Inactive Kinase Conformation Research Articles

Dual-Action Kinase Inhibitors Influence p38α MAP Kinase Dephosphorylation.

Reversible protein phosphorylation directs essential cellular processes including cell division, cell growth, cell death, inflammation, and differentiation. Because protein phosphorylation drives diverse diseases, kinases and phosphatases have been targets for drug discovery, with some achieving remarkable clinical success. Most protein kinases are activated by phosphorylation of their activation loops, which shifts the conformational equilibrium of the kinase towards the active state. To turn off the kinase, protein phosphatases dephosphorylate these sites, but how the conformation of the dynamic activation loop contributes to dephosphorylation was not known. To answer this, we modulated the activation loop conformational equilibrium of human p38α ΜΑP kinase with existing kinase inhibitors that bind and stabilize specific inactive activation loop conformations. From this, we discovered three inhibitors that increase the rate of dephosphorylation of the activation loop phospho-threonine by the PPM serine/threonine phosphatase WIP1. Hence, these compounds are "dual-action" inhibitors that simultaneously block the active site and stimulate p38α dephosphorylation. Our X-ray crystal structures of phosphorylated p38α bound to the dual-action inhibitors reveal a shared flipped conformation of the activation loop with a fully accessible phospho-threonine. In contrast, our X-ray crystal structure of phosphorylated apo human p38α reveals a different activation loop conformation with an inaccessible phospho-threonine, thereby explaining the increased rate of dephosphorylation upon inhibitor binding. These findings reveal a conformational preference of phosphatases for their targets and suggest a new approach to achieving improved potency and specificity for therapeutic kinase inhibitors.

A comprehensive exploration of the druggable conformational space of protein kinases using AI-predicted structures.

Protein kinase function and interactions with drugs are controlled in part by the movement of the DFG and ɑC-Helix motifs that are related to the catalytic activity of the kinase. Small molecule ligands elicit therapeutic effects with distinct selectivity profiles and residence times that often depend on the active or inactive kinase conformation(s) they bind. Modern AI-based structural modeling methods have the potential to expand upon the limited availability of experimentally determined kinase structures in inactive states. Here, we first explored the conformational space of kinases in the PDB and models generated by AlphaFold2 (AF2) and ESMFold, two prominent AI-based protein structure prediction methods. Our investigation of AF2's ability to explore the conformational diversity of the kinome at various multiple sequence alignment (MSA) depths showed a bias within the predicted structures of kinases in DFG-in conformations, particularly those controlled by the DFG motif, based on their overabundance in the PDB. We demonstrate that predicting kinase structures using AF2 at lower MSA depths explored these alternative conformations more extensively, including identifying previously unobserved conformations for 398 kinases. Ligand enrichment analyses for 23 kinases showed that, on average, docked models distinguished between active molecules and decoys better than random (average AUC (avgAUC) of 64.58), but select models perform well (e.g., avgAUCs for PTK2 and JAK2 were 79.28 and 80.16, respectively). Further analysis explained the ligand enrichment discrepancy between low- and high-performing kinase models as binding site occlusions that would preclude docking. The overall results of our analyses suggested that, although AF2 explored previously uncharted regions of the kinase conformational space and select models exhibited enrichment scores suitable for rational drug discovery, rigorous refinement of AF2 models is likely still necessary for drug discovery campaigns.

Discovery of an Allosteric, Inactive Conformation-Selective Inhibitor of Full-Length HPK1 Utilizing a Kinase Cascade Assay.

