Systems pharmacology reveals the molecular mechanisms of nerolidol against polycystic ovary syndrome through integrated transcriptomic, network pharmacology and experimental validation.

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine and metabolic disorder marked by hyperandrogenism, ovulatory dysfunction, insulin resistance, chronic inflammation and oxidative stress, arising from dysregulation across several interconnected molecular pathways. Because its pathogenesis is multifactorial, therapies targeting diverse biological processes at once remain scarce. Nerolidol, a naturally occurring sesquiterpene alcohol with antioxidant, anti-inflammatory and cytoprotective properties, has an action against PCOS whose molecular basis remains unresolved. Transcriptomic differences associated with PCOS were examined using the Gene Expression Omnibus (GEO) dataset GSE34526. Exploratory differential-expression screening identified nominally altered probes using an unadjusted P < 0.05 and |log2FC| > 1; however, no individual probe remained significant after Benjamini-Hochberg correction at FDR < 0.05. Functional enrichment analysis was subsequently used to investigate biological processes and pathways represented by these exploratory transcriptional signals. Gene Ontology (GO) and KEGG enrichment were applied to pinpoint dysregulated biological processes and signalling pathways. Computational findings were tested in a letrozole-induced PCOS rat model treated with nerolidol, with efficacy judged from oestrous cyclicity, ovarian histopathology, reproductive hormone profiles, oxidative stress biomarkers, inflammatory mediators and metabolic parameters. Transcriptomic analysis showed marked enrichment of processes related to kinase regulation, insulin secretion, intrinsic apoptotic signalling, receptor-mediated signalling and the DNA damage response, while KEGG analysis pointed to pathways governing endocrine regulation, cell signalling and metabolic homeostasis. In animal experiments, nerolidol restored oestrous cyclicity, improved ovarian morphology, corrected endocrine disturbances, and reduced oxidative stress and PCOS-related pathology. These phenotypic effects were functionally concordant with several biological processes highlighted by the computational analyses. However, because the predicted signalling molecules and pathways were not directly measured in ovarian tissue following nerolidol treatment, the proposed molecular mechanisms remain hypotheses requiring targeted experimental validation.