ArticleMolecular diversity2023
Evaluation of tea (Camellia sinensis L.) phytochemicals as multi-disease modulators, a multidimensional in silico strategy with the combinations of network pharmacology, pharmacophore analysis, statistics and molecular docking.
Article in Molecular diversity, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 20 citations in OpenAlex.
- Chemical screening of Hibiscus rosa-sinensis for their phytochemicals and their in vitro/in silico evaluation as α-amylase inhibitors.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Liubao tea as a functional fermented food: multi-omics insights into its modulation of lymphatic endothelial cell metabolism.Frontiers in nutrition · 2026Article
- Exploring the Potential of Dolutegravir in Alzheimer's Disease Treatment: Insights from Network Pharmacology andCentral nervous system agents in medicinal chemistry · 2026Article
- Article
- Synthesis and Isolation of Phenol- and Thiol-Derived Epicatechin Adducts Prepared from Avocado Peel Procyanidins Using Centrifugal Partition Chromatography and the Evaluation of Their Antimicrobial and Antioxidant Activity.Molecules (Basel, Switzerland) · 2024Article
- Network pharmacology and molecular docking: combined computational approaches to explore the antihypertensive potential of Fabaceae species.Bioresources and bioprocessing · 2024Article
- Revealing the role of metformin in gastric intestinal metaplasia treatment.Frontiers in pharmacology · 2024Article
- Evaluation of therapeutic potentials of selected phytochemicals against Nipah virus, a multi-dimensional in silico study.3 Biotech · 2023Article
- Antidiabetic Actions of Ethanol Extract ofMedicines (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Tea (Camellia sinensis L.) is considered as to be one of the most consumed beverages globally and a reservoir of phytochemicals with immense health benefits. Despite numerous advantages, tea compounds lack a robust multi-disease target study. In this work, we presented a unique in silico approach consisting of molecular docking, multivariate statistics, pharmacophore analysis, and network pharmacology approaches. Eight tea phytochemicals were identified through literature mining, namely gallic acid, catechin, epigallocatechin gallate, epicatechin, epicatechin gallate (ECG), quercetin, kaempferol, and ellagic acid, based on their richness in tea leaves. Further, exploration of databases revealed 30 target proteins related to the pharmacological properties of tea compounds and multiple associated diseases. Molecular docking experiment with eight tea compounds and all 30 proteins revealed that except gallic acid all other seven phytochemicals had potential inhibitory activities against these targets. The docking experiment was validated by comparing the binding affinities (Kcal mol
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