Molecular Dockings and Molecular Dynamics Simulations Reveal the Potency of Different Inhibitors against Xanthine Oxidase

Investigating the inhibition of xanthine oxidase by five catechins: Kinetic studies, spectroscopy, molecular docking, and dynamics simulations

Catechins compounds from tea have demonstrated significant inhibitory effects on xanthine oxidase (XOD). However, the precise inhibitory mechanisms of the main catechins on XOD remain to be fully elucidated. This study explored the inhibition mechanisms and binding characteristics of five catechins (GC, EGC, EC, EGCG, and ECG) on XOD through a combination of inhibition kinetics, multi-spectroscopy analysis, molecular docking, and dynamics simulations. Among the catechins, EGCG and ECG exhibited the most potent inhibitory activities against XOD. All five catechins were found to exhibit mixed inhibition, affecting the hydrophobic groups and secondary structure of XOD predominantly through hydrophobic interactions and hydrogen bonding. Molecular dynamics simulations revealed that a 3,4,5-trihydroxybenzoic acid moiety at C3 position significantly enhances the binding affinity of EGCG and ECG to XOD. Additionally, the decrease of β-sheet and random coil induced by EGCG and ECG was found to be crucial for enhancing inhibitory activity of XOD. In vitro cell experiments showed that EGCG and ECG significantly reduced high uric acid levels of BRL-3A cell. This study elucidates the inhibitory mechanisms of catechins on XOD, paving the way for their application as XOD inhibitors to combat hyperuricemia.

Structure-Activity Relationships and Changes in the Inhibition of Xanthine Oxidase by Polyphenols: A Review

Hyperuricemia (HUA), or elevated uric acid in the blood, has become more prevalent in recent years. Polyphenols, which are known to have good inhibitory activity on xanthine oxidoreductase (XOR), are effective in uric acid reduction. In this review, we address the structure-activity relationship of flavonoids that inhibit XOR activity from two perspectives: the key residues of XOR and the structural properties of flavonoids. Flavonoids' inhibitory effect is enhanced by their hydroxyl, methoxy, and planar structures, whereas glycosylation dramatically reduces their activity. The flavonoid structure-activity relationship informed subsequent discussions of the changes that occur in polyphenols' XOR inhibitory activity during their extraction, processing, gastrointestinal digestion, absorption, and interactions. Furthermore, gastrointestinal digestion and heat treatment during processing can boost the inhibition of XOR. Polyphenols with comparable structures may have a synergistic effect, and their synergy with allopurinol thus provides a promising future research direction.

Understanding the impact of binding free energy and kinetics calculations in modern drug discovery

INTRODUCTION

For rational drug design, it is crucial to understand the receptor-drug binding processes and mechanisms. A new era for the use of computer simulations in predicting drug-receptor interactions at an atomic level has begun with remarkable advances in supercomputing and methodological breakthroughs.

AREAS COVERED

End-point free energy calculation methods such as Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) or Molecular-Mechanics/Generalized Born Surface Area (MM/GBSA), free energy perturbation (FEP), and thermodynamic integration (TI) are commonly used for binding free energy calculations in drug discovery. In addition, kinetic dissociation and association rate constants (k off and k on ) play critical roles in the function of drugs. Nowadays, Molecular Dynamics (MD) and enhanced sampling simulations are increasingly being used in drug discovery. Here, the authors provide a review of the computational techniques used in drug binding free energy and kinetics calculations.

EXPERT OPINION

The applications of computational methods in drug discovery and design are expanding, thanks to improved predictions of the binding free energy and kinetic rates of drug molecules. Recent microsecond-timescale enhanced sampling simulations have made it possible to accurately capture repetitive ligand binding and dissociation, facilitating more efficient and accurate calculations of ligand binding free energy and kinetics.

