Network pharmacology-based anti-obesity activity of Gavedhuka (a millet): In silico study

Abstract BACKGROUND: Millet is a small-seeded crop widely used in Ayurveda for maintaining health; it has a significant effect on the economic impacts in developing countries. In Ayurveda, Gavedhuka ( Coix lacryma-jobi L.), a type of millet, is described for its anti-obesity activity. The prevalence of obesity has been increasing across the globe in past few decades. With increase in prevalence, mortality risks among obese persons have also been increasing. The objective of this study was to explore the activity of Gavedhuka ( C. lacryma-jobi L.) in obesity using network pharmacology. METHODS: Bioactive components present in Gavedhuka ( C. lacryma-jobi L.) were retrieved from the Indian Medicinal Plants, Phytochemistry, and Therapeutics databases. Absorption, distribution, metabolism, and excretion (ADME) study and target prediction of bioactive components was assessed with online software tools (SwissADME and SwissTargetPrediction tool). The targets of obesity were retrieved from the GeneCards database. The common targets of obesity between targets retrieved from GeneCards database and targets obtained from bioactive components were screened. The herb–bioactive–target network was constructed and visualized by software (Cytoscape 3.9.1). Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the common targets for activity of Gavedhuka ( C. lacryma-jobi L.) in obesity. RESULTS: A total of 24 bioactive components were obtained from Gavedhuka ( C. lacryma-jobi L.), out of which 11 bioactives qualified for the ADME study and nine bioactive-related targets were collected from these ADME-qualified bioactive. After removal of duplicates targets, a total of seven targets were finalized, and all seven targets were found common between targets of obesity retrieved from GeneCards. CONCLUSION: Palmitic acid was the top bioactive linked to more targets, while peroxisome proliferator-activated receptor delta and peroxisome proliferator-activated receptor alpha were the top crucial targets of Gavedhuka ( C. lacryma-jobi L.) for its activity in obesity. The KEGG pathway enrichment indicated that the activities of Gavedhuka ( C. lacryma-jobi L.) in obesity are primarily connected to the peroxisome proliferator-activated receptor signaling pathway. These observations may open new thoughts for future investigations into the mechanisms behind the activity of Gavedhuka ( C. lacryma-jobi L.) in other diseases also.

Institutions

Publication Details

Journal
Journal of Drug Research in Ayurvedic Sciences
Published
2024-11-01
DOI
https://doi.org/10.4103/jdras.jdras_94_23
Citations
1
Primary Topic
Microbial Metabolism and Applications
Type
article
Field-Weighted Citation Impact
0.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Network pharmacology-based anti-obesity activity of Gavedhuka (a millet): In silico study

1 citations
Journal of Drug Research in Ayurvedic Sciences
Microbial Metabolism and Applications
0.39
article

Network pharmacology-based anti-obesity activity of Gavedhuka (a millet): In silico study

article en
1 citations

Abstract

Abstract BACKGROUND: Millet is a small-seeded crop widely used in Ayurveda for maintaining health; it has a significant effect on the economic impacts in developing countries. In Ayurveda, Gavedhuka ( Coix lacryma-jobi L.), a type of millet, is described for its anti-obesity activity. The prevalence of obesity has been increasing across the globe in past few decades. With increase in prevalence, mortality risks among obese persons have also been increasing. The objective of this study was to explore the activity of Gavedhuka ( C. lacryma-jobi L.) in obesity using network pharmacology. METHODS: Bioactive components present in Gavedhuka ( C. lacryma-jobi L.) were retrieved from the Indian Medicinal Plants, Phytochemistry, and Therapeutics databases. Absorption, distribution, metabolism, and excretion (ADME) study and target prediction of bioactive components was assessed with online software tools (SwissADME and SwissTargetPrediction tool). The targets of obesity were retrieved from the GeneCards database. The common targets of obesity between targets retrieved from GeneCards database and targets obtained from bioactive components were screened. The herb–bioactive–target network was constructed and visualized by software (Cytoscape 3.9.1). Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the common targets for activity of Gavedhuka ( C. lacryma-jobi L.) in obesity. RESULTS: A total of 24 bioactive components were obtained from Gavedhuka ( C. lacryma-jobi L.), out of which 11 bioactives qualified for the ADME study and nine bioactive-related targets were collected from these ADME-qualified bioactive. After removal of duplicates targets, a total of seven targets were finalized, and all seven targets were found common between targets of obesity retrieved from GeneCards. CONCLUSION: Palmitic acid was the top bioactive linked to more targets, while peroxisome proliferator-activated receptor delta and peroxisome proliferator-activated receptor alpha were the top crucial targets of Gavedhuka ( C. lacryma-jobi L.) for its activity in obesity. The KEGG pathway enrichment indicated that the activities of Gavedhuka ( C. lacryma-jobi L.) in obesity are primarily connected to the peroxisome proliferator-activated receptor signaling pathway. These observations may open new thoughts for future investigations into the mechanisms behind the activity of Gavedhuka ( C. lacryma-jobi L.) in other diseases also.

Journal of Drug Research in Ayurvedic SciencesVol. 9(6)
Government of Uttar Pradesh (IN), Ministry of AYUSH (IN)
Partnerships for the goals
Openalex Percentile: Top 31%
Microbial Metabolism and Applications
0.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.