Integrating Ayurgenomics and Network Pharmacology for Mechanistic Insights into Rice-Derived Phytochemicals in Breast Cancer Intervention

introduction: Breast cancer (BC) persists as the most frequently diagnosed malignancy among women globally, characterized by marked heterogeneity, resistance to monotherapeutic agents, and substantial systemic toxicity associated with current treatment modalities. The imperative to identify multitargeted, low-toxicity interventions has fueled interest in phytotherapeutics, particularly from ethnomedicinal sources. In this context, the present study investigates the anticancer potential of Oryza sativa-derived phytocompounds through a comprehensive in silico framework integrating network pharmacology, molecular docking, and molecular dynamics (MD) simulation. materials and methods: Thirty-one metabolites identified via GC–MS profiling was structurally retrieved and filtered for drug-likeness using Swiss ADME, yielding ten candidates with optimal ADME characteristics. These compounds were subjected to multi-platform target prediction (Swiss Target Prediction, Target Net, SuperPred, SEA), resulting in 627 unique protein targets. Concurrently, 1,749 BC-associated targets were curated from GeneCards, STRING, and CTD. Comparative mapping identified 98 overlapping targets, which were analyzed for protein–protein interaction and functionally clustered using STRING and MCODE. KEGG and WebGestalt enrichment pinpointed the PI3K-Akt, Ras, and HIF-1 signaling pathways as significantly overrepresented. Three targets, PIK3CA, ESR1, and CASP8 emerged as critical BC regulators and were prioritized for docking studies. results: Oleic acid demonstrated the highest binding affinity across all targets. Subsequent MD simulations of the PIK3CA–oleic acid complex revealed high structural stability, low RMSD fluctuations, and persistent intermolecular interactions, suggesting robust target engagement. discussion: Functional annotation of clustered proteins revealed enrichment in oncogenic processes such as oxidative stress response, kinase activity modulation, and hormone-mediated signaling. conclusion: Collectively, the study highlights the multitarget pharmacological potential of Oryza sativa-derived compounds, particularly oleic acid, in modulating BC-relevant molecular axes. Although the results are promising, the absence of experimental validation remains a limitation, necessitating further translational studies to substantiate clinical relevance and therapeutic viability.

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Journal
Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine
Published
2026-03-27
DOI
https://doi.org/10.2174/0118756921408910260218063402
Primary Topic
Computational Drug Discovery Methods
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article
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article

Integrating Ayurgenomics and Network Pharmacology for Mechanistic Insights into Rice-Derived Phytochemicals in Breast Cancer Intervention

Sweety Sharma, Chhaya Gadgoli, Mangirish Tendulkar
Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine
Computational Drug Discovery Methods
article

Integrating Ayurgenomics and Network Pharmacology for Mechanistic Insights into Rice-Derived Phytochemicals in Breast Cancer Intervention

Sweety Sharma, Chhaya Gadgoli, Mangirish Tendulkar
article en

Abstract

introduction: Breast cancer (BC) persists as the most frequently diagnosed malignancy among women globally, characterized by marked heterogeneity, resistance to monotherapeutic agents, and substantial systemic toxicity associated with current treatment modalities. The imperative to identify multitargeted, low-toxicity interventions has fueled interest in phytotherapeutics, particularly from ethnomedicinal sources. In this context, the present study investigates the anticancer potential of Oryza sativa-derived phytocompounds through a comprehensive in silico framework integrating network pharmacology, molecular docking, and molecular dynamics (MD) simulation. materials and methods: Thirty-one metabolites identified via GC–MS profiling was structurally retrieved and filtered for drug-likeness using Swiss ADME, yielding ten candidates with optimal ADME characteristics. These compounds were subjected to multi-platform target prediction (Swiss Target Prediction, Target Net, SuperPred, SEA), resulting in 627 unique protein targets. Concurrently, 1,749 BC-associated targets were curated from GeneCards, STRING, and CTD. Comparative mapping identified 98 overlapping targets, which were analyzed for protein–protein interaction and functionally clustered using STRING and MCODE. KEGG and WebGestalt enrichment pinpointed the PI3K-Akt, Ras, and HIF-1 signaling pathways as significantly overrepresented. Three targets, PIK3CA, ESR1, and CASP8 emerged as critical BC regulators and were prioritized for docking studies. results: Oleic acid demonstrated the highest binding affinity across all targets. Subsequent MD simulations of the PIK3CA–oleic acid complex revealed high structural stability, low RMSD fluctuations, and persistent intermolecular interactions, suggesting robust target engagement. discussion: Functional annotation of clustered proteins revealed enrichment in oncogenic processes such as oxidative stress response, kinase activity modulation, and hormone-mediated signaling. conclusion: Collectively, the study highlights the multitarget pharmacological potential of Oryza sativa-derived compounds, particularly oleic acid, in modulating BC-relevant molecular axes. Although the results are promising, the absence of experimental validation remains a limitation, necessitating further translational studies to substantiate clinical relevance and therapeutic viability.

Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicineVol. 23
Bharatiya Vidya Bhavan (IN), Institute of Bioinformatics (IN), Institute of Bioinformatics and Applied Biotechnology (IN)
Openalex Percentile: Top 2%
Computational Drug Discovery Methods
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