β-keto amyrin isolated from Cryptostegia grandiflora R. br. inhibits inflammation caused by Daboia russellii viper venom: Direct binding of β-keto amyrin to phospholipase A2

The search for mechanism-based anti-inflammatory therapies is of fundamental importance to avoid undesired off-target effects. Phospholipase A2 (PLA2) activity is a potential molecular target for anti-inflammatory drugs because it fuels arachidonic acid needed to synthesize inflammation mediators, such as prostaglandins. Herein, we aim to investigate the molecular mechanism by which β-keto amyrin isolated from a methanolic extract of Cryptostegia grandiflora R. Br. Leaves can inhibit inflammation caused by Daboia russellii viper (DR) venom that mainly contains PLA2. We found that β-keto amyrin neutralizes DR venom-induced paw-edema in a mouse model. Molecular docking of PLA2 with β-keto amyrin complex resulted in a higher binding energy score of -8.86 kcal/mol and an inhibition constant of 611.7 nM. Diclofenac had a binding energy of -7.04 kcal/mol and an IC50 value of 620 nM, which predicts a poorer binding interaction than β-keto amyrin. The higher conformational stability of β-keto amyrin interaction compared to diclofenac is confirmed by molecular dynamics simulation. β-keto amyrin isolated from C. grandiflora inhibits the PLA2 activity contained in Daboia russellii viper venom. The anti-inflammatory property of β-keto amyrin is due to its direct binding into the active site of PLA2, thus inhibiting its enzyme activity.

Identification of inhibitors from a functional food-based plant Perillae Folium against hyperuricemia via metabolomics profiling, network pharmacology and all-atom molecular dynamics simulations

Introduction

Hyperuricemia (HUA) is a metabolic disorder caused by purine metabolism dysfunction in which the increasing purine levels can be partially attributed to seafood consumption. Perillae Folium (PF), a widely used plant in functional food, has been historically used to mitigate seafood-induced diseases. However, its efficacy against HUA and the underlying mechanism remain unclear.

Methods

A network pharmacology analysis was performed to identify candidate targets and potential mechanisms involved in PF treating HUA. The candidate targets were determined based on TCMSP, SwissTargetPrediction, Open Targets Platform, GeneCards, Comparative Toxicogenomics Database, and DrugBank. The potential mechanisms were predicted via Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) analyses. Molecular docking in AutoDock Vina and PyRx were performed to predict the binding affinity and pose between herbal compounds and HUA-related targets. A chemical structure analysis of PF compounds was performed using OSIRIS DataWarrior and ClassyFire. We then conducted virtual pharmacokinetic and toxicity screening to filter potential inhibitors. We further performed verifications of these inhibitors' roles in HUA through molecular dynamics (MD) simulations, text-mining, and untargeted metabolomics analysis.

Results

We obtained 8200 predicted binding results between 328 herbal compounds and 25 potential targets, and xanthine dehydrogenase (XDH) exhibited the highest average binding affinity. We screened out five promising ligands (scutellarein, benzyl alpha-D-mannopyranoside, elemol, diisobutyl phthalate, and (3R)-hydroxy-beta-ionone) and performed MD simulations up to 50 ns for XDH complexed to them. The scutellarein-XDH complex exhibited the most satisfactory stability. Furthermore, the text-mining study provided laboratory evidence of scutellarein's function. The metabolomics approach identified 543 compounds and confirmed the presence of scutellarein. Extending MD simulations to 200 ns further indicated the sustained impact of scutellarein on XDH structure.

Conclusion

Our study provides a computational and biomedical basis for PF treating HUA and fully elucidates scutellarein's great potential as an XDH inhibitor at the molecular level, holding promise for future drug design and development.

Identification of natural xanthine oxidase inhibitors: Virtual screening, anti-xanthine oxidase activity, and interaction mechanism

