Xanthine oxidase inhibitors: Virtual screening and mechanism of inhibition studies

Xanthine oxidase (XO), which plays a key role in purine metabolism, is an important target enzyme for the prevention and treatment of hyperuricemia. Inhibitory activity against XO is a common criterion for the screening of compounds with potential anti-hyperuricemic activity. In this study, 22 XO inhibitors were used to construct a 3D-QSAR pharmacophore model. Subsequently, molecular docking and in vitro activity evaluations were used to identify strong XO inhibitors from a list of 2000 natural compounds. The interaction mechanisms of these compounds with XO were analyzed based on inhibition kinetics and multi-spectral analyses. The pharmacophore model was composed of three hydrogen bond receptors and a hydrophobic center. The screened compounds - Diosmetin, Fisetin, and Genistein - all showed good XO inhibitory activity, with IC50 values of 1.86 ± 0.11 μM, 5.83 ± 0.08 μM, and 7.56 ± 0.10 μM, respectively. Kinetic analysis, fluorescence quenching assays, and molecular docking experiments showed that Diosmetin, Fisetin, and Genistein docked near the same active site of XO, mainly affecting the microenvironment of tryptophan residues. These molecules showed static binding to XO via hydrogen bonds, hydrophobic interactions, and van der Waals forces. Diosmetin and Genistein were competitive inhibitors, whereas Fisetin was a mixed inhibitor. Infrared spectroscopy showed that Diosmetin, Fisetin, and Genistein increased the α-helix content of XO from 7.4 % to 16.6 %, 21.4 %, and 11.2 %, respectively, thereby enhancing its stability. In summary, the pharmacophore model constructed in this study was accurate. The flavonoids Diosmetin, Fisetin, and Genistein effectively inhibited the activity of XO, and the amino acid residues LEU257, ILE353, and VAL259 played a key role in the interaction between the flavonoids and XO. These findings are of great significance for the screening and development of new XO inhibitors.

Biological Evaluation, Molecular Docking Analyses, and ADME Profiling of Certain New Quinazolinones as Anti-colorectal Agents

Colorectal carcinogenesis is a complex process, which is linked to dysregulation of human secretory phospholipases A₂ (hsPLA₂-G-IIA, hsPLA₂-G-V, and hsPLA₂-G-X), proteases (cathepsin-B, collagenase, thrombin, elastase, and trypsin), carbohydrate hydrolyzing enzymes (α-amylase and α-glucosidase), and free radical generating enzyme (xanthine oxidoreductase (XOR)). Therefore, some new quinazolinones were synthesized and evaluated as inhibitors against this array of enzymes as well as cytotoxic agents on LoVo and HCT-116 cells of colorectal cancer. Compounds 3g, 10, 8, 3c, and 1c exhibited promising cytotoxic effects with IC₅₀ values ranging from 206.07 to 459.79 μM. Nine compounds showed promising enzymatic inhibitory effects, 3b, 3d, 3f, 5, 1a, and 12 (α-amylase), 8 (thrombin, elastase and trypsin), 10 (hsPLA₂-G-IIA and hsPLA₂-G-V), and 3f (α-glucosidase and XOR). Therefore, the most active inhibitors, were subjected to validated molecular docking studies to identify their affinities and binding modes. The expected physicochemical and pharmacokinetic features of the active candidates, 1a, 1c, 3b, 3c, 3d, 3f, 3g, 5, 8, 10, and 12 were predicted using bioavailability radar charts and boiled-egg graphical representations along with the Lipinski rule of five filter. Collectively, these studies showed the significance of derivatives 1c, 3b, 3c, 3d, 8, 10, and 12 as lead scaffolds for further optimization to develop enzymes inhibitors and anti-colorectal agents.

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.

Hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) Simulation: A Tool for Structure-based Drug Design and Discovery

Quantum mechanics (QM) is physics based theory which explains the physical properties of nature at the level of atoms and sub-atoms. Molecular mechanics (MM) construct molecular systems through the use of classical mechanics. So, hybrid quantum mechanics and molecular mechanics (QM/MM) when combined together can act as computer-based methods which can be used to calculate structure and property data of molecular structures. Hybrid QM/MM combines the strengths of QM with accuracy and MM with speed. QM/MM simulation can also be applied for the study of chemical process in solutions as well as in the proteins, and has a great scope in structure-based drug design (CADD) and discovery. Hybrid QM/MM also applied to HTS, to derive QSAR models and due to availability of many protein crystal structures; it has a great role in computational chemistry, especially in structure- and fragment-based drug design. Fused QM/MM simulations have been developed as a widespread method to explore chemical reactions in condensed phases. In QM/MM simulations, the quantum chemistry theory is used to treat the space in which the chemical reactions occur; however the rest is defined through molecular mechanics force field (MMFF). In this review, we have extensively reviewed recent literature pertaining to the use and applications of hybrid QM/MM simulations for ligand and structure-based computational methods for the design and discovery of therapeutic agents.

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

Xanthine oxidase (XO), which can catalyze the formation of xanthine or hypoxanthine to uric acid, is the most important target of gout. To explore the conformational changes for inhibitor binding, molecular dockings and molecular dynamics simulations were performed. Docking results indicated that three inhibitors had similar pose binding to XO. Molecular dynamics simulations showed that the binding of three inhibitors influenced the secondary structure changes in XO. After binding to the inhibitor, the peptide Phe798-Leu814 formed different degrees of unhelix, while for the peptide Glu1065-Ser1075, only a partial helix region was formed when allopurinol was bound. Through the protein structure analysis in the simulation process, we found that the distance between the active residues Arg880 and Thr1010 was reduced and the distance between Glu802 and Thr1010 was increased after the addition of inhibitors. The above simulation results showed the similarities and differences of the interaction between the three inhibitors binding to the protein. MM-PBSA calculations suggested that, among three inhibitors, allopurinol had the best binding effect with XO followed by daidzin and puerarin. This finding was consistent with previous experimental data. Our results can provide some useful clues for further gout treatment research.