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Network pharmacological evaluation for identifying novel drug-like molecules from ginger (Zingiber officinale Rosc.) against multiple disease targets, a computational biotechnology approach

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Abstract

Ginger (Zingiber officinale Rosc.) is a popular spice used globally in ethnic cuisines and witnessed its extensive use in traditional medicine. In this study, we identified 12 phytochemicals from the ginger rhizome extract (hexane) through GC/MS analysis. After evaluating drug-likeliness, these phytochemicals were docked with 16 target proteins in silico, and docking scores were compared with their respective control drugs. Furthermore, multivariate statistical analysis (principal component analysis-PCA) was performed, and three different chemical clusters were identified. Pharmacophore analysis further identified common functional descriptors in the compounds under study. Finally, we developed a unique three-level network taking phytochemicals, target proteins and associated diseases based on the optimum docking scores. Overall, Oleic acid, Palmitic acid and Shogaol showed the highest coverage to the target proteins (12, 10 and 9 targets, respectively) and Oleic Acid scored the highest (5956) in PatchDock when docked against Peroxisome proliferator-activated receptor gamma (PDB id 1KNU, UniProt id P37231). This work provided significant insight into developing the protocol for rapid identification of potential drug likeliness of the identified phytochemicals.

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Authors and Affiliations

  1. Department of Life Sciences, CHRIST (Deemed to be University), Bangalore Central Campus, Bangalore, India

    Anish Nag

  2. School of Biological and Environmental Sciences, Shoolini University, Solan, India

    Ritesh Banerjee

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  1. Anish Nag
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  2. Ritesh Banerjee
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Nag, A., Banerjee, R. Network pharmacological evaluation for identifying novel drug-like molecules from ginger (Zingiber officinale Rosc.) against multiple disease targets, a computational biotechnology approach. Netw Model Anal Health Inform Bioinforma 10, 55 (2021). https://doi.org/10.1007/s13721-021-00330-6

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  • DOI: https://doi.org/10.1007/s13721-021-00330-6

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