactions catalyzed by the P450s include desaturation pathways and ring-closure reactions. In this work we study the aromatic cross-linking of glycopeptide units as, for instance, performed by the P450 isozyme OxyB as part of vancomycin biosynthesis. A series of density functional theory studies are reported on a large active site cluster model of 258 atoms containing the heme with its coordinated ligands, a representative substrate and its interacting protein residues. We show that the catalytic cycle intermediates Compound I and Compound II of P450 can rapidly and successively abstract a phenolic hydrogen atom from adjacent peptide groups to give a biradical intermediate with small reaction barriers. The latter can form the ether cross-link between the two aromatic residues, which is the rate-determining step in the reaction mechanism and involves a simultaneous proton transfer from the ipso-position to the ketone. A thermochemical analysis reveals that weak phenolic O-H bonds lead to hydrogen atom abstraction easily by Compound I and Compound II, enabling a selective aromatic cross-linking reaction.

How external perturbations affect the chemoselectivity of substrate activation by cytochrome P450 OleTJE.

Cytochrome P450 enzymes are versatile biocatalysts found in most forms of life. Generally, the cytochrome P450s react with dioxygen and hence are haem-based mono-oxygenases; however, in specific isozymes, H2O2 rather than O2 is used and these P450s act as peroxygenases. The P450 OleTJE is a peroxygenase that binds long to medium chain fatty acids and converts them to a range of products originating from Cα-hydroxylation, Cß-hydroxylation, Cα-Cß desaturation and decarboxylation of the substrate. There is still controversy regarding the details of the reaction mechanism of P450 OleTJE; how the products are formed and whether the product distributions can be influenced by external perturbations. To gain further insights into the structure and reactivity of P450 OleTJE, we set up a range of large active site model complexes as well as full enzymatic structures and did a combination of density functional theory studies and quantum mechanics/molecular mechanics calculations. In particular, the work focused on the mechanisms leading to these products under various reaction conditions. Thus, for a small cluster model, we find a highly selective Cα-hydroxylation pathway that is preferred over Cß-H hydrogen atom abstraction by at least 10 kcal mol-1. Introduction of polar residues to the model, such as an active site protonated histidine residue or through external electric field effects, lowers the Cß-H hydrogen atom abstraction barriers are lowered, while a full QM/MM model brings the Cα-H and Cß-H hydrogen atom abstraction barriers within 1 kcal mol-1. Our studies; therefore, implicate that environmental effects in the second-coordination sphere can direct and guide selectivities in enzymatic reaction mechanisms.

Entropy of Simulated Liquids Using Multiscale Cell Correlation.

Accurately calculating the entropy of liquids is an important goal, given that many processes take place in the liquid phase. Of almost equal importance is understanding the values obtained. However, there are few methods that can calculate the entropy of such systems, and fewer still to make sense of the values obtained. We present our multiscale cell correlation (MCC) method to calculate the entropy of liquids from molecular dynamics simulations. The method uses forces and torques at the molecule and united-atom levels and probability distributions of molecular coordinations and conformations. The main differences with previous work are the consistent treatment of the mean-field cell approximation to the approriate degrees of freedom, the separation of the force and torque covariance matrices, and the inclusion of conformation correlation for molecules with multiple dihedrals. MCC is applied to a broader set of 56 important industrial liquids modeled using the Generalized AMBER Force Field (GAFF) and Optimized Potentials for Liquid Simulations (OPLS) force fields with 1.14*CM1A charges. Unsigned errors versus experimental entropies are 8.7 J K - 1 mol - 1 for GAFF and 9.8 J K - 1 mol - 1 for OPLS. This is significantly better than the 2-Phase Thermodynamics method for the subset of molecules in common, which is the only other method that has been applied to such systems. MCC makes clear why the entropy has the value it does by providing a decomposition in terms of translational and rotational vibrational entropy and topographical entropy at the molecular and united-atom levels.

