Cytochrome P450 3A4 suppression by epimedium and active compound kaempferol leads to synergistic anti-inflammatory effect with corticosteroid

Li, Ké; Yu, Xiuhua; Maskey, Anish; Musa, Ibrahim; Wang, Zhen-Zheng; García, Víctor; Guo, Austin M.; Yang, Nan; Dunkin, David; Li, Jun-Xiong; Guo, Longgang; Cheng, Yung‐Chi; Yuan, Haoliang; Tiwari, Raj K.; Li, Xiumin

doi:10.3389/fphar.2022.1042756

Cited by 6 publications

(3 citation statements)

References 32 publications

(33 reference statements)

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“…[ 17 , 18 ] TCM Integrated Pharmacology Research Platform v2.0 (TCMIP) ( http://www.tcmip.cn/ETCM/index.php/Home/ ) is known as the Traditional Chinese Medicine Encyclopedia. [ 19 ] The database contains 402 herbal medicines, 3959 remedies and 7284 active ingredients, in addition to 2266 possible gene targets of active ingredients and 4323 diseases. The database also provides the methodology and results of systematic analysis.…”

Section: Methodsmentioning

confidence: 99%

Preliminary study on molecular mechanism of COVID-19 intervention by Polygonum cuspidatum through computer bioinformatics

Liu,

Han,

Yan

2024

Medicine

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To explore the mechanism of action of Polygonum cuspidatum in intervening in coronavirus disease 2019 using a network pharmacology approach and to preliminarily elucidate its mechanism. The active ingredients and action targets of P cuspidatum were classified and summarized using computer virtual technology and molecular informatics methods. The active ingredients and relevant target information of P cuspidatum were identified using the TCM Systematic Pharmacology Database and Analysis Platform, the TCM Integrated Pharmacology Research Platform v2.0, and the SwissTarget database. The GENECARDS database was used to search for COVID-19 targets. The STRING database was analyzed and combined with Cytoscape 3.7.1 software to construct a protein interaction network map to screen the core targets. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was then performed. The core compound, polydatin, was selected and the core targets were analyzed by computer virtual docking using software such as discovery studio autodock tool. In vitro cell models were constructed to experimentally validate the activity of the core compound, polydatin. By computer screening, we identified 9 active ingredients and their corresponding 286 targets from P cuspidatum. A search of the GENECARDS database for COVID-19 yielded 303 core targets. By mapping the active ingredient targets to the disease targets, 27 overlapping targets could be extracted as potential targets for the treatment of COVID-19 with P cuspidatum. In addition, the enrichment analysis of Kyoto Encyclopedia of Genes and Genomes pathway on core targets showed that the coronavirus disease, MAPK signaling pathway, NF kappa B signaling pathway, and other signaling pathways were highly enriched. Combined with the degree-high target analysis in the protein interaction network, it was found to be mainly concentrated in the NF-kappaB (NF-κB) signaling pathway, indicating that the NF-κB signaling pathway may be an important pathway for P cuspidatum intervention. In vitro assays showed no effect of 0.1 to 10 μM polydatin on cell viability, but an inhibitory effect on the transcriptional activity of NF-κB-RE. Molecular docking showed stable covalent bonding of polydatin molecules with Il-1β protein at residue leu-26, TNF protein ser-60, residue gly-121, and residue ile-258 of ICAM-1 protein, indicating a stable docking result. The treatment of COVID-19 with P cuspidatum is characterized by multi-component, multi-target, and multi-pathway, which can exert a complex network of regulatory effects through the interaction between different targets, providing a new idea and basis for further exploration of the mechanism of action of P cuspidatum in the treatment of COVID-19.

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Section: Methodsmentioning

confidence: 99%

Preliminary study on molecular mechanism of COVID-19 intervention by Polygonum cuspidatum through computer bioinformatics

Liu,

Han,

Yan

2024

Medicine

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“…Candidate cmp_B12, derived from Epimrdii Herba, is a flavonoid with a predicted IC 50 value of 0.5 µM. It has been reported to inhibit CYP3A4, thus exhibiting anti-inflammatory effects [40]. Candidate cmp_B13, isolated from Coicis Semen, is a steroid with an average predicted IC 50 value of 0.27 µM.…”

Section: Potential Mpges-1 Inhibitors In the Mfh Databasementioning

confidence: 99%

Discovering the Active Ingredients of Medicine and Food Homologous Substances for Inhibiting the Cyclooxygenase-2 Metabolic Pathway by Machine Learning Algorithms

