Metabolic profiling of milk thistle different organs using UPLC-TQD-MS/MS coupled to multivariate analysis in relation to their selective antiviral potential.

INTRODUCTION: Silybum marianum commonly known as milk thistle is one of the most imperative medicinal plants due to its remarkable pharmacological activities. Lately, the antiviral activities of S. marianum extract have been studied and it showed effectiveness against many viruses. OBJECTIVE: Although most previous studies were concerned mainly with silymarin content of the fruit, the present study provides comprehensive comparative evaluation of S. marianum different organs' chemical profiles using UPLC-MS/MS coupled to chemometrics to unravel potentially selective antiviral compounds against human coronavirus (HCoV-229E). METHODOLOGY: UPLC-ESI-TQD-MS/MS analysis was utilized to establish metabolic fingerprints for S. marianum organs namely fruits, roots, stems and seeds. Multivariate analysis, using OPLS-DA and HCA-heat map was applied to explore the main discriminatory phytoconstituents between organs. Selective virucidal activity of organs extracts against coronavirus (HCoV-229E) was evaluated for the first time using cytopathic effect (CPE) inhibition assay. Correlation coefficient analysis was implemented for detection of potential constituents having virucidal activity. RESULTS: UPLC-MS/MS analysis resulted in 87 identified metabolites belonging to different classes. OPLS-DA revealed in-between class discrimination between milk thistle organs proving their significantly different metabolic profiles. The results of CPE assay showed that all tested organ samples exhibited dose dependent inhibitory activity in nanomolar range. Correlation analysis disclosed that caffeic acid-O-hexoside, gadoleic and linolenic acids were the most potentially selective antiviral phytoconstituents. CONCLUSION: This study valorizes the importance of different S. marianum organs as wealthy sources of selective and effective antiviral candidates. This approach can be extended to unravel potentially active constituents from complex plant matrices.

Deciphering the putative bioactive metabolites and the underlying mechanism of Juniperus horizontalis Moench (Creeping juniper) in the treatment of inflammation using network pharmacology and molecular docking.

OBJECTIVES: To investigate the chemical composition of the alcoholic extract from creeping juniper leaves using HPLC-MS/MS and to elucidate its potential anti-inflammatory mechanism through network-based pharmacology analysis to collectively enable a systematic exploration of the chemical composition, mechanism of action, and therapeutic potential of the alcoholic extract from creeping juniper leaves, providing valuable insights into its suitability as an anti-inflammatory agent. METHODS: Chemical profiling of the alcoholic extract of creeping juniper leaves using HPLC-MS/MS and revealing its anti-inflammatory mechanism using network-based pharmacology. Further, isolation of some of the identified biomarkers, assessment of their ex-vivo anti-inflammatory activity, and determination of their binding to pro-inflammatory cytokines using molecular docking and dynamics. KEY FINDINGS: Thirty-seven compounds were annotated and forwarded to network pharmacology analysis which revealed that the highest interactions were exhibited by quercetin, cosmosiin, myricetin, amentoflavone, hyperoside, isorhamnetin, and quercitrin whereas the most enriched inflammatory targets were IL-2, PGF, VEGFA, and TNFs. PI3K-Akt signaling pathway, arachidonic acid metabolism, and MAPK signaling pathway were found to be the most enriched ones. Six hit compounds were isolated and identified as hyperoside, quercetrin, cupressuflavone, hinokiflavone, amentoflavone, and quercetin. The isolated compounds showed strong anti-inflammatory activity against TNF-α, IL-6, and IL-1ß, and molecular docking and dynamics simulation showed that quercetin, quercitrin, and hyperoside had the least binding energy with TNF-α, IL-6, and IL-1B, respectively. CONCLUSIONS: Creeping juniper may reduce inflammation based on the suggested multi-compounds and multi-pathways, and that provided the basis for creeping juniper use as a potential anti-inflammatory drug.

Metabolic profiling of Lantana camara L. using UPLC-MS/MS and revealing its inflammation-related targets using network pharmacology-based and molecular docking analyses.