Catalytic divergencies in the mechanism of L-arginine hydroxylating nonheme iron enzymes.

Many enzymes in nature utilize a free arginine (L-Arg) amino acid to initiate the biosynthesis of natural products. Examples include nitric oxide synthases, which generate NO from L-Arg for blood pressure control, and various arginine hydroxylases involved in antibiotic biosynthesis. Among the groups of arginine hydroxylases, several enzymes utilize a nonheme iron(II) active site and let L-Arg react with dioxygen and α-ketoglutarate to perform either C3-hydroxylation, C4-hydroxylation, C5-hydroxylation, or C4-C5-desaturation. How these seemingly similar enzymes can react with high specificity and selectivity to form different products remains unknown. Over the past few years, our groups have investigated the mechanisms of L-Arg-activating nonheme iron dioxygenases, including the viomycin biosynthesis enzyme VioC, the naphthyridinomycin biosynthesis enzyme NapI, and the streptothricin biosynthesis enzyme OrfP, using computational approaches and applied molecular dynamics, quantum mechanics on cluster models, and quantum mechanics/molecular mechanics (QM/MM) approaches. These studies not only highlight the differences in substrate and oxidant binding and positioning but also emphasize on electronic and electrostatic differences in the substrate-binding pockets of the enzymes. In particular, due to charge differences in the active site structures, there are changes in the local electric field and electric dipole moment orientations that either strengthen or weaken specific substrate C-H bonds. The local field effects, therefore, influence and guide reaction selectivity and specificity and give the enzymes their unique reactivity patterns. Computational work using either QM/MM or density functional theory (DFT) on cluster models can provide valuable insights into catalytic reaction mechanisms and produce accurate and reliable data that can be used to engineer proteins and synthetic catalysts to perform novel reaction pathways.

Design and discovery of anthranilamide derivatives as a potential treatment for neurodegenerative disorders via targeting cholinesterases and monoamine oxidases.

Neurodegenerative diseases with progressive cellular loss of the central nervous system and elusive disease etiology provide a continuous impetus to explore drug discovery programmes aiming at identifying robust and effective inhibitors of cholinesterase and monoamine oxidase enzymes. We herein present a concise library of anthranilamide derivatives involving a palladium-catalyzed Suzuki-Miyaura cross-coupling reaction to install the diverse structural diversity required for the desired biological action. Using Ellman's method, cholinesterase inhibitory activity was performed against AChE and BuChE enzymes. In vitro assay results demonstrated that anthranilamides are potent inhibitors with remarkable potency. Compound 6k emerged as the lead candidate and dual inhibitor of both enzymes with IC50 values of 0.12 ± 0.01 and 0.49 ± 0.02 µM against AChE and BuChE, respectively. Several other compounds were found as highly potent and selective inhibitors. Anthranilamide derivatives were also tested against monoamine oxidase (A and B) enzymes using fluorometric method. In vitro data revealed compound 6h as the most potent inhibitor against MAO-A, showing an IC50 value of 0.44 ± 0.02 µM, whereas, compound 6k emerged as the top inhibitor of MAO-B with an IC50 value of 0.06 ± 0.01 µM. All the lead inhibitors were analyzed for the identification of their mechanism of action using Michaelis-Menten kinetics experiments. Compound 6k and 6h depicted a competitive mode of action against AChE and MAO-A, whereas, a non-competitive and mixed-type of inhibition was observed against BuChE and MAO-B by compounds 6k. Molecular docking analysis revealed remarkable binding affinities of the potent inhibitors with specific residues inside the active site of receptors. Furthermore, molecular dynamics simulations were performed to explore the ability of potent compounds to form energetically stable complexes with the target protein. Finally, in silico ADME calculations also demonstrated that the potent compounds exhibit promising pharmacokinetic profile, satisfying the essential criteria for drug-likeness. Altogether, the findings reported in the current work clearly suggest that the identified anthranilamide derivatives have the potential to serve as effective drug candidates for future investigations.

