靶向 FLT3 的抗肿瘤小分子抑制剂的虚拟筛选.

Objective: To discover novel FLT3 inhibitors from the ChEMBL database by using virtual screening technology, and provide a theoretical foundation for the development of small molecule inhibitors targeting FLT3. Methods: Approximately 2.4 million small molecules from the ChEMBL database were selected as the dataset. FLT3 protein was chosen as the target, and virtual screening was conducted via molecular docking. The binding affinity and stability of target compounds with FLT3 protein were investigated by using 200 ns of molecular dynamics simulation. Results: Five novel potential FLT3 inhibitors (ChEMBL ID: 5186572, 4845881, 2151842, 3642822, 3916042) not previously reported in the literature were successfully discovered by virtual screening. The docking scores (-10.93 to -12.58) and binding free energies (-82.06 to -88.49 kcal/mol) of these compounds were superior to the reference compound Gilteritinib (-8.73 and -65.38 kcal/mol). The results of molecular dynamics simulation have demonstrated a strong binding affinity of the target compounds with FLT3 protein, leading to the formation of stable complexes. Conclusion: Five novel potential FLT3 inhibitors with potential anti-tumor activity not previously reported were discovered by virtual screening technology. These findings provide an important theoretical foundation for the development of next-generation FLT3 inhibitors. [ABSTRACT FROM AUTHOR]