Lantana camara L. is widely used in folk medicine for alleviation of inflammatory disorders, but studies that proved this folk use and that revealed the molecular mechanism of action in inflammation mitigation are not enough. Therefore, this study aimed to identify L. camara phytoconstituents using UPLC-MS/MS and explain their multi-level mechanism of action in inflammation alleviation using network pharmacology analysis together with molecular docking and in vitro testing. Fifty-seven phytoconstituents were identified in L. camara extract, from which the top hit compounds related to inflammation were ferulic acid, catechin gallate, myricetin and iso-ferulic acid. Whereas the most enriched inflammation related genes were PRKCA, RELA, IL2, MAPK 14 and FOS. Furthermore, the most enriched inflammation-related pathways were PI3K-Akt and MAPK signaling pathways. Molecular docking revealed that catechin gallate possessed the lowest binding energy against PRKCA, RELA and IL2, while myricetin had the most stabilized interaction against MAPK14 and FOS. In vitro cytotoxicity and anti-inflammatory testing indicated that L. camara extract is safer than piroxicam and has a strong anti-inflammatory activity comparable to it. This study is a first step in proving the folk uses of L. camara in palliating inflammatory ailments and institutes the groundwork for future clinical studies.

Alleviation of liver cirrhosis and associated portal-hypertension by Astragalus species in relation to their UPLC-MS/MS metabolic profiles: a mechanistic study.

Liver cirrhosis is a late-stage liver disease characterized by excessive fibrous deposition triggering portal-hypertension (PH); the prime restrainer for cirrhosis-related complications. Remedies that can dually oppose hepatic fibrosis and lower PH, may prevent progression into decompensated-cirrhosis. Different Astragalus-species members have shown antifibrotic and diuretic actions with possible subsequent PH reduction. However, A.spinosus and A.trigonus were poorly tested for eliciting these actions. Herein, A.spinosus and A.trigonus roots and aerial parts extracts were subjected to comprehensive metabolic-fingerprinting using UHPLC-MS/MS resulting in 56 identified phytoconstituents, followed by chemometric untargeted analysis that revealed variable metabolic profiles exemplified by different species and organ types. Consequently, tested extracts were in-vivo evaluated for potential antifibrotic/anticirrhotic activity by assessing specific markers. The mechanistic prospective to induce diuresis was investigated by analyzing plasma aldosterone and renal-transporters gene-expression. Serum apelin and dimethylarginine-dimethylaminohydrolase-1 were measured to indicate the overall effect on PH. All extracts amended cirrhosis and PH to varying extents and induced diuresis via different mechanisms. Further, An OPLS model was built to generate a comprehensive metabolic-profiling of A.spinosus and A.trigonus secondary-metabolites providing a chemical-based evidence for their efficacious consistency. In conclusion, A.spinosus and A.trigonus organs comprised myriad pharmacologically-active constituents that act synergistically to ameliorate cirrhosis and associated PH.

Chemical profiling and unraveling of anti-COVID-19 biomarkers of red sage (Lantana camara L.) cultivars using UPLC-MS/MS coupled to chemometric analysis, in vitro study and molecular docking.

