Exploring the Protein-Protein Interactions and the Physiological Impact of Cannabinoids through Bioinformatics Analysis

Authors

  • Shyam Sundar Shaha Department of Biochemistry & Molecular Biology, Gono Bishwabidyalay, Savar, Dhaka-1344, Bangladesh
  • Akhi Akter Department of Biochemistry & Molecular Biology, Gono Bishwabidyalay, Savar, Dhaka-1344, Bangladesh
  • Ruku Akter Department of Biochemistry & Molecular Biology, Gono Bishwabidyalay, Savar, Dhaka-1344, Bangladesh
  • Mehadi Hasan Evan Department of Pharmacy, Pabna University of Science and Technology, Pabna-6600, Bangladesh
  • Mst Tasmina Akter Department of Biochemistry & Molecular Biology, Gono Bishwabidyalay, Savar, Dhaka-1344, Bangladesh
  • Md Rifat Ahmed Department of Biochemistry & Molecular Biology, Gono Bishwabidyalay, Savar, Dhaka-1344, Bangladesh
  • Jwel Sharma Department of Chemistry, National University, Gazipur-1704, Bangladesh
  • Mita Rani Das Department of Biochemistry & Molecular Biology, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh
  • Yousuf Al Mamun Department of Biochemistry & Molecular Biology, Primeasia University, Banani, Dhaka, Bangladesh
  • Md Abdullah Department of Pharmacy, Pabna University of Science and Technology, Pabna-6600, Bangladesh
  • Md Liton Miah Department of Biochemistry & Molecular Biology, Gono Bishwabidyalay, Savar, Dhaka-1344, Bangladesh
  • Elachi Akter Department of Textile Engineering, Southeast University, 251/A, Tejgaon Industrial Area, Dhaka – 1208, Bangladesh
  • Md Ramjan Sheikh Department of Biochemistry & Molecular Biology, Hajee Mohammad Danesh Science and Technology University, Dinajpur-5200, Bangladesh

DOI:

https://doi.org/10.3329/brc.v11i2.82643

Keywords:

PCI, PPI, Delta 9-tetrahydrocannabinol, Cannabidiol, and Functional analysis.

Abstract

Background: Weed smoking is a vastly unfavorable and perilous practice that can lead to various diseases, but it can also have beneficial effects on the human body. It comprises mainly two bioactive cannabinoids, delta 9-tetrahydrocannabinol and cannabidiol; they have both adverse and beneficial effects on human health. Objective: This study aims to identify the proteins interacting with delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) to predict their potential influences on the human body. Materials and Methods: We retrieved 200 proteins from the STITCH and STRING databases to analyze the interaction networks (PCI and PPI). We used OmicsBox to perform functional and pathway analysis of proteins associated with these compounds. Furthermore, the Cytoscape networking tool was utilized to identify crucial proteins and their significant pathways. We used Pyrx to assess potential direct interactions between THC and CBD with their associated proteins. Results: Functional annotation analysis revealed that THC and CBD interacted with various biological processes of human health, including signaling, anatomical structure development, cell differentiation, DNA binding, oxidoreductase activity, and cytosol activity. Fourteen key proteins were identified based on degree centrality, including ESR1, CREB1, INS, POMC, CNR1, JUN, NTRK2, CYP2B6, PPIG, CYP3A4, CYP1A2, CYP2E1, CYP2C9, and CYP2C19. These proteins play regulatory roles in various Reactome and KEGG pathways. Hypothetical direct interaction analysis showed that THC strongly interacted with pre-prodynorphin protein (-8.5 kcal/mol) and CBD connected with Cytochrome P450 1A1 protein (-8 kcal/mol). Conclusion: Therefore, this study contributes to understanding protein interactions and pathways, aiding in the development of drugs targeting CBD- or THC-related changes or associated diseases.

Bioresearch Commu. 11(2): 1835-1851, 2025 (July)

Author Biography

Shyam Sundar Shaha, Department of Biochemistry & Molecular Biology, Gono Bishwabidyalay, Savar, Dhaka-1344, Bangladesh



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Published

2025-07-01

How to Cite

Shaha, S. S., Akter, A., Akter, R., Evan, M. H., Akter, M. T., Ahmed, M. R., … Sheikh, M. R. (2025). Exploring the Protein-Protein Interactions and the Physiological Impact of Cannabinoids through Bioinformatics Analysis. Bioresearch Communications, 11(2), 1835–1851. https://doi.org/10.3329/brc.v11i2.82643

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Original Article