Open Access Journal of Kinesiology and Sports Medicine (OAJKSM)

ISSN: 2995-0155

Research Article

Potentiality of Resveratrol in Mitigating Exercise-Induced Inflammation - A Bioinformatic Study on Interleukin-6 (IL-6) in Athletes

Authors: Arijit Chakraborty, Debasree Lodh and Surajit Bhattacharjee*

DOI: 10.23880/oajksm-16000111

Abstract

Background: Athletes, engaging in vigorous exercise, confront elevated reactive oxygen species (ROS) and inflammation. Dietary antioxidants, abundant in diverse foods, offer protection. Resveratrol, a potent polyphenol from grapes and berries, explores its anti-inflammatory potential and mechanism through in-silico analysis in athletes. Method: Initial steps involved IL-6 data retrieval (PDB ID 1alu), receptor preparation, and ligand selection (Resveratrol, CID 445154). IL-6 receptor binding site identification utilized literature and PyMol. Molecular docking was facilitated by AutoDock, validated through re-docking and overlay methods. Lead molecule selection in in silico virtual screening was based on binding energy (-5 to -15 kcal/mol). The evaluation concluded with interaction assessment and binding affinity calculation. Result and Discussion: The study utilized IL-6 from the Protein Data Bank. Resveratrol was prepared for molecular docking. Docking outcomes showed optimal fit and interaction of resveratrol with IL-6, forming three bonds and exhibiting a low binding energy of -5.2 kcal/mol. The research addressed exercise-induced inflammation, emphasizing IL-6's role. Bioinformatics and molecular docking provided insights into IL-6 binding. Resveratrol demonstrated a potential inhibitory effect on IL-6 action, presenting a promising avenue for anti-inflammatory intervention in athletes. Conclusion: Exploring resveratrol's anti-inflammatory potential on IL-6, our study used molecular docking, suggesting its protective effects in athletes. Ongoing research is vital for validation and broader implications.

Keywords: Exercise; Inflammation; Resveratrol; Interleukin-6 (Il-6); Bioinformatics

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