Impact of counteranions on N-heterocyclic carbene gold(i)-catalyzed cyclization of propargylic amide.

N-Heterocyclic carbene (NHC) Au(i)-catalyzed organic synthesis has recently been receiving increasing attention, especially with the activation of alkynes. In contrast, counteranions, being widely problematic in Au(i)-catalyzed transformations, are commonly considered as innocent partners and are not respectably included in a computational model. Herein, we report density functional theory (DFT) investigations of the Au(i)-catalyzed cyclization of propargylic amides to exploit the mechanistic effect of several counteranions to shed some light for further future developments. Among the counteranions used in this study, NTf2 -, ClO4 -, TsO-, TFA-, TfO-, MsO-, and SbF6 -, both the cyclization and protodeauration step favor the 5-exo-dig product over the 6-endo-dig product when the alkyne moiety is terminated with hydrogen. These anions reveal a crucial influence on the energy profile through lowering the barriers of the reaction. Mechanistically, the results obtained from all counteranions show that the protodeauration is slower than the cyclization. By using an energetic span model, the results clearly indicate that the rate-determining state is the protodeauration step for all counteranions, and thus protodeauration is the turnover-limiting step. The turnover frequency (TOF) results for the formation of the 5-exo-dig product show cyclization reactivity in the order of MsO- > TFA- > ClO4 - > NTf2 - > TfO- > TsO- ≫ SbF6 -, whereas an order of TFA- > MsO- > NTf2 - > TfO- ≈ ClO4 - > SbF6 - ⋙ TsO- is calculated for the protodeauration, suggesting that SbF6 - and TsO- are disfavored due to their slow protodeauration. In this regard, and for the 6-endo-dig pathway, our conclusions demonstrate an order of TfO- > TFA- > MsO- > NTf2 - > ClO4 - > TsO- ⋙ SbF6 - for the cyclization and TFA- > TsO- > MsO- > TfO- > NTf2 - > ClO4 - ⋙ SbF6 - for the protodeauration, advocating that the anions SbF6 -, NTf2 - and ClO4 - are unlikely partners for the 6-endo-dig pathway because of their slow protodeauration. Finally, the findings here advise that any engineering of the counteranion to increase the efficiency of catalytic system would be more effective on the protodeauration step rather than the cyclization step.

Discovery of druggable potent inhibitors of serine proteases and farnesoid X receptor by ligand-based virtual screening to obstruct SARS-CoV-2.

