Design of Novel FLT-3 Inhibitors Based on Dual-Layer 3D-QSAR Model and Fragment-Based Compounds <i>in Silico</i>

FMS-like tyrosine kinase 3 (FLT-3) is strongly correlated with acute myeloid leukemia, but no FLT-3–inhibitor cocomplex structure is available to assist the design of therapeutic inhibitors. Hence, we propose a dual-layer 3D-QSAR model for FLT-3 that integrates the pharmacophore, CoMFA, and CoMSIA. We then coupled the model with the fragment-based design strategy to identify novel FLT-3 inhibitors. In the first layer, the previously established model, Hypo02, was evaluated in terms of its correlation coefficient (<i>r</i>), RMS, cost difference, and configuration cost, with values of 0.930, 1.24, 106.45, and 16.44, respectively. Moreover, Fischer’s cross-validation test of data generated by Hypo02 yielded a 98% confidence level, and the validation of the testing set yielded a best <i>r</i> value of 0.87. The features of Hypo02 were separated into two parts and then used to screen the MiniMaybridge fragment compound database. Nine novel FLT-3 inhibitors were generated in this layer. In the second layer, Hypo02 was subjected to an alignment rule to generate CoMFA- and CoMSIA-based models, for which the partial least-squares validation method was utilized. The values of <i>q</i>², <i>r</i>², and predictive <i>r</i>² were 0.58, 0.98, and 0.76, respectively, derived from the CoMFA model with steric and electrostatic fields. The CoMSIA model with five different fields yielded values of 0.54, 0.97, and 0.76 for <i>q</i>², <i>r</i>², and predictive <i>r</i>², respectively. The CoMFA and CoMSIA models were used to constrain 3D structures of the nine novel FLT-3 inhibitors. This dual-layer 3D-QSAR model constitutes a valuable tool to easily and quickly screen and optimize novel potential FLT-3 inhibitors for the treatment of acute myeloid leukemia

Selecting Tyrosine Kinase Inhibitors for Gastrointestinal Stromal Tumor with Secondary KIT Activation-Loop Domain Mutations

<div><p>Advanced gastrointestinal stromal tumors (GIST), a <i>KIT</i> oncogene-driven tumor, on imatinib mesylate (IM) treatment may develop secondary <i>KIT</i> mutations to confer IM-resistant phenotype. Second-line sunitinib malate (SU) therapy is largely ineffective for IM-resistant GISTs with secondary exon 17 (activation-loop domain) mutations. We established an <i>in vitro</i> cell-based platform consisting of a series of COS-1 cells expressing <i>KIT</i> cDNA constructs encoding common primary±secondary mutations observed in GISTs, to compare the activity of several commercially available tyrosine kinase inhibitors on inhibiting the phosphorylation of mutant KIT proteins at their clinically achievable plasma steady-state concentration (Css). The inhibitory efficacies on <i>KIT</i> exon 11/17 mutants were further validated by growth inhibition assay on GIST48 cells, and underlying molecular-structure mechanisms were investigated by molecular modeling. Our results showed that SU more effectively inhibited mutant KIT with secondary exon 13 or 14 mutations than those with secondary exon 17 mutations, as clinically indicated. On contrary, at individual Css, nilotinib and sorafenib more profoundly inhibited the phosphorylation of KIT with secondary exon 17 mutations and the growth of GIST48 cells than IM, SU, and dasatinib. Molecular modeling analysis showed fragment deletion of exon 11 and point mutation on exon 17 would lead to a shift of KIT conformational equilibrium toward active form, for which nilotinib and sorafenib bound more stably than IM and SU. In current preclinical study, nilotinib and sorafenib are more active in IM-resistant GISTs with secondary exon 17 mutation than SU that deserve further clinical investigation.</p></div

Effects of TKIs on phosphorylated KIT with variant KIT mutations.

<p>(a) COS-1 cells transfected with KIT single mutants were starved and treated with indicated doses of IM, SU, and nilotinib for 30 minutes. The total expression and degree of phosphorylation of KIT were determined by western blot analysis. (b) Inhibitory ratios at Css (IR_Css) of IM, SU, and nilotinib, as the red arrow pointed, on KIT single mutations were determined by quantification of phosphorylated KIT/total KIT and estimated from the western blot in (a). The data are expressed as the mean ± SE of three independent experiments.</p

Rapid progression of IM-resistant tumor after SU treatment.

<p>A patient harboring KIT exon 11^{Val555_Leu576del}/17^Asn822Lys mutated, metastatic GIST within the liver after 3 months of SU at dose of 50 mg/day, 4 weeks-on/2 weeks-off., (a) before and (n) after SU treatment.</p

Effects of TKIs on phosphorylated KIT with mutations on exon 9 or 11/17.

<p>(a) COS-1 cell transfected with KIT double mutants were starved and treated with indicated doses of multiple TKIs for 30 minutes respectively. The total expression and degree of phosphorylation of KIT were determined by western blot analysis. (b) Inhibitory ratios at Css (IR_Css) of multiple TKIs, as the red arrow pointed, on KIT secondary mutations on exon 17 were determined by quantification of phosphorylated KIT/total KIT and estimated from the western blot in (a). The data are expressed as the mean ± SE of three independent experiments.</p

Effects of TKIs on phosphorylated KIT with mutations on exon 9 or 11/13 or 14.

<p>(a) COS-1 cell transfected with KIT double mutants were starved and treated with indicated doses of multiple TKIs for 30 minutes respectively. The total expression and degree of phosphorylation of KIT were determined by western blot analysis. (b) Inhibitory ratios at Css (IR_Css) of multiple TKIs, as the red arrow pointed, on KIT secondary mutations on exon 13 or 14 were determined by quantification of phosphorylated KIT/total KIT and estimated from the western blot in (a). The data are expressed as the mean ± SE of three independent experiments.</p

Effects and antitumor activities of TKI on GIST48 cells.

<p>(a) GIST48 cells were starved and treated with indicated doses of TKIs for 30 minutes respectively. The total expression and degree of phosphorylation of KIT were determined by western blot analysis. (b) Inhibitory ratios at Css (IR_Css) of TKIs, as the red arrow pointed, on mutated KIT of GIST48 were determined by quantification of phosphorylated KIT/total KIT and estimated from the western blot in (a). (c) Antitumor activities of TKIs against GIST48 cells were preformed with TKIs as indicated doses for 3 days respectively. The cell viabilities were determined by comparing each data to untreated control. (d) Survival ratios at Css of TKIs against GIST48 were estimated from (c). The data are expressed as the mean ± SE of three independent experiments.</p

Binding energies and interactions of TKIs to KIT 11^{Val555_Leu576del}/17^Asp820Gly mutations.

<p>(a) Stereo views of IM, nilotinib, and sorafenib binding to KIT showing key hydrogen bonds formed with A599 and R684 in different models. (b) Binding energies of IM, SU, nilotinib, dasatinib, and sorafenib were estimated according docking TKIs to KIT mutants on exon 11^{Val555_Leu576del}/exon 17^Asp820Gly.</p

Clinical outcomes of TKIs on IM/SU-resistant GIST.

<p>S.D.: stable disease; PFS: progression-free survival; OS: overall survival; N.A: not available.</p