Research Article

Computational Investigation of the Interaction of Large-scale Plant and Animal-Derived Natural Secondary Metabolites with FOXM1

Volume: 4 Number: 3 September 30, 2025
TR EN

Computational Investigation of the Interaction of Large-scale Plant and Animal-Derived Natural Secondary Metabolites with FOXM1

Abstract

FOXM1, a transcription factor from the Forkhead box family, serves as a crucial proto-oncogene that plays a role in cancer advancement, spread to distant sites, and resistance to chemotherapy across various human malignancies. The development of selective and therapeutically efficient FOXM1 inhibitors remains a significant challenge in the field. This study employed a multi-step computational approach to identify novel small-molecule compounds that target the DNA-binding domain (DBD) of FOXM1. A structure-guided virtual screening process was conducted using an extensive chemical compound database, evaluated against the crystallographic structure of FOXM1’s DNA-binding domain (PDB ID: 3G73). The top-ranking compounds underwent preliminary 10-nanosecond evaluations, subsequently followed by comprehensive 100-nanosecond molecular dynamics (MD) simulations. The binding affinities of the most thermodynamically stable protein-ligand complexes were determined through MM/GBSA calculations. The preliminary computational screening revealed 21 compounds that exhibited docking scores superior to -9.1 kcal/mol. Following 10 ns MD simulations, five compounds were selected, and 100 ns MD simulations confirmed the stable binding of these two compounds (comp_105546, comp_112458). MM/GBSA calculations identified comp_112458 as the most potent binder (-36.25±3.5 kcal/mol). This study successfully identified novel chemical scaffolds with high predicted affinity and stable binding modes against FOXM1, providing a strong foundation for the development of targeted anticancer agents. These promising computational results require validation through in vitro and in vivo studies.

Keywords

Cancer therapy , FOXM1 , MM/GBSA , Molecular dynamics , Virtual screening

References

  1. Raghuwanshi S, Gartel AL. Small-molecule inhibitors targeting FOXM1: Current challenges and future perspectives in cancer treatments. Biochim Biophys Acta Rev Cancer. 2023;1878(6):189015.
  2. Raghuwanshi S, Zhang X, Arbieva Z, et al. Novel FOXM1 inhibitor STL001 sensitizes human cancers to a broad-spectrum of cancer therapies. Cell Death Discov. 2024;10(1):211.
  3. Merjaneh N, Hajjar M, Lan YW, Kalinichenko VV, Kalin TV. The promise of combination therapies with FOXM1 inhibitors for cancer treatment. Cancers (Basel). 2024;16(4):756.
  4. Noor F, Junaid M, Almalki AH, Almaghrabi M, Ghazanfar S, Tahir ul Qamar M. Deep learning pipeline for accelerating virtual screening in drug discovery. Sci Rep. 2024;14(1):28321.
  5. Zhou G, Rusnac DV, Park H, et al. An artificial intelligence accelerated virtual screening platform for drug discovery. Nat Commun. 2024;15(1):7761.
  6. Naithani U, Guleria V. Integrative computational approaches for discovery and evaluation of lead compound for drug design. Front Drug Discov. 2024;4:1362456.
  7. busharkh KAN, Comert Onder F, Çınar V, Hamurcu Z, Ozpolat B, Ay M. A drug repurposing study identifies novel FOXM1 inhibitors with in vitro activity against breast cancer cells. Med Oncol. 2024;41(8):188.
  8. Littler DR, Alvarez-Fernández M, Stein A, et al. Structure of the FoxM1 DNA-recognition domain bound to a promoter sequence. Nucleic Acids Res. 2010;38(13):4527-4538.
  9. Lasham J, Djurabekova A, Zickermann V, Vonck J, Sharma V. Role of protonation states in the stability of molecular dynamics simulations of high-resolution membrane protein structures. J Phys Chem B. 2024;128(10):2304-2316.
  10. Wishart DS, Guo AC, Oler E, et al. HMDB 5.0: The human metabolome database for 2022. Nucleic Acids Res. 2022;50(D1):D622-D631.
APA
Düzgün, Z., Demırtaş Korkmaz, F., & Alp, E. (2025). Computational Investigation of the Interaction of Large-scale Plant and Animal-Derived Natural Secondary Metabolites with FOXM1. Farabi Tıp Dergisi, 4(3), 63-72. https://doi.org/10.59518/farabimedj.1745493