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Structure-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation of VEGF inhibitors for the clinical treatment of Ovarian Cancer

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Abstract

Vascular endothelial growth factor (VEGF) and its receptor play an important role both in physiologic and pathologic angiogenesis, which is identified in ovarian cancer progression and metastasis development. The aim of the present investigation is to identify a potential vascular endothelial growth factor inhibitor which is playing a crucial role in stimulating the immunosuppressive microenvironment in tumor cells of the ovary and to examine the effectiveness of the identified inhibitor for the treatment of ovarian cancer using various in silico approaches. Twelve established VEGF inhibitors were collected from various literatures. The compound AEE788 displays great affinity towards the target protein as a result of docking study. AEE788 was further used for structure-based virtual screening in order to obtain a more structurally similar compound with high affinity. Among the 80 virtual screened compounds, CID 88265020 explicates much better affinity than the established compound AEE788. Based on molecular dynamics simulation, pharmacophore and comparative toxicity analysis of both the best established compound and the best virtual screened compound displayed a trivial variation in associated properties. The virtual screened compound CID 88265020 has a high affinity with the lowest re-rank score and holds a huge potential to inhibit the VGFR and can be implemented for prospective future investigations in ovarian cancer.

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Funding

This work was supported by the Taif University Researchers Supporting Program (Project number: TURSP-2020/151), Taif University, Saudi Arabia.

The authors are grateful to the Deanship of Scientific Research, King Saud University, for funding through the Vice Deanship of Scientific Research Chairs.

SKS thank Alagappa University, Department of Biotechnology (DBT), New Delhi (No. BT/PR8138/BID/7/458/2013, dated 23rd May 2013), DST-PURSE 2nd Phase Programme Order No. SR/PURSE Phase 2/38 (G dated 21.02.2017 and FIST (SR/FST/LSI—667/2016), MHRD RUSA 1.0 and RUSA 2.0 for providing the financial assistance. UP gratefully acknowledge the Indian Council of Medical Research (ISRM/11/(19)/2017, dated 09.08.2018).

SKS thankfully acknowledges the Tamil Nadu State Council for Higher Education (TANSCHE) for the research grant (Au/S.o. (P&D): TANSCHE Projects: 117/2021).

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Authors and Affiliations

  1. In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore, 452010, Madhya Pradesh, India

    Sourav Mukherjee, Manasi Yadav, Anushka Bhrdwaj, Ravina Khandelwal, Leena Prajapati, Aravind Panicker, Aashish Chaudhary & Anuraj Nayarisseri

  2. Key Laboratory of Chemical Biology (Ministry of Education), Department of Pharmaceutics, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, 44 Cultural West Road, Jinan, Shandong Province, 250012, People’s Republic of China

    Mohnad Abdalla

  3. Department of Zoology, Nizam College, Osmania University, Hyderabad, 500001, Telangana, India

    Maddala Madhavi

  4. Department of Human Anatomy, College of Medicine, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia

    Ashraf Albrakati

  5. Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia

    Tajamul Hussain

  6. Research Chair for Biomedical Applications of Nanomaterials, Biochemistry Department, College of Science, King Saud University, Riyadh, Saudi Arabia

    Tajamul Hussain & Anuraj Nayarisseri

  7. Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd, Mahalakshmi Nagar, Indore, 452010, Madhya Pradesh, India

    Anuraj Nayarisseri

  8. Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630 003, Tamil Nadu, India

    Sanjeev Kumar Singh

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  1. Sourav Mukherjee
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Contributions

SM contributed equally to this work with MA. SM and MA were involved in molecular docking, molecular dynamics simulation, and writing — review and editing. LP, AP, AC, and MM contributed towards inhibitor collection, data curation, formal analysis, validation, and visualization. AB was involved in molecular dynamics simulation. MY, RK, AAB, and TH were involved in molecular docking, ADMET analysis, R programming analysis, and writing — review and editing. AN, AAB, TH, and SKS contributed in investigation, supervision, and writing — review and editing.

Corresponding authors

Correspondence to Anuraj Nayarisseri or Sanjeev Kumar Singh.

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Sourav Mukherjee and Mohnad Abdalla have contributed equally to this work.

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Mukherjee, S., Abdalla, M., Yadav, M. et al. Structure-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation of VEGF inhibitors for the clinical treatment of Ovarian Cancer. J Mol Model 28, 100 (2022). https://doi.org/10.1007/s00894-022-05081-3

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