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Appl Biochem Biotechnol ; 196(3): 1316-1349, 2024 Mar.
Article in English | MEDLINE | ID: mdl-37392324

ABSTRACT

Cervical cancer is one of the main causes of cancer death in women globally, and its epidemiology is similar to that of a low-infectious venereal illness. Many sexual partners and early age at first intercourse have been demonstrated to have a significant influence on risk. TGF-ß1 is a multifunctional cytokine that is required for cervical carcinoma metastasis, tumor development, progression, and invasion. The TGF-ß1 signaling system plays a paradoxical function in cancer formation, suppressing early-stage tumor growth while increasing tumor progression and metastasis. Importantly, TGF-ß1 and TGF-ß receptor 1 (TGF-ßR1), two components of the TGF-ß signaling system, are substantially expressed in a range of cancers, including breast cancer, colon cancer, gastric cancer, and hepatocellular carcinoma. The current study aims to investigate possible inhibitors targeting TGF-ß1 using molecular docking and dynamic simulations. To target TGF-ß1, we used anti-cancer drugs and small molecules. MVD was utilized for virtual screening, and the highest scoring compound was then subjected to MD simulations using Schrodinger software package v2017-1 (Maestro v11.1) to identify the most favorable lead interactions against TGF-ß1. The Nilotinib compound has shown the least XP Gscore of -2.581 kcal/mol, 30ns MD simulations revealing that the Nilotinib- TGF-ß1 complex possesses the lowest energy of -77784.917 kcal/mol. Multiple parameters, including Root Mean Square Deviation, Root Mean Square Fluctuation, and Intermolecular Interactions, were used to analyze the simulation trajectory. Based on the results; we conclude that the ligand nilotinib appears to be a promising prospective TGF-ß1inhibitor for reducing TGF-ß1 expression ad halting cervical cancer progression.


Subject(s)
Transforming Growth Factor beta1 , Uterine Cervical Neoplasms , Female , Humans , Transforming Growth Factor beta1/metabolism , Uterine Cervical Neoplasms/drug therapy , Molecular Docking Simulation , Cell Line, Tumor , Prospective Studies , Early Detection of Cancer
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