Achieving selectivity across the human kinome is a major hurdle in kinase inhibitor drug discovery. Assays using active, phosphorylated protein kinases bias hits toward poorly selective inhibitors that bind within the highly conserved adenosine triphosphate (ATP) pocket. Targeting inactive (vs active) kinase conformations offers advantages in achieving selectivity because of their more diversified structures. Kinase cascade assays are typically initiated with target kinases in their unphosphorylated inactive forms, which are activated during the assays. Therefore, these assays are capable of identifying inhibitors that preferentially bind to the unphosphorylated form of the enzyme in addition to those that bind to the active form. We applied this cascade assay to the emerging cancer immunotherapy target hematopoietic progenitor kinase 1 (HPK1), a serine/threonine kinase that negatively regulates T cell receptor signaling. Using this approach, we discovered an allosteric, inactive conformation-selective triazolopyrimidinone HPK1 inhibitor, compound 1. Compound 1 binds to unphosphorylated HPK1 >24-fold more potently than active HPK1, is not competitive with ATP, and is highly selective against kinases critical for T cell signaling. Furthermore, compound 1 does not bind to the isolated HPK1 kinase domain alone but requires other domains. Together, these data indicate that 1 is an allosteric HPK1 inhibitor that attenuates kinase autophosphorylation by binding to a pocket consisting of residues within and outside of the kinase domain. Our study demonstrates that cascade assays can lead to the discovery of highly selective kinase inhibitors. The triazolopyrimidinone described in this study may represent a privileged chemical scaffold for further development of potent and selective HPK1 inhibitors.

Validation of ion mobility spectrometry - mass spectrometry as a screening tool to identify type II kinase inhibitors of FGFR1 kinase.

The protein kinase FGFR1 regulates cellular processes in human development. As over-activity of FGFR1 is implicated with cancer, effective inhibitors are in demand. Type I inhibitors, which bind to the active form of FGFR1, are less effective than type II inhibitors, which bind to the inactive form. Screening to distinguish between type I and type II inhibitors is required. X-ray crystallography was used to indicate whether a range of potential inhibitors bind to the active or inactive FGFR1 kinase conformation. The binding affinity of each ligand to FGFR1 was measured using biochemical methods. Electrospray ionisation - ion mobility spectrometry - mass spectrometry (ESI-IMS-MS) in conjunction with collision-induced protein unfolding generated a conformational profile of each FGFR1-ligand complex. The results indicate that the protein's conformational profile depends on whether the inhibitor is type I or type II. X-ray crystallography confirmed which of the kinase inhibitors bind to the active or inactive form of FGFR1 kinase. Collision-induced unfolding combined with ESI-IMS-MS showed distinct differences in the FGFR1 folding landscape for type I and type II inhibitors. Biochemical studies indicated a similar range of FGFR1 affinities for both types of inhibitors, thus providing confidence that the conformational variations detected using ESI-IMS-MS can be interpretated unequivocally and that this is an effective screening method. A robust ESI-IMS-MS method has been implemented to distinguish between the binding mode of type I and type II inhibitors by monitoring the conformational unfolding profile of FGFR1. This rapid method requires low sample concentrations and could be used as a high-throughput screening technique for the characterisation of novel kinase inhibitors.

Kinematic Flexibility Analysis of Active and Inactive Kinase Conformations

AbstractProtein kinases are cellular enzymes that catalyze the transfer of phosphates from adenosine triphosphate (ATP) to their substrates. Phosphorylation regulates a multitude of cellular activities, and impaired kinase activity is frequently oncogenic. Inactive or activated forms of kinases are often classified into specific conformations of their activation loops and surrounding areas. This information is valuable for developing potent and selective kinase inhibitors. However, these classification schemes ignore how the dynamics of kinases can differ between states. Here, we apply kinematic flexibility analysis (KFA) to characterize differences in the degree of rigidification between active and inactive states for a large set of kinases in the Protein Data Bank (PDB). Overall, we found that the activation loop in the active state rigidifies kinase conformations, while this effect is less pronounced in the inactive state.

Comprehensive Model for Epidermal Growth Factor Receptor Ligand Binding Involving Conformational States of the Extracellular and the Kinase Domains.