Tian,

Zhang,

Yan

2023

Molecules

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Cyclooxygenase-2 (COX-2) and microsomal prostaglandin E2 synthase (mPGES-1) are two key targets in anti-inflammatory therapy. Medicine and food homology (MFH) substances have both edible and medicinal properties, providing a valuable resource for the development of novel, safe, and efficient COX-2 and mPGES-1 inhibitors. In this study, we collected active ingredients from 503 MFH substances and constructed the first comprehensive MFH database containing 27,319 molecules. Subsequently, we performed Murcko scaffold analysis and K-means clustering to deeply analyze the composition of the constructed database and evaluate its structural diversity. Furthermore, we employed four supervised machine learning algorithms, including support vector machine (SVM), random forest (RF), deep neural networks (DNNs), and eXtreme Gradient Boosting (XGBoost), as well as ensemble learning, to establish 640 classification models and 160 regression models for COX-2 and mPGES-1 inhibitors. Among them, ModelA_ensemble_RF_1 emerged as the optimal classification model for COX-2 inhibitors, achieving predicted Matthews correlation coefficient (MCC) values of 0.802 and 0.603 on the test set and external validation set, respectively. ModelC_RDKIT_SVM_2 was identified as the best regression model based on COX-2 inhibitors, with root mean squared error (RMSE) values of 0.419 and 0.513 on the test set and external validation set, respectively. ModelD_ECFP_SVM_4 stood out as the top classification model for mPGES-1 inhibitors, attaining MCC values of 0.832 and 0.584 on the test set and external validation set, respectively. The optimal regression model for mPGES-1 inhibitors, ModelF_3D_SVM_1, exhibited predictive RMSE values of 0.253 and 0.35 on the test set and external validation set, respectively. Finally, we proposed a ligand-based cascade virtual screening strategy, which integrated the well-performing supervised machine learning models with unsupervised learning: the self-organized map (SOM) and molecular scaffold analysis. Using this virtual screening workflow, we discovered 10 potential COX-2 inhibitors and 15 potential mPGES-1 inhibitors from the MFH database. We further verified candidates by molecular docking, investigated the interaction of the candidate molecules upon binding to COX-2 or mPGES-1. The constructed comprehensive MFH database has laid a solid foundation for the further research and utilization of the MFH substances. The series of well-performing machine learning models can be employed to predict the COX-2 and mPGES-1 inhibitory capabilities of unknown compounds, thereby aiding in the discovery of anti-inflammatory medications. The COX-2 and mPGES-1 potential inhibitor molecules identified through the cascade virtual screening approach provide insights and references for the design of highly effective and safe novel anti-inflammatory drugs.

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“…Numerous studies have begun to focus on the food system with various co-existing flavonoids owing to health benefits of the combined effects [ 10 , 11 , 12 ]. Therefore, various studies with different models have been applied to explore the mechanisms of flavonoids combinations [ 13 , 14 , 15 , 16 ]. This study is based on this phenomenon, focusing on the synergistic effects of key flavonoids.…”

Section: Introductionmentioning

confidence: 99%

Characterization of the Synergistic Antioxidant Activity of Epigallocatechin Gallate (EGCG) and Kaempferol

et al. 2023

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Epigallocatechin gallate (EGCG) and kaempferol exhibit cellular antioxidant activity; however, their interactive effects in terms of antioxidant actions and underlying mechanisms remain unclear. In this study, their cytoprotective effects were examined against 2,2-azobis (2-amidinopropane) dihydrochloride solution (ABAP)-induced oxidative stress in HepG2 cells. The results showed that the median effective dose (EC50) of the EGCG and kaempferol (6:1.5, c/c) combination was 3.4 ± 0.1 μg/mL, with a combination index (CIavg) value of 0.54, which represented a significant synergistic effect. Further experiments proved that the combined pretreatment with EGCG and kaempferol exerted protective effects by suppressing reactive oxygen species (ROS) generation, upregulating cellular antioxidant enzyme activities (superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px)) in a dose-dependent manner. The mechanism of synergistic antioxidant effects of EGCG combined with kaempferol may be due to the up-regulation of higher antioxidant enzyme activities that improve the antioxidant capacities and balance the cell oxidative stress. The synergistic antioxidant effect of EGCG and kaempferol can provide a theoretical basis for the development of formulas of functional food ingredients.

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Cytochrome P450 3A4 suppression by epimedium and active compound kaempferol leads to synergistic anti-inflammatory effect with corticosteroid

Cited by 6 publications

References 32 publications

Preliminary study on molecular mechanism of COVID-19 intervention by Polygonum cuspidatum through computer bioinformatics

Preliminary study on molecular mechanism of COVID-19 intervention by Polygonum cuspidatum through computer bioinformatics

Discovering the Active Ingredients of Medicine and Food Homologous Substances for Inhibiting the Cyclooxygenase-2 Metabolic Pathway by Machine Learning Algorithms

Characterization of the Synergistic Antioxidant Activity of Epigallocatechin Gallate (EGCG) and Kaempferol

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