Identifying novel therapeutic inhibitors to target FMS-like tyrosine kinase-3 (FLT3) against acute myeloid leukemia: a molecular docking, molecular dynamics, and DFT study

Abstract

Around 30% of acute myeloid leukemia (AML) patients have triggering mutations in Feline McDonough Sarcoma (FMS)-like tyrosine kinase 3 (FLT3), which has been suggested as a possible therapeutic candidate for AML therapy. Many tyrosine kinase inhibitors are available and have a wide variety of applications in the treatment of cancer by inhibiting subsequent steps of cell proliferation. Therefore, our study aims to identify effective antileukemic agents against FLT3 gene. Initially, well-known antileukemic drug candidates have been chosen to generate a structure-based pharmacophore model to assist the virtual screening of 217,77,093 compounds from the Zinc database. The final hits compounds were retrieved and evaluated by docking against the target protein, where the top four compounds have been selected for the analysis of ADMET. Based on the density functional theory (DFT), the geometry optimization, frontier molecular orbital (FMO), HOMO-LUMO, and global reactivity descriptor values have been evaluated that confirming a satisfactory profile and reactivity order for the selected candidates. In comparison to control compounds, the docking results revealed that the four compounds had substantial binding energies (-11.1 to −11.5 kcal/mol) with FLT3. The physicochemical and ADMET (adsorption, distribution, metabolism, excretion, toxicity) prediction results corresponded to the bioactive and safe candidates. Molecular dynamics (MD) confirmed the better binding affinity and stability compared to gilteritinib as a potential FLT3 inhibitor. In this study, a computational approach has been performed that found a better docking and dynamics score against target proteins, indicating potent and safe antileukemic agents, furthermore in-vivo and in-vitro investigations are recommended.

Communicated by Ramaswamy H. Sarma

Keywords:

• Acute myeloid leukemia
• FLT3
• pharmacophore modeling
• quantum mechanical calculation
• HOMO
• LUMO
• DFT
• FMO
• molecular docking
• molecular dynamics simulation
• ADME

Acknowledgments

Authors would like to thank the Department of Chemistry for providing technical support. The authors are also grateful to the HPCC (Aziz Supercomputer) and Advanced Biological Invention Centre, Bioinventics (https://bioinventics.com/) for the resources. We are also thankful to the Department of Pharmacy at King Abdulaziz University for providing facility in Molecular Dynamics Simulation.

Disclosure statement

The authors declare no potential conflicts of interest.

Author contributions

Conceptualization, O.I.O., and W.M.I.H.; methodology, M.R.I.; software, M.R.I., and W.M.I.H.; validation, O.I.O.; formal analysis, W.M.I.H., and O.I.O.; investigation, M.R.I., and W.M.I.H.; resources and data curation, M.R.I.; writing-original draft preparation, M.R.I.; writing‐review and editing, M.R.I., and W.M.I.H.; supervision, W.M.I.H., and O.I.O. All the authors have read and agreed to the published version of the manuscript.

Additional information

Funding

Authors would like to thank the Deanship of Scientific Research (DSR) at King Abdulaziz, Jeddah, for supporting this work under grant no. 1020-130-1443.