The epidermal growth factor (EGF) receptor (EGFR) undergoes ligand-dependent dimerization to initiate transmembrane signaling. Although crystallographic structures of the extracellular and kinase domains are available, ligand binding has not been quantitatively analyzed taking the influence of both domains into account. Here, we developed a model explicitly accounting for conformational changes of the kinase and extracellular domains, their dimerizations and ligand binding to monomeric and dimeric receptor species. The model was fitted to ligand binding data of suspended cells expressing receptors with active or inactive kinase conformations. Receptor dimers with inactive, symmetric configuration of the kinase domains exhibit positive cooperativity and very weak binding affinity for the first ligand, whereas dimers with active, asymmetric kinase dimers are characterized by negative cooperativity and subnanomolar binding affinity for the first ligand. The homodimerization propensity of EGFR monomers with active kinase domains is ∼100-times higher than that of dimers with inactive kinase domains. Despite this fact, constitutive, ligand-independent dimers are mainly generated from monomers with inactive kinase domains due to the excess of such monomers in the membrane. The experimental finding of increased positive cooperativity at high expression levels of EGFR was recapitulated by the model. Quantitative prediction of ligand binding to different receptor species revealed that EGF binds to receptor monomers and dimers in an expression-level dependent manner without significant recruitment of monomers to dimers upon EGF stimulation below the phase transition temperature of the membrane. Results of the fitting offer unique insight into the workings of the EGFR.

Abstract B45: Surveillance of RAS-RAF dynamics in vivo: Tracking activity conformations and drug-induced interactions

Abstract Live-cell recordings of protein conformations and interactions yield novel mechanistic insights into physiologic and pathologic protein functions. We have developed an adaptable and genetically encoded bioluminescence-based biosensor platform to precisely measure signaling dynamics of full-length RAS GTPases and RAF kinases upon physiologic pathway activation, post-translational modifications, mutagenesis, and drug binding. We have recorded the impact of both patient mutations and bioactive small-molecule binding on kinase conformations and binary interactions of GTP-loaded H, N, KRAS with kinases such as RAF. Systematic profiling of αC-helix-OUT BRAF inhibitors (BRAFi) vemurafenib, dabrafenib, encorafenib, and PLX8394 using the BRAF reporter reporter platform (displaying 10 different patient mutations) revealed differences in drug specificities and efficacies. Unexpectedly, the αC-helix-OUT BRAFi engagement with the catalytic pocket of mutated BRAF stabilized an inactive and intermediate full-length kinase conformation, which provoked the enhancement of binary RAS:RAF interactions. We showed that the interference with RAS interactions and nanoclustering has the potential to antagonize the sequential formation of drug-induced tetrameric RAS:RAF complexes. Recently, we have bioengineered a reporter toolbox for direct in vivo recordings of RAS activity conformations. First, we demonstrated that the wild-type RAS reporter—expressed at levels far below endogenous RAS proteins—responds to physiologic pathway activation. Second, we showed that hot-spot RAS mutations display a similar effect on the intramolecular dynamics. The systematic implementation, combination, and advancement of the GTPase and kinase reporter platform have the potential to be used to identify novel means for regulating or perturbing RAS-RAF-ERK signaling in vivo. Citation Format: Ruth Röck, Johanna Mayrhofer, Omar Torres-Quesada, Florian Enzler, Jakob Troppmair, Eduard Stefan. Surveillance of RAS-RAF dynamics in vivo: Tracking activity conformations and drug-induced interactions [abstract]. In: Proceedings of the AACR Special Conference on Targeting RAS-Driven Cancers; 2018 Dec 9-12; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(5_Suppl):Abstract nr B45.

Lead identification and characterization of hTrkA type 2 inhibitors.

Virtual in silico structure-guided modeling, followed by in vitro biochemical screening of a subset of commercially purchasable compound collection resulted in the identification of several human tropomyosin receptor kinase A (hTrkA) inhibitors that bind the orthosteric ATP site and exhibit binding preference for the inactive kinase conformation. The type 2 binding mode with the DFG-out and αC-helix out hTrkA kinase domain conformation was confirmed from X-ray crystallographic solution of a representative inhibitor analog, 1b. Additional hTrkA and hTrkB (selectivity) assays in recombinant cells, neurite outgrowth inhibition using rat PC12 cells, early ADME profiling, and preliminary pharmacokinetic evaluation in rodents guided the lead inhibitor progression in the discovery screening funnel.

