ArticleApplied biochemistry and biotechnology2024
Virtual Screening, Molecular Docking, and Dynamic Simulations Revealed TGF-β1 Potential Inhibitors to Curtail Cervical Cancer Progression.
Article in Applied biochemistry and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 16 citations in OpenAlex.
- Computational theranostics strategy for pancreatic ductal adenocarcinoma.Molecular diversity · 2026Article
- Computational discovery of ATP-competitive GSK3β inhibitors using database-driven virtual screening and deep learning.Molecular diversity · 2026Article
- AI-driven peptide discovery for endometrial cancer: deep generative modeling and molecular simulation in the big data era.Journal of computer-aided molecular design · 2026Article
- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
- Evaluating TGF-β1 gene expression and promoter polymorphism in cervical cancer progression.Journal of molecular histology · 2025Article
- Multi-omics profiling reveals the role of 4-ethylbenzoic acid in promoting proliferation and invasion of cervical cancer.Frontiers in medicine · 2025Article
- Identification of novel therapeutic inhibitors against E6 and E7 oncogenes of HPV-16 associated with cervical cancer.PloS one · 2025Article
- Piperine's potential in treating polycystic ovarian syndrome explored through in-silico docking.Scientific reports · 2024Article
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8 authors at 2 institutions in 1 country.
Funding
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-β1 is a multifunctional cytokine that is required for cervical carcinoma metastasis, tumor development, progression, and invasion. The TGF-β1 signaling system plays a paradoxical function in cancer formation, suppressing early-stage tumor growth while increasing tumor progression and metastasis. Importantly, TGF-β1 and TGF-β receptor 1 (TGF-βR1), two components of the TGF-β 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-β1 using molecular docking and dynamic simulations. To target TGF-β1, 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-β1. The Nilotinib compound has shown the least XP Gscore of -2.581 kcal/mol, 30ns MD simulations revealing that the Nilotinib- TGF-β1 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-β1inhibitor for reducing TGF-β1 expression ad halting cervical cancer progression.
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