FLT3 mutations, observed in approximately 30–35% of Acute Myeloid Leukemia (AML) cases, drive leukemic proliferation and survival pathways, presenting a significant challenge in clinical management. To address this therapeutic need, we employed a comprehensive computational approach integrating pharmacophore screening, molecular docking, ADMET analysis, and molecular dynamics simulations to identify potent inhibitors targeting FLT3. Utilizing ligand-based pharmacophore models generated from experimentally proven FLT3 inhibitors from BindingDB, we screened over 400,000 natural compounds from the COCONUT database. Hits identified through pharmacophore screening underwent further evaluation via Lipinski and Golden triangle criteria to ensure drug-like properties. Molecular docking against the FLT3 receptor, combined with ADMET analyses, facilitated the prioritization of lead compounds. Subsequently, three promising candidates were subjected to molecular dynamics simulations to assess binding stability. Our findings reveal three top-performing compounds, demonstrating robust and stable binding affinity and favorable ADMET characteristics. These compounds hold promise as potential scaffolds or leads for developing novel FLT3 inhibitors in AML therapy.
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