Integrative transcriptomics and structure-based screening identifies Phyllanthus amarus phytocompounds as potential...

Area of Science:

• Oncology
• Computational Biology
• Pharmacognosy

Background:

• Ovarian cancer is a leading cause of gynecological cancer deaths due to late diagnosis and molecular complexity.
• Identifying oncogenic drivers and new therapeutic strategies is crucial for improving patient outcomes.

Purpose of the Study:

• To identify key molecular targets in ovarian cancer using computational methods.
• To screen for potential anticancer compounds from natural sources.

Main Methods:

• Integrative computational pipeline analyzing transcriptomic data (GSE14407, GSE18520, GSE26712).
• Identification and prioritization of WNT5A as a target via gene expression analysis.
• GC-MS profiling of Phyllanthus amarus for compound identification.
• Virtual screening, molecular docking, ADME/toxicity prediction, molecular dynamics simulations, and FEP calculations.

Main Results:

• WNT5A identified as a key regulator in tumor progression, metastasis, and chemoresistance.
• Enrichment analysis revealed WNT5A's role in mesenchymal development and signaling pathways.
• 48 compounds from P. amarus were identified, with several showing favorable interactions with WNT5A via molecular docking.
• Molecular dynamics and FEP calculations confirmed the stability and binding affinity of selected compounds to WNT5A.

Conclusions:

• The study highlights WNT5A as a promising therapeutic target for ovarian cancer.
• Bioactive compounds from P. amarus demonstrate potential as novel anticancer agents.
• These in silico findings provide a foundation for experimental validation and drug development.