Computer-aided drug discovery of a dual-target inhibitor for ovarian cancer: therapeutic intervention targeting CDK1/TTK signaling pathway and structural insights in the NCI-60

Sung-Ling Tang; Maryam Rachmawati Sumitra; Yu-Cheng Kuo; Han-Lin Hsu; Muhamad Ansar; Sheng-Liang Huang; Shih-Yu Lee; Hong-Jaan Wang; Bashir Lawal; Alexander T H Wu; Lung-Ching Chen; Hsu-Shan Huang

doi:10.1016/j.compbiomed.2025.110445

Computer-aided drug discovery of a dual-target inhibitor for ovarian cancer: therapeutic intervention targeting CDK1/TTK signaling pathway and structural insights in the NCI-60

Comput Biol Med. 2025 Jul:193:110445. doi: 10.1016/j.compbiomed.2025.110445. Epub 2025 May 29.

Authors

Affiliations

¹ School of Pharmacy, National Defense Medical Center, Taipei, 11490, Taiwan.
² PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan; Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan.
³ Department of Pharmacology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, 11031, Taiwan; School of Post-Baccalaureate Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung, 40604, Taiwan.
⁴ Graduate Institute of Clinical Medicine, Taipei Medical University, Taipei, 11031, Taiwan; Division of Pulmonary Medicine, Department of Internal Medicine, Wanfang Hospital, Taipei Medical University, Taipei, 11031, Taiwan.
⁵ Ph.D. Program in the Clinical Drug Development of Herbal Medicine, Taipei Medical University, Taipei, 110301, Taiwan.
⁶ Graduate Institute of Aerospace and Undersea Medicine, National Defense Medical Center, Taipei, 11490, Taiwan.
⁷ UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA.
⁸ Ph.D. Program of Translational Medicine, College of Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan.
⁹ Division of Cardiology, Department of Internal Medicine, Shin Kong Wu Ho-Su Memorial Hospital, Taipei, 11101, Taiwan.
¹⁰ School of Pharmacy, National Defense Medical Center, Taipei, 11490, Taiwan; PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan; Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan; Ph.D. Program in Biotechnology Research and Development, College of Pharmacy, Taipei Medical University, Taipei, 11031, Taiwan. Electronic address: huanghs99@tmu.edu.tw.

PMID: 40446543
DOI: 10.1016/j.compbiomed.2025.110445

Abstract

Ovarian cancer remains the third most prevalent and deadliest gynecologic malignancy worldwide, with most patients eventually developing resistance to platinum-based chemotherapy. This highlights a critical unmet need for innovative multitargeted therapies to address current treatment challenges. In this study, we identified 35 differentially expressed genes (DEGs) through integrated analysis of four GEO ovarian cancer datasets, with validation using TCGA data. Gene Ontology (GO) and KEGG enrichment analyses highlighted key tumor-associated pathways, and protein-protein interaction (PPI) network modeling prioritized CDK1 and TTK as high-value therapeutic targets. We evaluated the association between molecular genomic features and drug responses across the NCI-60 ovarian cancer cell line panel (IGROV1, OVCAR-3, OVCAR-4, OVCAR-5, OVCAR-8, NCI/ADR-RES, and SK-OV-3), using a series of salicylanilide-derived compounds and four FDA-approved drugs (cabozantinib, paclitaxel, rapamycin, and niclosamide) from the NCI Developmental Therapeutics Program (DTP). Among these, NSC765690 (MCC22) emerged as the most promising candidate. It demonstrated potent antiproliferative activity, high target selectivity, and strong binding affinity to both CDK1 and TTK. Multi-omics integration, combined with AI-driven network modeling, further elucidated NSC765690's mechanism of action and its relevance to ovarian cancer pathogenesis. Additionally, ADMET and pharmacokinetic profiling confirmed its favorable drug-like properties and low predicted toxicity. Collectively, these findings establish NSC765690 as a potent dual-target inhibitor and exemplify a rational, data-driven drug discovery pipeline for overcoming chemotherapy resistance in ovarian cancer.

Keywords: Dual-target small molecule inhibitor; Machine learning; Molecular docking; Molecular dynamics simulations; NCI-60 panel; Ovarian cancer.

MeSH terms

Antineoplastic Agents* / chemistry
Antineoplastic Agents* / pharmacology
CDC2 Protein Kinase* / antagonists & inhibitors
CDC2 Protein Kinase* / genetics
CDC2 Protein Kinase* / metabolism
Cell Cycle Proteins* / antagonists & inhibitors
Cell Cycle Proteins* / genetics
Cell Cycle Proteins* / metabolism
Cell Line, Tumor
Drug Discovery* / methods
Female
Humans
Ovarian Neoplasms* / drug therapy
Ovarian Neoplasms* / genetics
Ovarian Neoplasms* / metabolism
Protein Kinase Inhibitors* / chemistry
Protein Kinase Inhibitors* / pharmacology
Protein Serine-Threonine Kinases* / antagonists & inhibitors
Protein Serine-Threonine Kinases* / genetics
Protein Serine-Threonine Kinases* / metabolism
Protein-Tyrosine Kinases* / antagonists & inhibitors
Protein-Tyrosine Kinases* / metabolism
Signal Transduction* / drug effects

Substances

CDC2 Protein Kinase
CDK1 protein, human
TTK protein, human
Protein Serine-Threonine Kinases
Antineoplastic Agents
Cell Cycle Proteins
Protein Kinase Inhibitors
Protein-Tyrosine Kinases