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  • Kocaeli Üniversitesi Sağlık Bilimleri Dergisi
  • Cilt: 11 Sayı: 1
  • Comprehensive In Silico Characterization of Phenolic Compounds: Structural Optimization, Molecular D...

Comprehensive In Silico Characterization of Phenolic Compounds: Structural Optimization, Molecular Docking, and ADMET Profiling of Potential Syncytin-2 Inhibitors for Glioblastoma and Lung Cancer Therapeutics

Authors : Aliye Demet Demirağ, Hatice Güngör
Pages : 18-29
Doi:10.30934/kusbed.1610257
View : 15 | Download : 30
Publication Date : 2025-03-21
Article Type : Research Paper
Abstract :Objective: To investigate the interactions between selected phenolic compounds (hesperidin, naringin, neohesperidin, kaempferol, apigenin, hesperetin, and nobiletin) and syncytin-2 protein, evaluating their potential as novel therapeutic agents for glioblastoma and lung cancer treatment. Methods: Molecular docking simulations were employed to analyze phenolic compound-syncytin-2 protein interactions. Comprehensive in silico ADMET analyses were conducted to assess pharmacokinetic properties and toxicity profiles of the compounds. Results: Hesperidin and neohesperidin exhibited the highest affinity to syncytin-2, with binding affinities of -10.5 kcal/mol and -10.0 kcal/mol, respectively. Molecular-level analyses demonstrated that hesperidin forms critical hydrogen bonds and hydrophobic interactions with Isoleucine 371, Alanine 372, and Leucine 309 amino acid residues. ADMET analyses revealed that these two compounds exhibit low toxicity potential and optimal pharmacokinetic profiles. Conclusion: This research provides evidence that phenolic compounds may serve as inhibitors of syncytin-2 in the treatment of glioblastoma and lung cancer. The identified molecular interactions and promising ADMET profiles support the need for further investigation of these compounds. Future studies should focus on optimizing phenolic compound-based inhibitors, conducting preclinical and clinical evaluations, and assessing their potential therapeutic effects within the tumor microenvironment.
Keywords : Glioblastoma multiforme, lung cancer, syncytin-2, phenolic compounds, molecular docking, ADMET analysis

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