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Indian Journal of Pharmaceutical Education and ResearchNOW IN
Article

Network Pharmacology-Based Modeling of Phytocompounds in a Traditional Siddha Formulation-Kabasura kudineer with Special Reference to SARS-CoV-2

Krishna Kant Gupta1★, Yatindrapravanan Narasimhan1★, Shashank Ravichandran1★, Brindha Pemaiah2★, Davidraj Chellappan2★, Ragothaman Madhava Rao Yennamalli1★, Sriram Sridharan2★★ Corresponding author

  1. 1Department of Bioinformatics, School of Chemical and Biotechnology, SASTRA (Deemed to be University), Thanjavur, Tamil Nadu, INDIA.
  2. 2Centre for Advanced Research in Indian System of Medicine (CARISM), School of Chemical and Biotechnology, SASTRA (Deemed to be University), Thanjavur, Tamil Nadu, INDIA.

CORRESPONDENCE

Krishna Kant Gupta

Dr. Ragothaman Madhava Rao YennamalliDepartment of Bioinformatics, School of Chemical and Biotechnology, SASTRA Deemed to be University, Thanjavur, Tamil Nadu, INDIA.

ragothaman@scbt.sastra.edu

Received: 18-02-2024; Revised: 05-08-2024; Accepted: 29-01-2025.

Volume 59, Issue 2 · pp. 682–694 · PUBLISHED Apr-Jun 2025 · DOI: 10.5530/ijper.20256024

View on IJPER original site ↗

ABSTRACT

Background Kabasurak kudineer (Kk), a traditional Siddha formulation containing 15 plant-based ingredients has been prescribed in Siddha medicine for the management and treatment of flu-like symptoms. Currently, the Ministry of AYUSH, Government of India has been prescribing Kk as a possible preventive and prophylactic formulation against COVID-19. Objectives: The present study focuses on computational methods and aims to identify host targets in different pathways where the phytocompounds of Kk possibly interact. Materials and Methods Using the curated list of phytocompounds from 15 plants obtained from existing literature, each compound was searched against the Pubchem database and downloaded using which probable host targets were predicted in Swiss Target Prediction and Binding database. Probability scores of 0.5 and above was selected as high-confidence targets and a score of less than 0.5 as low-confidence targets. Results We constructed a network of compounds and their possible interacting targets and identified three pathways, namely Phosphatidylinositol 3-Kinase (P13K/AKT), Repressor Activator Protein 1 (Rap1) and Mitogen Activated Protein Kinase (MAPK) pathways that the phytocompounds possibly modulate. Additionally, we performed molecular docking simulations for the phytocompounds with target’s 3D structure to map the molecular interaction and ascertain their role in antiviral treatment, where we found ellagic acid as the best binder to the targets of these three pathways. Conclusion Using a network pharmacology approach this study demonstrated that Kk can modulate three important molecular pathways (P13K/AKT, Rap1 and MAPK) associated with COVID-19 and this could be due to the effect of the phyto ingredient ellagic acid.

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    Gupta, K. K., Narasimhan, Y., Ravichandran, S., Pemaiah, B., Chellappan, D., Yennamalli, R. M. R., & Sridharan, S. (2025). Network Pharmacology-Based Modeling of Phytocompounds in a Traditional Siddha Formulation-Kabasura kudineer with Special Reference to SARS-CoV-2. Indian Journal of Pharmaceutical Education and Research, 59(2), 682–694. https://doi.org/10.5530/ijper.20256024