Available online 15 October 2025
Author links open overlay panel, , , , AbstractFLT3 is a critical prognostic marker in acute myeloid leukemia (AML) due to its high frequency of mutation. Primary mutations in FLT3 include point mutations or deletions in the tyrosine kinase domain (TKD) and internal tandem duplications (ITD) in the juxtamembrane (JM) region. These mutations lead to ligand-independent activation, disrupting the JM region and kinase domain interaction, resulting in autophosphorylation of FLT3 and activation of signalling pathways such as STAT5, MAPK, and AKT, which promotes increased proliferation and resistance to apoptosis. So developing effective therapeutics against these mutant FLT3 proteins is crucial for AML treatment. Here we employed computational approaches, including Molecular Dynamics (MD) simulation, cluster analysis, and Normal Mode Analysis, to investigate the dynamic behaviours of FLT3 mutant structures (TKD mutants Y842C/F in FLT3-WT, FLT3- ITD, and ITD mutant in FLT3-WT). The molecular dynamics (MD) simulation studies revealed that all these mutations significantly affect the optimized state, flexibility, and compactness of the FLT3 protein. Cluster analysis also confirmed that these mutations significantly impacted protein flexibility. Specifically, the point mutation TKD (Y842C) and the combined mutation ITD with TKD (Y842F) increased the flexibility of the FLT3 protein, while the point mutation TKD (Y842F), ITD in the JM region, and the combined mutation of ITD with TKD(Y842C) made the protein more rigid form. These findings underscore the diverse conformations of mutated FLT3 structures, contributing to FLT3 function deregulation and highlighting their potential as therapeutic targets in AML treatment.
Graphical abstract
Download: Download high-res image (129KB)Download: Download full-size imageKeywordsLeukemia
AML
FLT3 protein
Structural conformations
Combination mutation
Point mutation
Protein dynamics
Flexibility
RTK’s
© 2025 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
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