Identification of a New Inhibitor That Stabilizes Interleukin-2-Inducible T-Cell Kinase in Its Inactive Conformation

Interleukin-2-inducible T-cell kinase (ITK) plays an important role in T-cell signaling and is considered a promising drug target. As the ATP binding sites of protein kinases are highly conserved, the design of selective kinase inhibitors remains a challenge. Targeting inactive kinase conformations can address the issue of kinase inhibitor selectivity. It is important for selectivity considerations to identify compounds that stabilize inactive conformations from the primary screen hits. Here we screened a library of 390,000 compounds with an ADP-Glo assay using dephosphorylated ITK. After a surface plasmon resonance (SPR) assay was used to filter out promiscuous inhibitors, 105 hits were confirmed. Next, we used a fluorescent biosensor to enable the detection of conformational changes to identify inactive conformation inhibitors. A single-cysteine-substituted ITK mutant was labeled with acrylodan, and fluorescence emission was monitored. Using a fluorescent biosensor assay, we identified 34 inactive conformation inhibitors from SPR hits. Among them, one compound was bound to a site other than the ATP pocket and exhibited excellent selectivity against a kinase panel. Overall, (1) biochemical screening using dephosphorylated kinase, (2) hit confirmation by SPR assay, and (3) fluorescent biosensor assay that can distinguish inactive compounds provide a useful platform and offer opportunities to identify selective kinase inhibitors.

Machine Learning Models for Accurate Prediction of Kinase Inhibitors with Different Binding Modes.

Noncovalent inhibitors of protein kinases have different modes of action. They bind to the active or inactive form of kinases, compete with ATP, stabilize inactive kinase conformations, or act through allosteric sites. Accordingly, kinase inhibitors have been classified on the basis of different binding modes. For medicinal chemistry, it would be very useful to derive mechanistic hypotheses for newly discovered inhibitors. Therefore, we have applied different machine learning approaches to generate models for predicting different classes of kinase inhibitors including types I, I1/2, and II as well as allosteric inhibitors. These models were built on the basis of compounds with binding modes confirmed by X-ray crystallography and yielded unexpectedly accurate and stable predictions without the need for deep learning. The results indicate that the new machine learning models have considerable potential for practical applications. Therefore, our data sets and models are made freely available.

BRAF inhibitors promote intermediate BRAF(V600E) conformations and binary interactions with activated RAS.

Oncogenic BRAF mutations initiate tumor formation by unleashing the autoinhibited kinase conformation and promoting RAS-decoupled proliferative RAF-MEK-ERK signaling. We have engineered luciferase-based biosensors to systematically track full-length BRAF conformations and interactions affected by tumorigenic kinase mutations and GTP loading of RAS. Binding of structurally diverse αC-helix-OUT BRAF inhibitors (BRAFi) showed differences in specificity and efficacy by shifting patient mutation-containing BRAF reporters from the definitive opened to more closed conformations. Unexpectedly, BRAFi engagement with the catalytic pocket of V600E-mutated BRAF stabilized an intermediate and inactive kinase conformation that enhanced binary RAS:RAF interactions, also independently of RAF dimerization in melanoma cells. We present evidence that the interference with RAS interactions and nanoclustering antagonizes the sequential formation of drug-induced RAS:RAF tetramers. This suggests a previously unappreciated allosteric effect of anticancer drug-driven intramolecular communication between the kinase and RAS-binding domains of mutated BRAF, which may further promote paradoxical kinase activation and drug resistance mechanisms.

Binding to an Unusual Inactive Kinase Conformation by Highly Selective Inhibitors of Inositol-Requiring Enzyme 1α Kinase-Endoribonuclease

A series of imidazo[1,2-b]pyridazin-8-amine kinase inhibitors were discovered to allosterically inhibit the endoribonuclease function of the dual kinase-endoribonuclease inositol-requiring enzyme 1α (IRE1α), a key component of the unfolded protein response in mammalian cells and a potential drug target in multiple human diseases. Inhibitor optimization gave compounds with high kinome selectivity that prevented endoplasmic reticulum stress-induced IRE1α oligomerization and phosphorylation, and inhibited endoribonuclease activity in human cells. X-ray crystallography showed the inhibitors to bind to a previously unreported and unusually disordered conformation of the IRE1α kinase domain that would be incompatible with back-to-back dimerization of the IRE1α protein and activation of the endoribonuclease function. These findings increase the repertoire of known IRE1α protein conformations and can guide the discovery of highly selective ligands for the IRE1α kinase site that allosterically inhibit the endoribonuclease.

