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. 2024 Sep;82(3):2625-2650.
doi: 10.1007/s12013-024-01375-w. Epub 2024 Jul 3.

Molecular Mechanism of Cynodon dactylon Phytosterols Targeting MAPK3 and PARP1 to Combat Epithelial Ovarian Cancer: A Multifaceted Computational Approach

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Molecular Mechanism of Cynodon dactylon Phytosterols Targeting MAPK3 and PARP1 to Combat Epithelial Ovarian Cancer: A Multifaceted Computational Approach

Acharya Balkrishna et al. Cell Biochem Biophys. 2024 Sep.

Abstract

Epithelial Ovarian Cancer (EOC) presents a global health concern, necessitating the development of innovative therapeutic strategies to combat its impact. This study was employed to investigate the unexplored therapeutic efficacy of Cynodon dactylon phytochemicals against EOC using a multifaceted computational approach. A total of 19 out of 89 rigorously curated phytochemicals were assessed as potential drug targets via ADMET profiling, while protein-protein interaction analysis scrutinized the top 20 hub genes among 264 disease targets, revealing their involvement in cancer-related pathways and underscoring their significance in EOC pathogenesis. In molecular docking, Stigmasterol acetate showed the highest binding affinity (-10.9 kcal/mol) with Poly [ADP-ribose] polymerase-1 (PDB: 1UK1), while Arundoin and Beta-Sitosterol exhibited strong affinities (-10.4 kcal/mol and -10.1 kcal/mol, respectively); additionally, Beta-Sitosterol interacting with Mitogen-activated protein kinase 3 (PDB: 4QTB) showed a binding affinity of -10.1 kcal/mol, forming 2 hydrogen bonds and a total of 10 bonds with 10 residues. Molecular dynamics simulations exhibited the significant structural stability of the Beta-Sitosterol-4QTB complex with superior binding free energy (-36.61 kcal/mol) among the three complexes. This study identified C. dactylon phytosterols, particularly Beta-Sitosterol, as effective in targeting MAPK3 and PARP1 to combat EOC, laying the groundwork for further experimental validation and drug development efforts.

Keywords: Cynodon dactylon; ADMET; Epithelial Ovarian Cancer; MD Simulation; Molecular Docking; Network Pharmacology.

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