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Virtual Screening, Molecular Docking, and Dynamic Simulations Revealed TGF-β1 Potential Inhibitors to Curtail Cervical Cancer Progression

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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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Data Availability

Data supporting the productivity of this investigation are available from the corresponding author upon request.

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Acknowledgements

Thankful to the Department of Genetics & Biotechnology, Osmania University and Department of Bioinformatics, SVIMS University for providing the Bioinformatics/software facilities.

Funding

This study was supported by grants of Prof. Smita C. Pawar received from the Science and Engineering Research Board(SERB), Govt. of India, reference Nos. SB/EMEQ-471/2014and EEQ/2019/000569 dt 06-Jan-2020, and the fellowship was provided by CSIR-UGC to Pavan Kumar Poleboyina & Akbar Pasha, ICMR to Shivaji Bhanothu & Sneha Malleswari Poleboyina. The facilities were partially provided by DSTPURSE-II.

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  1. Department of Genetics & Biotechnology, University College of Science, Osmania University, Hyderabad, Telangana, 500007, India

    Pavan Kumar Poleboyina, Akbar Pasha, Doneti Ravinder, Shivaji Bhanothu, Sneha Malleswari Poleboyina & Smita C. Pawar

  2. Department of Bioinformatics, SVIMS University, Tirupati, Andhra Pradesh, 517 507, India

    Umakanth Naik & Umamaheshwari Amineni

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  1. Pavan Kumar Poleboyina
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  2. Umakanth Naik
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  3. Akbar Pasha
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  4. Doneti Ravinder
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  5. Shivaji Bhanothu
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  6. Sneha Malleswari Poleboyina
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  7. Umamaheshwari Amineni
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  8. Smita C. Pawar
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Contributions

Smita C Pawar & Pavan Kumar Poleboyina conceptualized, designed interpreted data, and edited the manuscript; Pavan Kumar Poleboyina, UmaKanth Naik, UmaMaheshwari Amineni, Akbar Pasha, Doneti Ravinder, Shivaji Bhanothu, Sneha Malleswari Poleboyina designed and conducted the study. All authors have approved the manuscript in its current form.

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Correspondence to Smita C. Pawar.

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Poleboyina, P.K., Naik, U., Pasha, A. et al. Virtual Screening, Molecular Docking, and Dynamic Simulations Revealed TGF-β1 Potential Inhibitors to Curtail Cervical Cancer Progression. Appl Biochem Biotechnol 196, 1316–1349 (2024). https://doi.org/10.1007/s12010-023-04608-5

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