Redefining the Protein Kinase Conformational Space with Machine Learning

Protein kinases are dynamic, adopting different conformational states that are critical for their catalytic activity. We assess a range of structural features derived from the conserved αC helix and DFG motif to define the conformational space of the catalytic domain of protein kinases. We then construct Kinformation, a random forest classifier, to annotate the conformation of 3,708 kinase structures in the PDB. Our classification scheme captures known active and inactive kinase conformations and defines an additional conformational state, thereby refining the current understanding of the kinase conformational space. Furthermore, network analysis of the small molecules recognized by each conformation captures chemical substructures that are associated with each conformation type. Our description of the kinase conformational space is expected to improve modeling of protein kinase structures, as well as guide the development of conformation-specific kinase inhibitors with optimal pharmacological profiles.

TRK xDFG Mutations Trigger a Sensitivity Switch from Type I to II Kinase Inhibitors

On-target resistance to next-generation kinase inhibitors, drugs specifically designed to maintain potency in the setting of kinase domain mutations, remains poorly characterized. Having identified that xDFG (TRKA G667) mutations confer second-generation TRK inhibitor resistance in patients with TRK fusion-positive cancers, we used computational modeling and biochemical assays to study how these affect drug binding. We found that xDFG mutations stabilize the inactive kinase conformation, hampering the binding of type I second-generation TRK inhibitors, while increasing the affinity for type II multikinase inhibitors. Type II drugs consistently inhibit the growth and TRK-mediated signaling of isogenic and patient-derived models harboring xDFG mutations. Collectively these data demonstrate that TRK xDFG substitutions trigger conformational changes that favor type II binding mechanisms. Given prior identification of paralogous xDFG resistance mutations in other oncogene addicted cancers, these findings provide insight into rational drug design to address these recalcitrant resistant alterations by leveraging inhibitor class affinity switching.

Redefining the Protein Kinase Conformational Space with Machine Learning

Protein kinases are dynamic, adopting different conformational states that are critical for their catalytic activity. We assess a range of structural features derived from the conserved αC helix and DFG motif to define the conformational space of the catalytic domain of protein kinases. We then construct Kinformation, a random forest classifier, to annotate the conformation of 3,708 kinase structures in the PDB. Our classification scheme captures known active and inactive kinase conformations and defines an additional conformational state, thereby refining the current understanding of the kinase conformational space. Furthermore, network analysis of the small molecules recognized by each conformation captures chemical substructures that are associated with each conformation type. Our description of the kinase conformational space is expected to improve modeling of protein kinase structures, as well as guide the development of conformation-specific kinase inhibitors with optimal pharmacological profiles.

An active‐like Src conformation explains its dynamic regulation

Biological signaling by protein kinases plays an essential role in cellular function. The switch between inactive and active protein kinase conformations is central to their regulation. The active conformations of protein kinases are triggered and maintained by various post‐translational modifications. The inactive conformation of Src tyrosine kinase has a non‐phosphorylated activation loop and a rolled‐out αC helix. The R‐spine at the Src kinase core is disassembled via the RS3 residue when the αC helix is disengaged. Maneuvering of the C‐spine is crucial for obtaining a pseudokinase conformation of Src that could be crucial for exploring its scaffolding functions. Our Umbrella sampling methods allow for mapping the conformational landscape of the Src kinase domain and characterizing four defining states; the inactive, active conformations and two intermediates. Mutation of the C‐spine V281F allows for the closing of the two kinase lobes in the absence of ATP. An allosteric region at the β3‐αC loop allows for engaging the αC helix and the RS3 residue of the R‐spine via the L297F mutation. The L297F/ V281F double mutant allows for stabilization of a unique catalytically dead kinase conformation in the active‐like state. These studies allow for exploration of active‐like Src kinase states that define both the underlying kinase activation switch and the dynamic allostery in the molecular communication at the kinase core.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Discovery of Inactive Conformation-Selective Kinase Inhibitors by Utilizing Cascade Assays.