Xanthine oxidase (XO) is a crucial target for hyperuricemia treatment(s). Naturally occurred XO inhibitors with minimal toxicity and high efficacy have attracted researchers' attention. With the goal of quickly identifying natural XO inhibitors, an integrated computational screening strategy was constructed by molecular docking and calculating the free energy of binding. Twenty-seven hits were achieved from a database containing 19,377 natural molecules. This includes fourteen known XO inhibitors and four firstly-reported inhibitors (isolicoflavonol, 5,7-dihydroxycoumarin, parvifolol D and clauszoline M, IC50 < 40 μM). Iolicoflavonol (hit 8, IC50 = 8.45 ± 0.68 μM) and 5,7-dihydroxycoumarin (hit 25, IC50 = 10.91 ± 0.71 μM) displayed the great potency as mixed-type inhibitors. Docking study and molecular dynamics simulation revealed that both hits could interact with XO's primarily active site residues ARG880, MOS1328, and ASN768 of XO. Fluorescence spectroscopy studies showed that hit 8 bound to the active cavity region of XO, causing changes in XO's conformation and hydrophobicity. Hits 8 and 25 exhibit favorable Absorption, Distribution, Metabolism, and Excretion (ADME) properties. Additionally, no cytotoxicity against human liver cells was observed at their median inhibition concentrations against XO. Therefore, the present study offers isolicoflavonol and 5,7-dihydroxycoumarin with the potential to be disease-modifying agents for hyperuricemia.

Molecular level investigation of interactions between pharmaceuticals and β-cyclodextrin (β-CD) functionalized adsorption sites for removal of pharmaceutical contaminants from water

This study describes a novel application of the use of molecular modeling tools for investigating the adsorption of organic micropollutants (OMPs) from water by nanocomposites. The partitioning of pharmaceuticals onto β-Cyclodextrin (β-CD) functionalized adsorbents was investigated at the molecular level to explore the atomistic interactions of pharmaceutical contaminants in water systems with β-CD and to provide insight into possible approaches for removal of pharmaceuticals from water. Molecular electrostatic surface potential mapping of β-CD derivatives was employed to examine the impact of substitution degree of β-CD and type of grafting agent on host-guest complexation. The stability of the complexes of selected pharmaceuticals and β-CD derivatives were assessed via molecular dynamics simulations to evaluate competitive adsorption between organic micropollutants (OMPs) and between OMPs and fulvic acid, a representative natural organic material (NOM) component found in water systems. Molecular electrostatic surface potential maps showed that grafting agents with aromatic and amine functional groups were found to provide attractive interactions for negatively charged OMPs. In addition, optimization of substitution degree of β-CD is necessary to enhance adsorption of target OMPs. Furthermore, it was found that aromatic ring bearing grafting agents can provide additional electrostatic attractions by π-π interactions with the aromatic ring of the OMPs. The impact of common water quality characteristics on adsorption was assessed and it was revealed that the effect of pH and calcium on adsorption depends on the ionizable functional groups present on the grafting agent. Molecular dynamics simulations showed that adsorption of target OMPs does not solely depend on hydrophobicity but is affected by electrostatic interactions. The simulations revealed that fulvic acid which is commonly present in environmental waters can be a competitor with ibuprofen for the β-CD cavity. Ultimately, this study showed that molecular level simulation can be effectively employed to investigate adsorption of OMPs by β-CD functionalized adsorbents and could be employed to enhance their design and subsequent environmental applications.

Comparative Atomistic Insights on Apo and ATP-I1171N/S/T in Nonsmall-Cell Lung Cancer

Anaplastic lymphoma kinase (ALK) rearrangements occur in about 5% of nonsmall cell lung cancer (NSCLC) patients. Despite being first recognized as EML4-ALK, fusions with several additional genes have been identified, all of which cause constitutive activation of the ALK kinase and subsequently lead to tumor development. ALK inhibitors first-line crizotinib, second-line ceritinib, and alectinib are effective against NSCLC patients with these rearrangements. Patients progressing on crizotinib had various mutations in the ALK kinase domain. ALK fusion proteins are activated by oligomerization through the fusion partner, which leads to the autophosphorylation of the kinase's domain and consequent downstream activation. The proposed computational study focuses on understanding the activation mechanism of ALK and ATP binding of wild-type (WT) and I1171N/S/T mutations. We analyzed the conformational change of ALK I1171N/S/T mutations and ATP binding using molecular docking and molecular dynamics simulation approaches. According to principal component analysis and free energy landscape, it is clear that I1171N/S/T mutations in Apo and ATP showed different energy minima/unstable structures compared to WT-Apo. The results revealed that I1171N/S/T mutations and ATP binding significantly supported a change toward an active-state conformation, whereas WT-Apo remained inactive. We demonstrated that I1171N/S/T mutations are persistent in an active state and independent of ATP. The I1171S/T mutations showed greater intermolecular H-bonds with ATP than WT-ATP. The molecular mechanics Poisson-Boltzmann surface area analysis revealed that the I1171N/S/T mutation binding energy was similar to that of WT-ATP. This study shows that I1171N/S/T can form stable bonds with ATP and may contribute to a constitutively active kinase. Based on the Y1278-C1097 H-bond and E1167-K1150 salt bridge interaction, I1171N strongly promotes the constitutively active kinase independent of ATP. This structural mechanism study will aid in understanding the oncogenic activity of ALK and the basis for improving the ALK inhibitors.

