In silico screening of potential FGF2 inhibitors for cancer therapy

Cancer remains one of the leading causes of death worldwide and is characterized by the dysregulation of multiple signalling pathways involved in cell survival, proliferation, differentiation, and migration. Among these, fibroblast growth factor 2 (FGF2) serves as a key regulator that promotes tumor growth and metastasis and is frequently upregulated in several cancers, including glioblastoma, gastric and breast cancer, acute myeloid leukemia, nasopharyngeal carcinoma, and non-small cell lung cancer. Many cancers, such as glioblastoma where FGF2 plays a key role, remain incurable. Cancer's heterogeneity limits treatment efficacy, underscoring the urgent need to develop diverse and more effective therapeutic options. In the present study, structure-based screening was performed with target protein FGF2 using the LEA3D database, where eight FDA-approved drugs, Elbasvir (1), Velpatasvir (2), Daclatasvir (3), Ritonavir (4), Paliperidone Palmitate (5), Saralasin (6), Nystatin (7), and Cobicistat (8), were identified as potential therapeutics capable of interfering with the binding of FGF2 to its receptor (FGFR), thereby blocking downstream oncogenic signalling pathways. This was followed by molecular docking or redocking and molecular dynamics (MD) simulation studies of the identified potential 8 drugs against the crystal structure of FGF2 (PDB ID: 1BFG). Molecular docking study showed Elbasvir (1) to exhibit the strongest binding affinity (-8.1 kcal/mol), followed by Velpatasvir (2) (-7.6 kcal/mol), Daclatasvir (3) (-7.5 kcal/mol), Ritonavir (4) (-6.2 kcal/mol), Paliperidone Palmitate (5) (-5.9 kcal/mol), Saralasin (6) (-5.4 kcal/mol), Nystatin (8) (-5.2 kcal/mol), and Cobicistat (-5.1 kcal/mol). MD simulations further validated the stability of binding between the identified drugs and FGF2, revealing that compounds 1-6 exhibited the most sustained and stable interactions, thereby supporting their potential as effective FGF2 inhibitors. Compound 8 exhibited milder fluctuations compared to compound 7 and demonstrated stable binding during the final phase of the 100 ns MD simulation, beginning around 90 ns. In contrast, compound 7 showed the least stability throughout the simulation. Overall, the study provides mechanistic insights into the molecular interactions between FGF2 and these candidate drugs, highlighting the promising potential of compounds 1-6 and 8 for subsequent in vitro validation in cancer therapeutics.

The online version contains supplementary material available at 10.1007/s40203-025-00495-2.