Achieving selectivity across the human kinome is a major hurdle in kinase inhibitor drug discovery. Targeting inactive (vs active) kinase conformations offers advantages in achieving selectivity because of their more diversified structures. Discovery of inactive conformation-selective inhibitors, however, has been hampered partly by the lack of general assay methods. Herein, we show that such inhibitors can be discovered by utilizing kinase cascade assays. This type of assay is initiated with the target kinase in its unphosphorylated, inactive conformation, which is activated during the assay. Inactive conformation-selective inhibitors stabilize the inactive kinase, block activation, and yield reduced kinase activity. We investigate the properties of the assay by mathematical modeling, as well as by proof-of-concept experiments using the BRAF-MEK1 cascade. This study demonstrates effective identification of inactive conformation-selective inhibitors by cascade assays, reveals key factors that impact results, and provides guidelines for successful cascade assay development.

The allosteric inhibitor ABL001 enables dual targeting of BCR-ABL1.

Chronic myeloid leukaemia (CML) is driven by the activity of the BCR-ABL1 fusion oncoprotein. ABL1 kinase inhibitors have improved the clinical outcomes for patients with CML, with over 80% of patients treated with imatinib surviving for more than 10 years. Second-generation ABL1 kinase inhibitors induce more potent molecular responses in both previously untreated and imatinib-resistant patients with CML. Studies in patients with chronic-phase CML have shown that around 50% of patients who achieve and maintain undetectable BCR-ABL1 transcript levels for at least 2 years remain disease-free after the withdrawal of treatment. Here we characterize ABL001 (asciminib), a potent and selective allosteric ABL1 inhibitor that is undergoing clinical development testing in patients with CML and Philadelphia chromosome-positive (Ph+) acute lymphoblastic leukaemia. In contrast to catalytic-site ABL1 kinase inhibitors, ABL001 binds to the myristoyl pocket of ABL1 and induces the formation of an inactive kinase conformation. ABL001 and second-generation catalytic inhibitors have similar cellular potencies but distinct patterns of resistance mutations, with genetic barcoding studies revealing pre-existing clonal populations with no shared resistance between ABL001 and the catalytic inhibitor nilotinib. Consistent with this profile, acquired resistance was observed with single-agent therapy in mice; however, the combination of ABL001 and nilotinib led to complete disease control and eradicated CML xenograft tumours without recurrence after the cessation of treatment.

Cap Analysis of Gene Expression (CAGE) Sequencing Reveals Alterations of the Transcriptional Signatures of FLT3-ITD with Secondary D835 TKD Mutations in Acute Myeloid Leukemia