The coronavirus, a subfamily of the coronavirinae family, is an RNA virus with over 40 variations that can infect humans, non-human mammals and birds. There are seven types of human coronaviruses, including SARS-CoV-2, is responsible for the recent COVID-19 pandemic. The current study is focused on the identification of drug molecules for the treatment of COVID-19 by targeting human proteases like transmembrane serine protease 2 (TMPRSS2), furin, cathepsin B, and a nuclear receptor named farnesoid X receptor (FXR). TMPRSS2 and furin help in cleaving the spike protein of the SARS-CoV-2 virus, while cathepsin B plays a critical role in the entry and pathogenesis. FXR, on the other hand, regulates the expression of ACE2, and its inhibition can reduce SARS-CoV-2 infection. By inhibiting these four protein targets with non-toxic inhibitors, the entry of the infectious agent into host cells and its pathogenesis can be obstructed. We have used the BioSolveIT suite for pharmacophore-based computational drug designing. A total of 1611 ligands from the ligand library were docked with the target proteins to obtain potent inhibitors on the basis of pharmacophore. Following the ADMET analysis and protein ligand interactions, potent and druggable inhibitors of the target proteins were obtained. Additionally, toxic substructures and the less toxic route of administration of the most potent inhibitors in rodents were also determined computationally. Compounds namely N-(diaminomethylene)-2-((3-((1R,3R)-3-(2-(methoxy(methyl)amino)-2-oxoethyl)cyclopentyl)propyl)amino)-2-oxoethan-1-aminium (26), (1R,3R)-3-(((2-ammonioethyl)ammonio)methyl)-1-((4-propyl-1H-imidazol-2-yl)methyl)piperidin-1-ium (29) and (1R,3R)-3-(((2-ammonioethyl)ammonio)methyl)-1-((1-propyl-1H-pyrazol-4-yl)methyl)piperidin-1-ium (30) were found as the potent inhibitors of TMPRSS2, whereas, 1-(1-(1-(1H-tetrazol-1-yl)cyclopropane-1­carbonyl)piperidin-4-yl)azepan-2-one (6), (2R)-4-methyl-1-oxo-1-((7R,11S)-4-oxo-6,7,8,9,10,11-hexahydro-4H-7,11-methanopyrido[1,2-a]azocin-9-yl)pentan-2-aminium (12), 4-((1-(3-(3,5-dimethylisoxazol-4-yl)propanoyl)piperidin-4-yl)methyl)morpholin-4-ium (13), 1-(4,6-dimethylpyrimidin-2-yl)-N-(3-oxocyclohex-1-en-1-yl)piperidine-4-carboxamide (14), 1-(4-(1,5-dimethyl-1H-1,2,4-triazol-3-yl)piperidin-1-yl)-3-(3,5-dimethylisoxazol-4-yl)propan-1-one (25) and N,N-dimethyl-4-oxo-4-((1S,5R)-8-oxo-5,6-dihydro-1H-1,5-methanopyrido[1,2-a][1,5]diazocin-3(2H,4H,8H)-yl)butanamide (31) inhibited the FXR preferentially. In case of cathepsin B, N-((5-benzoylthiophen-2-yl)methyl)-2-hydrazineyl-2-oxoacetamide (2) and N-([2,2'-bifuran]-5-ylmethyl)-2-hydrazineyl-2-oxoacetamide (7) were identified as the most druggable inhibitors whereas 1-amino-2,7-diethyl-3,8-dioxo-6-(p-tolyl)-2,3,7,8-tetrahydro-2,7-naphthyridine-4­carbonitrile (5) and (R)-6-amino-2-(2,3-dihydroxypropyl)-1H-benzo[de]isoquinoline-1,3(2H)-dione (20) were active against furin.

Identification of potential inhibitors targeting yellow fever virus helicase through ligand and structure-based computational studies.

Yellow fever is a flavivirus having plus-sensed RNA which encodes a single polyprotein. Host proteases cut this polyprotein into seven nonstructural proteins including a vital NS3 protein. The present study aims to identify the most effective inhibitor against the helicase (NS3) using different advanced ligand and structure-based computational studies. A set of 300 ligands was selected against helicase by chemical structural similarity model, which are similar to S-adenosyl-l-cysteine using infiniSee. This tool screens billions of compounds through a similarity search from in-built chemical spaces (CHEMriya, Galaxi, KnowledgeSpace and REALSpace). The pharmacophore was designed from ligands in the library that showed same features. According to the sequence of ligands, six compounds (29, 87, 99, 116, 148, and 208) were taken for pharmacophore designing against helicase protein. Subsequently, compounds from the library which showed the best pharmacophore shared-features were docked using FlexX functionality of SeeSAR and their optibrium properties were analyzed. Afterward, their ADME was improved by replacing the unfavorable fragments, which resulted in the generation of new compounds. The selected best compounds (301, 302, 303 and 304) were docked using SeeSAR and their pharmacokinetics and toxicological properties were evaluated using SwissADME. The optimal inhibitor for yellow fever helicase was 2-amino-N-(4-(dimethylamino)thiazol-2-yl)-4-methyloxazole-5-carboxamide (302), which exhibits promising potential for drug development.Communicated by Ramaswamy H. Sarma.