ETHNOPHARMACOLOGICAL RELEVANCE: Red sage (Lantana camara L.) (Verbenaceae) is a widely spread plant that was traditionally used in Brazil, India, Kenya, Thailand, Mexico, Nigeria, Australia and Southeast Asia for treating several ailments including rheumatism and leprosy. Despite its historical role in relieving respiratory diseases, limited studies progressed to the plant's probable inhibition to respiratory viruses especially after the striking spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. AIM OF THE STUDY: This study aimed to investigate the inhibitory activity of different L. camara cultivars to SARS-CoV-2, that was not previously inspected, and clarify their mechanisms of action in the metabolomics viewpoint, and to determine the biomarkers that are related to such activity using UPLC-MS/MS coupled to in vitro-studies and chemometric analysis. MATERIALS AND METHODS: Chemical profiling of different cultivars was accomplished via UPLC-MS/MS. Principle component analysis (PCA) and orthogonal projection to latent structures (OPLS) models were built using SIMCA® (multivariate data analysis software). Cytotoxicity and COVID-19 inhibitory activity testing were done followed by TaqMan Real-time RT-PCR (Reverse transcription polymerase chain reaction) assay that aimed to study extracts' effects on RNA-dependent RNA polymerase (RdRp) and E-genes expression levels. Detected biomarkers from OPLS analysis were docked into potential targets pockets to investigate their possible interaction patterns using Schrodinger® suite. RESULTS: UPLC-MS/MS analysis of different cultivars yielded 47 metabolites, most of them are triterpenoids and flavonoids. PCA plots revealed that inter-cultivar factor has no pronounced effect on the chemical profiles of extracts except for L. camara, cultivar Drap d'or flowers and leaves extracts as well as for L. camara cv Chelsea gem leaves extract. Among the tested extracts, flowers and leaves extracts of L. camara cv Chelsea gem, flowers extracts of L. camara cv Spreading sunset and L. camara cv Drap d'or showed the highest selectivity indices scoring 12.3, 10.1, 8.6 and 7.8, respectively, indicating their relative high safety and efficacy. Leaves and flowers extracts of L. camara cv Chelsea gem, flowers extracts of L. camara cv Spreading sunset and L. camara cv Drap d'or were the most promising inhibitors to viral plaques exhibiting IC50 values of 3.18, 3.67, 4.18 and 5.01 µg/mL, respectively. This was incremented by OPLS analysis that related their promising COVID-19 inhibitory activities to the presence of twelve biomarkers. Inhibiting the expression of RdRp gene is the major mechanism behind the antiviral activity of most extracts at almost all concentration levels. Molecular docking of the active biomarkers against RdRp revealed that isoverbascoside, luteolin-7,4'-O-diglucoside, camarolic acid and lantoic acid exhibited higher docking scores of -11.378, -10.64, -6.72 and -6.07 kcal/mol, respectively, when compared to remdesivir (-5.75 kcal/mol), thus these four compounds can serve as promising anti-COVID-19 candidates. CONCLUSION: Flowers and leaves extracts of four L. camara cultivars were recognized as rich sources of phytoconstituents possessing anti-COVID-19 activity. Combination of UPLC-MS/MS and chemometrics is a promising approach to detect chemical composition differences among the cultivars and correlate them to COVID-19 inhibitory activities allowing to pinpoint possible biomarkers. Further in-vitro and in-vivo studies are required to verify their activity.

Network pharmacology-based analysis for unraveling potential cancer-related molecular targets of Egyptian propolis phytoconstituents accompanied with molecular docking and in vitro studies.

Cancer is one of the predominant causes of death worldwide. The new trend nowadays is to exploit natural products with the hope of developing new anticancer agents with fewer side effects. Propolis is one of these natural products which showed effectiveness in cancer treatment. The aim of this study is to understand the multi-level mechanism of action of propolis constituents in cancer treatment using an integrated approach of network pharmacology-based analysis, molecular docking and in vitro cytotoxicity testing. An inhouse database of chemical constituents from Egyptian propolis was compiled and assessed for its ADME properties using the QikProp module in the Schrodinger software. STITCH, UniProt, STRING, KEGG and DAVID databases were used for construction of constituent-target gene, gene-pathway, and constituent-target gene-pathway networks with the aid of Cytoscape 3.8.2. The network pharmacology-based analysis showed that the hit propolis constituents related to cancer targets were genistein, luteolin, benzoic acid, quercetin and vanillic acid, whereas the main cancer-associated targets were CYP1A1, CYP19A1, ESR1, NOS3, CASP3 and AKT1. Twenty-four cancer-related pathways were recognized where the most enriched ones were pathways in cancer and estrogen signaling pathway. The most enriched biological processes involved in the mechanism of action of propolis constituents in cancer treatment were negative regulation of the apoptotic process and the metabolic process and negative regulation of cellular glucuronidation. Molecular docking analysis of the top hit compounds against the most enriched target proteins in the constructed networks was carried out using the Maestro interface of the Schrodinger software. Among hit compounds, quercetin and genistein exhibited the most stabilized interaction. Finally, confirmation of the potential anticancer activity of propolis was assured by in vitro cytotoxicity testing of propolis extract on human prostate cancer (DU-145), breast adenocarcinoma (MCF-7) and colorectal adenocarcinoma (Caco-2) cell lines. This study presents deeper insights about propolis molecular mechanisms of action in cancer for the first time using an integrated approach of network pharmacology, molecular docking and in vitro testing.

Royal jelly fatty acids bioprofiling using TLC-MS and digital image analysis coupled with chemometrics and non-parametric regression for discovering efficient biomarkers against melanoma.

