Various machine learning approaches coupled with molecule simulation in the screening of natural compounds with xanthine oxidase inhibitory activity

Rosmarinic acid in Perilla frutescens L. as a potential adenosine deaminase inhibitor: Preparation, machine learning validation and binding mechanism study

Gout, a prevalent arthritic disease, can be mitigated by adenosine deaminase (ADA) inhibitors that reduce uric acid production. In this study, the extraction process of rosmarinic acid (RA) from Perilla frutescens L. (P. frutescens) was optimized, and the best yield was 2.22 mg/g. Quantitative structure-activity relationship (QSAR) model was used to predict ADA inhibitors (ADAIs) in potential foods. The random forest model constructed by ChemoPy descriptor was the best (AUC = 0.9648), and five candidate compounds (including RA) were screened. The inhibitory activity of RA on ADA was confirmed in vitro (IC50 = 55.11 μM). Molecular docking showed that ADAIs and ADA were stably bound through hydrogen bonding and hydrophobic interaction. Molecular dynamics (MD) simulation verified the dynamic stability of ADAIs and ADA complexes. This study provides a theoretical basis for RA from P. frutescens extract as a potential compound for the treatment of gout and for the rapid screening of foodborne ADAIs.

Identification and mechanistic study of piceatannol as a natural xanthine oxidase inhibitor

Natural Xanthine oxidase (XOD) inhibitors represent promising therapeutic agents for hyperuricemia (HUA) treatment due to their potent efficacy and favorable safety profiles. This study involved the construction of a comprehensive database of 315 XOD inhibitors and development of 28 machine learning-based QSAR models. The ChemoPy light gradient boosting machine model exhibited the best performance (AUC = 0.9371 and MCC = 0.7423). This model identified three potential XOD inhibitors from the FooDB database: daphnetin, 7-hydroxycoumarin, and piceatannol. Molecular docking and dynamics simulations revealed favorable interactions, with piceatannol showing a remarkable stability through hydrogen bonding and hydrophobic interactions. ADME predictions suggested that all three compounds possess desirable drug-like properties and safety characteristics. Subsequent in vitro enzyme inhibition assays validated computational predictions, with piceatannol exhibiting the strongest inhibitory activity (IC50 = 8.80 ± 0.05 μM). Multispectroscopic analyses revealed that piceatannol-XOD binding was predominantly mediated by hydrogen bonding and van der Waals forces, which induced conformational changes characterized by decreased α-helical content and increased proportions of β-sheets, β-turns, and random coils. This study presents an efficient strategy for the identification of natural XOD inhibitors, elucidates the molecular mechanism of piceatannol-mediated XOD inhibition, and establishes a foundation for its therapeutic application in HUA treatment.

Exploring the anti-gout potential of sunflower receptacles alkaloids: A computational and pharmacological analysis

Gout, a painful condition marked by elevated uric acid levels often linked to the diet's high purine and alcohol content, finds a potential treatment target in xanthine oxidase (XO), a crucial enzyme for uric acid production. This study explores the therapeutic properties of alkaloids extracted from sunflower (Helianthus annuus L.) receptacles against gout. By leveraging computational chemistry and introducing a novel R-based clustering algorithm, "TriDimensional Hierarchical Fingerprint Clustering with Tanimoto Representative Selection (3DHFC-TRS)," we assessed 231 alkaloid molecules from sunflower receptacles. Our clustering analysis pinpointed six alkaloids with significant gout-targeting potential, particularly emphasizing the fifth cluster's XO inhibition capabilities. Through molecular docking and the BatchDTA prediction model, we identified three top compounds-2-naphthylalanine, medroxalol, and fenspiride-with the highest XO affinity. Further molecular dynamics simulations assessed their enzyme active site interactions and binding free energies, employing MM-PBSA calculations. This investigation not only highlights the discovery of promising compounds within sunflower receptacle alkaloids via LC-MS but also introduces medroxalol as a novel gout treatment candidate, showcasing the synergy of computational techniques and LC-MS in drug discovery.

Antihyperuricemic activity and inhibition mechanism of xanthine oxidase inhibitory peptides derived from whey protein by virtual screening

Xanthine oxidase (XO), a rate-limiting enzyme in uric acid production, is the pivotal therapeutic target for gout and hyperuricemia. In this study, 57 peptides from α-lactalbumin and β-lactoglobulin were obtained via virtual enzymatic hydrolysis, and 10 XO inhibitory peptides were virtually screened using molecular docking. Then toxicity, allergenicity, solubility, and isoelectric point of the obtained 10 novel peptides were evaluated by in silico tools. The XO activity of these synthetic peptides was tested using an in vitro assay by high-performance liquid chromatography. Their inhibitory mechanism was further explored by molecular docking. The results showed that 4 peptides GL, PM, AL, and AM exhibited higher inhibitory activity, and their half maximal inhibitory concentration in vitro was 10.20 ± 0.89, 23.82 ± 0.94, 34.49 ± 0.89, and 40.45 ± 0.92 mM, respectively. The peptides fitted well with XO through hydrogen bond, hydrophobic interaction, and van der Waals forces, and amino acid residues Glu802, Leu873, Arg880, and Pro1076 played an important role in this process. Overall, this study indicated 4 novel peptides GL, PM, AL, and AM from whey protein exhibited XO inhibitory activity, and they might be useful and safe XO inhibitors for hyperuricemia prevention and treatment.