Virtual screening-molecular docking-activity evaluation of Ailanthus altissima (Mill.) swingle bark in the treatment of ulcerative colitis

BACKGROUND

The dried bark of Ailanthus altissima (Mill.) Swingle is widely used in traditional Chinese medicine for the treatment of ulcerative colitis. The objective of this study was to explore the therapeutic basis of the dried bark of Ailanthus altissima (Mill.) Swingle for the treatment of ulcerative colitis based on Virtual Screening-Molecular Docking-Activity Evaluation technology.

METHODS

By searching the Traditional Chinese Medicine Systems Pharmacology TCMSP Database and Analysis Platform, 89 compounds were obtained from the chemical components of the dried bark of Ailanthus altissima (Mill.) Swingle. Then, after preliminarily screening the compounds based on Lipinski's rule of five and other relevant conditions, the AutoDock Vina molecular docking software was used to evaluate the affinity of the compounds to ulcerative colitis-related target proteins and their binding modes through use of the scoring function to identify the best candidate compounds. Further verification of the compound's properties was achieved through in vitro experiments.

RESULTS

Twenty-two compounds obtained from the secondary screening were molecularly docked with ulcerative colitis-related target proteins (IL-1R, TLR, EGFR, TGFR, and Wnt) using AutoDock Vina. The free energies of the highest scoring compounds binding to the active cavity of human IL-1R, TLR, EGFR, TGFR, and Wnt proteins were - 8.7, - 8.0, - 9.2, - 7.7, and - 8.5 kcal/mol, respectively. The potential compounds, dehydrocrebanine, ailanthone, and kaempferol, were obtained through scoring function and docking mode analysis. Furthermore, the potential compound ailanthone (1, 3, and 10 µM) was found to have no significant effect on cell proliferation, though at 10 µM it reduced the level of pro-inflammatory factors caused by lipopolysaccharide.

CONCLUSION

Among the active components of the dried bark of Ailanthus altissima (Mill.) Swingle, ailanthone plays a major role in its anti-inflammatory properties. The present study shows that ailanthone has advantages in cell proliferation and in inhibiting of inflammation, but further animal research is needed to confirm its pharmaceutical potential.

Mechanism Exploration of Amyloid-β-42 Disaggregation by Single-Chain Variable Fragments of Alzheimer's Disease Therapeutic Antibodies

Alzheimer's disease (AD) is a specific neurodegenerative disease. This study adopts single-chain variable fragments (scFvs) as a potential immunotherapeutic precursor for AD. According to the remarkable effects of monoclonal antibodies, such as the depolymerization or promotion of Aβ42 efflux by Crenezumab, Solanezumab, and 12B4, it is attractive to prepare corresponding scFvs targeting amyloid-β-42 protein (Aβ42) and investigate their biological activities. Crenezumab-like scFv (scFv-C), Solanezumab-like scFv (scFv-S), and 12B4-like scFv (scFv-12B4) were designed and constructed. The thermal stabilities and binding ability to Aβ42 of scFv-C, scFv-S, and scFv-12B4 were evaluated using unfolding profile and enzyme-linked immunosorbent assay. As the results indicated that scFv-C could recognize Aβ42 monomer/oligomer and promote the disaggregation of Aβ42 fiber as determined by the Thioflavin-T assay, the potential mechanism of its interaction with Aβ42 was investigated using molecular dynamics analysis. Interactions involving hydrogen bonds and salt bonds were predicted between scFv-C and Aβ42 pentamer, suggesting the possibility of inhibiting further aggregation of Aβ42. The successfully prepared scFvs, especially scFv-C, with favorable biological activity targeting Aβ42, might be developed for a potentially efficacious clinical application for AD.

Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches

Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro). Strong binding ligands can thus be suggested as potential inhibitors for blocking the biological activity of the protease. In this context, this paper aims to provide a short review of computational approaches that have recently been applied in the search for inhibitor candidates of Mpro. In particular, molecular docking and molecular dynamics (MD) simulations are usually combined to predict the binding affinity of thousands of compounds. Quantitative structure-activity relationship (QSAR) is the least computationally demanding and therefore can be used for large chemical collections of ligands. However, its accuracy may not be high. Moreover, the quantum mechanics/molecular mechanics (QM/MM) method is most commonly used for covalently binding inhibitors, which also play an important role in inhibiting the activity of SARS-CoV-2. Furthermore, machine learning (ML) models can significantly increase the searching space of ligands with high accuracy for binding affinity prediction. Physical insights into the binding process can then be confirmed via physics-based calculations. Integration of ML models into computational chemistry provides many more benefits and can lead to new therapies sooner.

Characterization of xanthine oxidase inhibitory activities of phenols from pickled radish with molecular simulation

•

The 2,6-Dihydroxyacetophenone (DHAP), 4-Hydroxyphenethyl alcohol (4-HPEA), and 4-Hydroxybenzaldehyde (HBA) in pickled radish showed a good affinity for xanthine oxidase (XOD) in the molecular docking results.

•

DHAP, 4-HPEA and HBA inhibit in vitro XOD enzymatic activity by affecting secondary structure and hydrophobic groups, IC₅₀ were: 1.24 ± 0.02 mM, 24.52 ± 0.8 mM, and 2.67 ± 0.9 µM, respectively.

•

DHAP, 4-HPEA and HBA reduce xanthine-induced high uric acid levels in BRL 3A cells by inhibiting XOD enzyme activity (p < 0.05).

Pickled radish is a general source of natural bioactive compounds that include phenols. Here, we used molecular docking, fluorescence quenching, circular dichroism spectroscopy and molecular dynamics simulations to identify potential inhibitors against xanthine oxidase from a library of pickled radish compounds. The most effective compounds were selected for validation through in vitro experiments including enzyme activity inhibition tests, and cell-based assays. Molecular docking results revealed that 2,6-Dihydroxyacetophenone, 4-Hydroxyphenethyl alcohol, and 4-Hydroxybenzaldehyde exhibited significant effects on xanthine oxidase inhibition. Three phenols have varying degrees of inhibition on xanthine oxidase, which is driven by hydrophobic interactions and hydrogen bonds and affects the secondary structure and hydrophobic homeostasis of xanthine oxidase. The stability of xanthine oxidase inhibition by three phenols was analyzed by molecular dynamics simulation. Finally, cellular experiments confirmed that three phenols reduced uric acid levels by inhibiting the xanthine oxidase enzyme activity of BRL 3A cells.

Exploration of the Interactions between Maltase–Glucoamylase and Its Potential Peptide Inhibitors by Molecular Dynamics Simulation