A comprehensive approach of untargeted and targeted fatty acid bioprofiling of different royal jelly commercial and pharmaceutical products based on HPTLC-image analysis and melanoma cytotoxic activity together with chemometric analysis was applied in this study for discovering efficient biomarkers. Principal component analysis based on HPTLC-image analysis fingerprints of fatty acid loading plots were used to determine the chemical markers responsible for classification of royal jelly samples into fresh and lyophilized ones. These markers were identified using the HPTLC-MS technique as 8-hydroxyoctanoic acid, 3,10-dihydroxydecanoic acid, 10-hydroxy-2-decenoic acid, decanedioic acid and 10-hydroxydecanoic acid. These discriminating markers were quantified via the HPTLC-imaging technique for targeted profiling using two different methods: parametric and non-parametric regression. The non-parametric regression method exhibited superiority in terms of linearity, accuracy and precision. Biomarkers were determined from the 3D-loading plot of orthogonal projection to latent structures model based on the fatty acid quantitative data together with the melanoma cytotoxic activity data. 10-Hydroxy-2-decenoic acid showed the greatest reduction in melanoma cell viability followed by decanedioic acid then 8-hydroxyoctanoic acid. The present study is considered the first attempt to discriminate fresh and lyophilized royal jelly samples based on their holistic lipidomic profile to discover efficient fatty acid reducing melanoma cell viability.

A Validated Stability-Indicating HPTLC Assay for Determination of 10-Hydroxy-2-Decenoic Acid Content in Royal Jelly Products Using Robust Regression Methods.

A new, simple, stability-indicating high-performance thin-layer chromatography method was developed for the quantification of 10-hydroxy-2-decenoic acid (10-HDA) in some royal jelly products marketed in Egypt. The used solvent system was chloroform:acetic acid (10:1, v/v) and the bands were measured densitometrically at 210 nm. First- and second-derivative treatments of the data were performed. The present study shows a comparison between three statistical regression methods for handling data: parametric, nonparametric and weighted regression (WR) methods. The developed methods were validated as per International Conference on Harmonization guidelines. To validate the stability-indicating power of the developed analytical method, the royal jelly standard was subjected to forced degradation studies including the effect of hydrolysis, oxidation, photolysis and dry heat. It was found that derivative treatment of the chromatographic response data gives improved quantitation and sensitivity of the chromatographic signals. Weighted regression of the response data is found to be advantageous over the use of both parametric and nonparametric regression models. This was shown by a great enhancement in the accuracy and precision in the analysis of 10-HDA in royal jelly products. The % recovery in case of WR was 99.92 ± 0.16, while % recovery in case of nonparametric and parametric regressions were 99.56 ± 0.25 and 98.63 ± 0.65, respectively.

Analysis of astragalosides I, II and IV in some Egyptian Astragalus species and Astragalus dietary supplements using high-performance liquid chromatography/evaporative light scattering detector and non-parametric regression.

INTRODUCTION: GenuTs Astragalus L. is characterised by the presence of cycloartane saponins which have wide biological activities such as antioxidant, immunomodulating' hepatoprotective and anti-inflammatory activities. From these cycloartane saponins are astragalosides I, II and IV which have been regarded as the most important active constituents in Astragalus species. OBJECTIVES: This work describes the quantitative analysis of astragalosides I, II and IV in some Egyptian Astragalus species and Astragalus dietary supplements in a single run by high-performance liquid chromatography/evaporative light scattering detector (HPLC/ELSD) using gradient elution. METHODOLOGY: The method of quantitation adopted in this study is the standard addition method. First and second derivative treatment of the data was performed, and the study presents comparison between two statistical regression methods for handling data; parametric and non-parametric regression methods. RESULTS: Derivative treatment of the chromatographic response data gives improved quantitation of the chromatographic signals. Non-parametric regression of the data using Theil's method is advantageous over the usual least squares method as it assumes that errors could occur in both x- and y-directions and they might not be normally distributed. In addition, it could effectively circumvent any outlier data points. CONCLUSION: Due to the simplicity and the good accuracy and reproducibility of the suggested methods, they could be used for analysis and quality control of Astragalus species and Astragalus dietary supplements.