Ferulic acid ameliorates hyperuricemia by regulating xanthine oxidase

Hyperuricemia is characterized by elevated uric acid (UA) level in the body. The xanthine oxidase (XO) inhibitory ability is an important way to evaluate the anti-hyperuricemia effect of natural products. Ferulic acid (FA) is a phenolic acid compound, and it is a free radical scavenger with many physiological functions. The aim of this study was to investigate the structure-activity relationship, potential mechanism and interaction of FA as XO's inhibitor. In the cell experiment, using 1.25 mM adenosine to incubate for 24 h under the optimal conditions (37 °C, pH = 7.2) can increase the UA production by 1.34 folds. PCR analysis showed that FA could reduce the mRNA expression level of XO. FA inhibited XO in a mixed mode (IC50 = 13.25 μM). The fluorescence quenching of XO by FA occurs through a static mechanism, with an inhibition constant of Ki = 9.527 × 10-5 mol L-1 and an apparent coefficient of α = 1.768. The enthalpy and entropy changes were found as -267.79 KJ mol-1 and - 860.85 KJ mol-1, indicating that both hydrogen binding and hydrophobic are involved in the interaction of this polyphenolic natural compound with XO. Thus, FA supplementation may be a potential therapeutic strategy to improve hyperuricemia by reducing UA production.

Novel xanthine oxidase inhibitory peptides derived from whey protein: identification, in vitro inhibition mechanism and in vivo activity validation

As the development of hyperuricemia (HUA) and gout continues to accelerate worldwide, there is increasing interest in the use of xanthine oxidase (XO) inhibitors as therapeutic agents for the management of HUA and gout. In the present study, XO inhibitory peptides were identified from whey protein isolate (WPI) hydrolysates, and the underlying inhibitory mechanism and in vivo activities was investigated. WPI hydrolysates were isolated and purified, and two peptides (ALPM and LWM) with lower binding energy were screened by molecular docking. The result showed that these two peptides interacted with residues around the active site of XO through hydrogen bond and hydrophobic interaction. The IC₅₀ values of ALPM and LWM were 7.23 ± 0.22 and 5.01 ± 0.31 mM, respectively. According to the Lineweaver-Burk curve, the inhibition types of ALPM and LWM were non-competitive inhibition. Circular dichroism (CD) spectra indicated ALPM and LWM could change the secondary structure of XO. Molecular dynamics simulations revealed that XO-peptide complexes were more stable and compact than XO. Moreover, animal studies have shown that ALPM and LWM have anti-hyperuricemia effects in vivo. This study suggested that ALPM and LWM can be considered as natural XO inhibitors for the treatment of HUA.

Combination of Machine Learning Algorithms with Concentration-Area Fractal Method for Soil Geochemical Anomaly Detection in Sediment-Hosted Irankuh Pb-Zn Deposit, Central Iran

Prediction of geochemical concentration values is essential in mineral exploration as it plays a principal role in the economic section. In this paper, four regression machine learning (ML) algorithms, such as K neighbor regressor (KNN), support vector regressor (SVR), gradient boosting regressor (GBR), and random forest regressor (RFR), have been trained to build our proposed hybrid ML (HML) model. Three metric measurements, including the correlation coefficient, mean absolute error (MAE), and means squared error (MSE), have been selected for model prediction performance. The final prediction of Pb and Zn grades is achieved using the HML model as they outperformed other algorithms by inheriting the advantages of individual regression models. Although the introduced regression algorithms can solve problems as single, non-complex, and robust regression models, the hybrid techniques can be used for the ore grade estimation with better performance. The required data are gathered from in situ soil. The objective of the recent study is to use the ML model’s prediction to classify Pb and Zn anomalies by concentration-area fractal modeling in the study area. Based on this fractal model results, there are five geochemical populations for both cases. These elements' main anomalous regions were correlated with mining activities and core drilling data. The results indicate that our method is promising for predicting the ore elemental distribution.

Vanillic Acid as a Promising Xanthine Oxidase Inhibitor: Extraction from Amomum villosum Lour and Biocompatibility Improvement via Extract Nanoemulsion

Gout is an oxidative stress-related disease. Food-derived vanillic acid, a promising xanthine oxidase inhibitor, could potentially be used as a safe, supportive, and therapeutic product for gout. The extraction of vanillic acid from a classic Chinese herbal plant Amomum villosum with ethanol was investigated in the study. The optimum conditions were determined as extraction time of 74 min, extraction temperature of 48.36 °C, and a solid-to-liquid ratio of 1:35 g·mL⁻¹ using the Box–Behnken design (BBD) of response surface methodology (RSM). The experimental extraction yield of 9.276 mg·g⁻¹ matched with the theoretical value of 9.272 ± 0.011 mg·g⁻¹ predicted by the model. The vanillic acid in Amomum villosum was determined to be 0.5450 mg·g⁻¹ by high-performance liquid chromatography–diode array detection (HPLC–DAD) under the optimum extraction conditions and exhibited xanthine oxidase (XO) inhibitory activity, with the half-maximal inhibitory concentration (IC50) of 1.762 mg·mL⁻¹. The nanoemulsion of Amomum villosum extract consists of 49.97% distilled water, 35.09% S_mix (mixture of tween 80 and 95% ethanol with 2:1 ratio), and 14.94% n-octanol, with a particle size of 110.3 ± 1.9 nm. The nanoemulsion of Amomum villosum extract exhibited markable XO inhibitory activity, with an inhibition rate of 58.71%. The result demonstrated the potential benefit of Amomum villosum as an important dietary source of xanthine oxidase inhibitors for gout.

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.