PHARMACEUTICALS · Published 2026-08-05 · DOI 10.3390/ph19081234
Poojhashri Jayagopal, Sandhiya Prabhakar, Abhinand Ponneri Adithavarman, Somdatta Yashwant Chaudhari
<b>Background</b>: Serous ovarian cancer (SOC) is the most aggressive subtype of epithelial ovarian cancer, frequently diagnosed at advanced stages with poor prognosis and chemotherapy resistance. Checkpoint kinase 1 (CHEK1), a key regulator of the DNA damage response, is overexpressed in ovarian cancer, making it a promising therapeutic target. No study has systematically evaluated natural compounds as CHEK1 inhibitors in SOC through an integrative transcriptomic and computational framework. <b>Methods</b>: A meta-analysis of three GEO datasets (GSE27651, GSE36668, GSE54388; n = 83) was performed using ImaGEO. DEGs were identified at |log<sub>2</sub>FC| ≥ 2 and FDR < 0.05. Pathway enrichment, PPI network analysis, virtual screening of 40 phytochemicals against CHEK1 (PDB: 9CE4), 100 ns MD simulations, and ADMET profiling were conducted using established bioinformatics and computational tools. <b>Results</b>: A total of 511 DEGs were identified, with significant dysregulation of apoptosis, DNA repair, and cell cycle pathways. CHEK1 emerged as the central hub gene. Baicalein exhibited the highest binding affinity (−9.334 kcal/mol), surpassing Prexasertib (−7.2 kcal/mol). MD simulations confirmed complex stability, and ADMET profiling demonstrated favorable drug-likeness with zero Lipinski violations. <b>Conclusions</b>: CHEK1 is established as a validated therapeutic target in SOC, and Baicalein is identified as a computationally superior natural lead compound, warranting experimental validation in ovarian cancer models.
Abstract from DOAJ. Public domain (CC0 1.0).
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Jayagopal, P., Prabhakar, S., Adithavarman, A., et al. (2026). Integrative Bioinformatics Identification of Baicalein as a Phytochemical Inhibitor of CHEK1 in Serous Ovarian Cancer: A Multi-Stage In Silico Drug Discovery Approach. PHARMACEUTICALS. https://doi.org/10.3390/ph19081234