Diabetes mellitus, a chronic metabolic disorder, represents a serious threat to human health. The gut enzyme maltase–glucoamylase (MGAM) has attracted considerable attention as a potential therapeutic target for the treatment of type 2 diabetes. Thus, developing novel inhibitors of MGAM holds the promise of improving clinical management. The dipeptides, Thr-Trp (TW) and Trp-Ala (WA), are known inhibitors of MGAM; however, studies on how they interact with MGAM are lacking. The work presented here explored these interactions by utilizing molecular docking and molecular dynamics simulations. Results indicate that the active center of the MGAM could easily accommodate the flexible peptides. Interactions involving hydrogen bonds, cation-π, and hydrophobic interactions are predicted between TW/WA and residues including Tyr1251, Trp1355, Asp1420, Met1421, Glu1423, and Arg1510 within MGAM. The electrostatic energy was recognized as playing a dominant role in both TW-MGAM and WA-MGAM systems. The binding locations of TW/WA are close to the possible acid-base catalytic residue Asp1526 and might be the reason for MGAM inhibition. These findings provide a theoretical structural model for the development of future inhibitors.

A multiscale screening strategy for the identification of novel xanthine oxidase inhibitors based on the pharmacological features of febuxostat analogues

Two compounds as potential XOI hits were identified by a novel screening strategy based on the pharmacophores of well-known scaffolds.

Chemical Compounds, Antioxidant Activities, and Inhibitory Activities Against Xanthine Oxidase of the Essential Oils From the Three Varieties of Sunflower (Helianthus annuus L.) Receptacles

Background/Aim: Essential oils of sunflower receptacles (SEOs) have antibacterial and antioxidant potential. However, the differences of biological activities from the different varieties of sunflowers have not been studied till now. The purpose of this study was to compare the differences of chemical compounds, antioxidant activities, and inhibitory activities against xanthine oxidase (XO) of SEOs from the three varieties of sunflowers including LD5009, SH363, and S606.

Methods: SEOs were extracted by using the optimal extraction conditions selected by response surface methodology (RSM). Chemical compounds of SEOs were identified from the three varieties of sunflowers by gas chromatography-mass spectrometry (GC-MS). Antioxidant activities of SEOs were detected by 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and iron ion reduction ability. Inhibitory activities of SEOs against XO were measured by using UV spectrophotometer. XO inhibitors were selected from the main chemical compounds of SEOs by the high-throughput selections and molecular simulation docking.

Results: The extraction yields of SEOs from LD5009, SH363, and S606 were 0.176, 0.319, and 0.580%, respectively. A total of 101 chemical compounds of SEOs were identified from the three varieties of sunflowers. In addition, the results of inhibitory activities against XO showed that SEOs can reduce uric acid significantly. Eupatoriochromene may be the most important chemical compounds of SEOs for reducing uric acid. The results of antioxidant activities and inhibitory activities against XO showed that SEOs of LD5009 had the strongest antioxidant and XO inhibitory activities. The Pearson correlation coefficient (r > 0.95) showed that γ-terpinene, (E)-citral, and L-Bornyl acetate were highly correlated with the antioxidant activities and XO inhibitory ability.

Conclusion: SEOs had antioxidant activities and XO inhibitory ability. It would provide more scientific information for utilization and selection of varieties of sunflowers, which would increase the food quality of sunflowers and incomes of farmers.

Searching and designing potential inhibitors for SARS-CoV-2 Mpro from natural sources using atomistic and deep-learning calculations

The spread of severe acute respiratory syndrome coronavirus 2 novel coronavirus (SARS-CoV-2) worldwide has caused the coronavirus disease 2019 (COVID-19) pandemic. A hundred million people were infected, resulting in several millions of death worldwide. In order to prevent viral replication, scientists have been aiming to prevent the biological activity of the SARS-CoV-2 main protease (3CL pro or Mpro). In this work, we demonstrate that using a reasonable combination of deep-learning calculations and atomistic simulations could lead to a new approach for developing SARS-CoV-2 main protease (Mpro) inhibitors. Initially, the binding affinities of the natural compounds to SARS-CoV-2 Mpro were estimated via atomistic simulations. The compound tomatine, thevetine, and tribuloside could bind to SARS-CoV-2 Mpro with nanomolar/high-nanomolar affinities. Secondly, the deep-learning (DL) calculations were performed to chemically alter the top-lead natural compounds to improve ligand-binding affinity. The obtained results were then validated by free energy calculations using atomistic simulations. The outcome of the research will probably boost COVID-19 therapy.