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◆ Frontiers in Bioinformatics2026-04-08· In silico

Transcriptomics-driven identification of CDK1 as a central oncogenic driver in TNBC: an in silico structural modeling and MD simulation approach

Uma Chaudhary, S. Kumar, Magesh Ramaswamy, Mythili Asaithambi

原始摘要(英文原文)· Original abstract
Introduction: Triple-negative breast cancer (TNBC) is an aggressive subtype that lacks ER, PR, and HER2 receptors, which limits the availability of targeted therapies. In this study, we analyzed CDK1 as a potential molecular target and evaluated natural compounds that might inhibit its activity. Methods: Transcriptomic comparison revealed 85 commonly upregulated mRNAs in TNBC, and functional enrichment combined with PPI network analysis indicated CDK1 as a major hub gene. To search for potential inhibitors, we screened an anticancer-focused phytochemical library from the SuperNatural 3.0 database using molecular docking followed by ADMET assessment. Results: Among the screened molecules, CID17584963 showed the strongest binding energy (-8.09 kcal/mol) and displayed pharmacokinetic properties comparable to or better than those of paclitaxel. Long-timescale (500 ns) molecular dynamics simulations further supported the stability of the CDK1-CID17584963 complex, with root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration, solvent-accessible surface area (SASA), hydrogen-bond profiles, and principal component analysis (PCA) all indicating consistent interactions throughout the trajectory. Discussion: Taken together, these findings indicate that CID17584963 interacts with CDK1 more stably than the reference drug and may serve as a promising natural compound for further studies in TNBC therapy.
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