Multitarget-Directed Multiple Ligands in Anti-VEGF Resistant Glioblastoma Therapeutics: An in Silico Approach to Identify Potential Phytochemicals

Authors

  • Kesavan R. Arya Department of Computational Biology and Bioinformatics, University of Kerala, India https://orcid.org/0009-0004-5714-9524
  • Sasikumar J. Soumya Department of Computational Biology and Bioinformatics, University of Kerala, India
  • Anuroopa G. Nadh Department of Computational Biology and Bioinformatics, University of Kerala, India https://orcid.org/0000-0002-5231-6678
  • Thankamani R. Aswathy Department of Computational Biology and Bioinformatics, University of Kerala, India
  • Vijayalakshmi B. Department of Computational Biology and Bioinformatics, University of Kerala, India
  • Achuthsankar S. Nair Department of Computational Biology and Bioinformatics, University of Kerala, India
  • Oommen V. Oommen Department of Computational Biology and Bioinformatics, University of Kerala, India
  • Perumana R. Sudhakaran Department of Computational Biology and Bioinformatics, University of Kerala, India

DOI:

https://doi.org/10.47852/bonviewMEDIN52023816

Keywords:

glioblastoma, transcriptome data analysis, angiogenesis, anti-VEGF therapy, drug resistance, molecular docking, Medhya Rasayana

Abstract

Angiogenesis is an important process in tumor progression. Vascular endothelial growth factor (VEGF) is the key factor regulating angiogenesis, and hence, anti-VEGF therapy is considered a useful therapeutic approach in tumor conditions. However, the drug resistance and lack of efficacy of existing drugs limit the potential of such a therapeutic approach in certain cases, and the tumor growth will continue through alternative mechanisms. Glioblastoma (GBM) is one such type of tumor that shows resistance to anti-VEGF therapy. Previously, we identified the hub genes differentially expressed in anti-VEGF resistance in GBM. Medhya Rasayana, an Ayurvedic formulation, is used for the management of neurological disorders. In the present study, we used computational docking methods to identify the phytochemicals present in the medicinal plants of Medhya Rasayana, which can target the proteins expressed by the hub genes associated with anti-VEGF resistance. Network pharmacological analysis was also performed to identify the highly effective phytochemicals for a possible adjuvant therapy. Results showed that multiple phytochemicals of Glycirrhiza glabra Linn, Evolvulus alsinoides, and Celastrus paniculatus target the anti-VGEF resistant proteins in GBM. This indicates the multi-targeting property of phytocompounds of Medhya Rasayana plants, which may be considered for adjuvant therapy along with anti-VEGF therapy.

 

Received: 10 July 2024 | Revised: 11 October 2024 | Accepted: 6 January 2025

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

 

Data Availability Statement

The data that support this work are available upon reasonable request to the corresponding author.

 

Author Contribution Statement

Kesavan R. Arya: Methodology, Formal analysis, Investigation, Writing - original draft, Writing - review & editing, Visualization, Funding acquisition. Sasikumar J. Soumya: Methodology, Formal analysis, Investigation, Writing - original draft, Writing - review & editing,Visualization, Funding acquisition. Anuroopa G. Nadh: Formal analysis, Investigation, Funding acquisition. Thankamani R. Aswathy: Formal analysis, Investigation. Vijayalakshmi B.: Investigation. Achuthsankar S. Nair: Resources, Project administration. Oommen V. Oommen: Validation, Resources, Writing - review & editing, Project administration. Perumana R. Sudhakaran: Conceptualization, Methodology, Validation, Investigation, Resources, Writing - review & editing, Project administration, Funding acquisition.


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Published

2025-01-21

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Section

Research Articles

How to Cite

Multitarget-Directed Multiple Ligands in Anti-VEGF Resistant Glioblastoma Therapeutics: An in Silico Approach to Identify Potential Phytochemicals. (2025). Medinformatics, 2(1), 57–69. https://doi.org/10.47852/bonviewMEDIN52023816