Exploring the anti-inflammatory effects of bioactive compounds from assam tea clones: in silico and in vitro approaches

Year 2025, Volume: 12 Issue: 3, 572 - 581, 04.09.2025

Nishanth Pitcham , Hariram Natarajan

https://doi.org/10.21448/ijsm.1542644

Abstract

The consumption of tea, derived from Camellia sinensis, ranks second globally after water. This research explores the anti-inflammatory properties of tea plant varieties from Assam, including TEEN ALI, TV-17, and TV-22, through a comprehensive approach that combines experimental and computational techniques. The Albumin Denaturation Method revealed significant anti-inflammatory effects in all three varieties, with TV-22 demonstrating the highest inhibition rate at 82.11%. This underscores its potential as a powerful anti-inflammatory agent, warranting further investigation. In this study, comparative analysis indicates a link between the composition of tea plant samples and their anti-inflammatory efficacy. In silico modeling, particularly molecular docking, was utilized to evaluate the interaction of selected bioactive compounds with key inflammatory receptors—COX-2, IL-1, and IL-18. Compounds like 2,4-di-tert-butylphenol and caffeine displayed interactions and have energy values comparable to or superior to standard drugs (Diclofenac and Aspirin), suggesting their potential as promising drug candidates. However, the valuable insights the results provided underscore the importance of conducting thorough experimental validations, such as in vitro and in vivo studies, to confirm the efficacy and safety of identified compounds. It opens up avenues for future research by stressing the need to extensively explore specific bioactive compounds, especially in TV-22, which could lead to the development of new anti-inflammatory therapeutics. This interdisciplinary study establishes a groundwork for understanding the therapeutic potential of tea plants and provides a roadmap for creating anti-inflammatory drugs from in natural sources.

Keywords

Camellia sinensis , Bioactive compounds , Anti-inflammatory , In silico modeling , Caffein

Project Number

1

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