Understanding the Role of Activation Loop Mutants in Drug Efficacy for FLT3-ITD

Abstract

The type III receptor tyrosine kinase FLT3 is a pivotal kinase for hematopoietic progenitor cell regulation, with significant implications in acute myeloid leukemia (AML) through mutations like internal tandem duplication (ITD). This study delves into the structural intricacies of FLT3, the roles of activation loop mutants, and their interaction with tyrosine kinase inhibitors. Coupled with this, the research leverages molecular contrastive learning and protein language modeling to examine interactions between small molecule inhibitors and FLT3 activation loop mutants. Utilizing the ConPLex platform, over 5.7 million unique FLT3 activation loop mutants-small molecule pairs were analyzed. The binding free energies of three inhibitors were assessed, and cellular apoptotic responses were evaluated under drug treatments. Notably, the introduction of the Xepto50 scoring system provides a nuanced metric for drug efficacy. The findings underscore the modulation of molecular interactions and cellular responses by Y842 mutations in FLT3-KD, highlighting the need for tailored therapeutic approaches in FLT3-ITD-related malignancies.

Keywords: drug sensitivity scores; four-parameter logistic curve; molecular docking; molecular modeling.

Figure 1

Interaction dynamics of FLT3 kinase domain and its mutants with small molecules. (A) Distribution of interaction scores for over 5.7 million unique FLT3-KD-small molecule pairs sourced from the ChEMBL database. ConPLex platform with a threshold score of >0.8 was used to identify interactions between small molecules and FLT3 kinase domains. (B) Trend analysis of interaction scores, revealing a descending order from FLT3-KD > FLT3-KD-Y842C > FLT3-KD-Y842F. (C) Specific interaction scores for FLT3 inhibitors.

Figure 2

Differential apoptotic responses and binding energy analyses of FLT3-ITD Y842 mutants under drug treatments. (A) Measurement of apoptotic cells using the annexin V-7-AAD kit after treating cells with specific inhibitors for 48 h prior to processing and analysis (n = 5). (B) Binding energy, represented as negative values, is plotted against various drug–mutant pairs. (C) Calculation of relative apoptotic cells by subtracting the number of apoptotic cells observed in DMSO-treated controls from those treated with specific inhibitors.

Figure 3

Assessment of various drug sensitivity metrics. (A) IC₅₀ values were determined using GraphPad Prism 9 (n = 5), derived from interpolated values at 50 and subsequently transformed to a negative log₁₀ scale. (B) The area under the curve (AUC) was computed from the same dataset, with a baseline response set at 10. (C) Drug Sensitivity Score 1 (DSS1) was determined using the Xepto50 software (version 0.0.2). (D) The Xepto50 score was derived from the normalized AUC at a specific interval on a logarithmic concentration axis.