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Molecular Docking and dynamic simulation analysis of flavonoid derivatives as COX-2 inhibitors
Pasula Janakiramulu1, Estari Mamidala1
1Department of Zoology, Kakatiya University, Vidyaranyapuri, Warangal, Telangana State 506009 India.
Abstract:
Cyclooxygenase-2 (COX-2) is a key enzyme involved in inflammation and tumor progression, playing a significant role in the development of various cancers, including colorectal, breast, lung, and prostate cancers. In this study, molecular docking and molecular dynamics (MD) simulations were conducted to evaluate the binding potential and stability of flavonoid compounds as potential COX-2 inhibitors. A total of 36 flavonoid compounds were selected based on pharmacokinetic properties and subjected to molecular docking analysis. Binding affinity calculations revealed that several flavonoids exhibited strong interactions with COX-2, with Cudraflavone A showing the highest binding affinity of - 10.19 kcal/mol, surpassing the standard inhibitor Rofecoxib (- 9.4 kcal/mol). Key interactions were identified with critical active site residues, including Tyr130, Glu465, and Arg44, through hydrogen bonding and hydrophobic interactions. To further assess the stability of the COX-2-flavonoid complex, molecular dynamics simulations were performed using GROMACS. Root-mean-square deviation (RMSD) analysis demonstrated that the COX-2-Cudraflavone A complex exhibited greater structural stability compared to the unbound enzyme. Root-mean-square fluctuation (RMSF) analysis indicated reduced flexibility in key regions of the enzyme upon ligand binding, reinforcing its stabilizing effect. Additionally, the radius of gyration (Rg) analysis confirmed that the complex maintained a more compact conformation, suggesting enhanced structural integrity. These findings suggest that Cudraflavone A is a promising candidate for COX-2 inhibition, exhibiting superior binding affinity and stabilizing effects. This study provides valuable insights into the potential development of flavonoid-based COX-2 inhibitors for cancer and anti-inflammatory therapeutics.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s40203-025-00349-x.
Insights
Cudraflavone A shows superior binding affinity and stability as a cyclooxygenase-2 (COX-2) inhibitor compared to Rofecoxib. This flavonoid compound offers potential for developing new anti-cancer and anti-inflammatory drugs.
Area of Science:
- * Computational chemistry
- * Molecular pharmacology
- * Medicinal chemistry
Background:
- * Cyclooxygenase-2 (COX-2) is implicated in inflammation and the progression of various cancers.
- * Developing selective COX-2 inhibitors is crucial for therapeutic interventions.
- * Flavonoids are natural compounds with potential pharmacological activities.
Purpose of the Study:
- * To evaluate the binding potential and stability of flavonoid compounds as COX-2 inhibitors using computational methods.
- * To identify potent flavonoid inhibitors with superior efficacy compared to existing drugs.
- * To explore the molecular interactions between flavonoids and the COX-2 active site.
Main Methods:
- * Molecular docking simulations were performed on 36 selected flavonoid compounds against the COX-2 enzyme.
- * Binding affinities were calculated, and key interactions with active site residues were analyzed.
- * Molecular dynamics (MD) simulations using GROMACS assessed the stability of the COX-2-flavonoid complexes.
Main Results:
- * Cudraflavone A exhibited the highest binding affinity (-10.19 kcal/mol), exceeding that of Rofecoxib (-9.4 kcal/mol).
- * Key interactions, including hydrogen bonding and hydrophobic contacts, were observed with critical COX-2 residues (Tyr130, Glu465, Arg44).
- * MD simulations indicated that the COX-2-Cudraflavone A complex displayed enhanced structural stability, compactness, and reduced flexibility.
Conclusions:
- * Cudraflavone A is a highly promising candidate for selective COX-2 inhibition.
- * The study provides a strong rationale for developing Cudraflavone A as a therapeutic agent for cancer and inflammatory diseases.
- * Computational approaches are effective in identifying novel drug candidates from natural product libraries.
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