Mutations in the gene encoding Fms-like tyrosine kinase-3 (FLT3) are found in approximately 30% of acute myeloid leukemia (AML) patients, with two distinct groups of mutations; the internal tandem duplication mutations in juxtamembrane domain (FLT3-ITD) and the point mutations within the tyrosine kinase domains (FLT3-TKD).The second-generation tyrosine kinase inhibitor (TKI) quizartinib which primarily targets an inactive (type II) kinase conformation, has demonstrated responses in relapsed/refractory FLT3-ITD AML patients. However, duration of response to quizartinib is limited largely by secondary mutations in FLT3-TKD, most commonly at D835 activation loop, emerging in at least 20% of patients.To elucidate the alterations of transcript signatures of quizartinib-resistant FLT3-ITD/D835 mutants in AML, we performed cap analysis of gene expression (CAGE) sequencing utilizing 11 FLT3-ITD and 6 FLT3-ITD/D835 primary AML cells with wild type NPM1. CAGE identifies and quantifies the 5’ ends of capped mRNA transcripts, which enables the identification of transcription start sites (TSS) and allows investigating promoter structures necessary for gene expression. The TSS of genes altered in AML cells with FLT3-ITD/D835 compared with FLT3-ITD were mapped, and CAGE detected upregulation of 124 genes and downregulation of 25 genes in FLT3-ITD/D835 cells (FDR < 0.05). Specifically, several genes closely linked with activation of MAPK signaling (MAPK6, TCF4), AKT/mTOR signaling (NBN) and both (TNFAIP6) were upregulated in the D835 acquired cells. Expression of inflammatory response cytokine genes IL1B and IL8 were also increased in FLT3-ITD/D835 cells.The FLT related functional pathway analysis by KEGG ontology indicated that Ras pathway with its downstream Raf/MAPK and PI3K/AKT/mTOR signaling including transcription factor NFKB are the most significantly activated pathways in FLT3-ITD/D835 cells compared to FLT3-ITD cells. No additional activation of STAT5 pathway, a direct downstream signaling of mutated FLT3, was found in FLT3-ITD/D835 cells.To assess the underlying molecular basis of transcription signature, we performed an unbiased search for enriched sequence motifs using HOMER software. HOMER revealed upregulation of 80 motifs and downregulation of 51 motifs in AML cells with FLT3-ITD/D835 compared with FLT3-ITD (q < 0.05). Motifs of AP-1, JUN, CEBP, ATF and NFKB were substantially enriched in FLT3-ITD/D835 compared to FLT3-ITD cells. ETS, SPI-1 and RUNX1 were the most common binding motifs altered (both increased and decreased) by D835 mutation acquisition. Of note, AP-1 modulates inflammatory response and is tightly regulated by MAPK.To validate the transcriptional changes and the highlighted gene ontology results of AML primary samples, we utilized paired isogenic FLT3-ITD or FLT3-ITD/D835Y transfected Ba/F3 cell lines. As predicted, type II kinase inhibitor quizartinib was active against FLT3-ITD Ba/F3 cells (IC50; 0.6nM) but not FLT3-ITD/D835Y Ba/F3 cells (IC50; > 5000nM). Type I kinase inhibitor crenolanib was highly active against both FLT3-ITD (IC50; 2.1nM) and FLT3-ITD/D835Y cells (IC50; 16.4nM). Focusing on FLT related Ras pathway, we first investigated MAPK activation in these cells. Immunoblot analysis demonstrated substantial reduction of phospho- (p-) ERK after quizartinib (5nM) or crenolanib (50nM) treatment both in FLT3-ITD and FLT3-ITD/D835Y cells, irrespective of their susceptibility. We next examined p-S6, the target of PI3K/AKT/mTOR and MAPK signaling, and observed that crenolanib but not quizartinib successfully diminished p-S6 expression in FLT3-ITD/D835Y cells. FLT3-ITD/D835 cells showed higher baseline expression of NFkB regulator p-IkB compared to FLT3-ITD cells, which was not repressed by crenolanib.In conclusion, our study showed that the acquired D835 mutation in FLT3-ITD AML cells facilitates transcriptional network activation to induce proinflammatory genes through Ras-MAPK-NF-κB/AP-1 pathway and Ras-PI3K-AKT-mTOR signaling. This transcriptional modulation promotes oncogenic pro-survival and proliferative signaling in AML cells and defines differential sensitivity against Type I and Type II kinase inhibitors. DisclosuresShah:ARIAD: Research Funding; BMS: Research Funding; Daiichi-Sankyo: Research Funding; Pfizer: Research Funding; Plexxikon: Research Funding. Konopleva:Reata Pharmaceuticals: Equity Ownership; Abbvie: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Stemline: Consultancy, Research Funding; Eli Lilly: Research Funding; Cellectis: Research Funding; Calithera: Research Funding.

UM-164: A Potent c-Src/p38 Kinase Inhibitor with In Vivo Activity against Triple-Negative Breast Cancer.

c-Src has been shown to play a pivotal role in breast cancer progression, metastasis, and angiogenesis. In the clinic, however, the limited efficacy and high toxicity of existing c-Src inhibitors have tempered the enthusiasm for targeting c-Src. We developed a novel c-Src inhibitor (UM-164) that specifically binds the DFG-out inactive conformation of its target kinases. We hypothesized that binding the inactive kinase conformation would lead to improved pharmacologic outcomes by altering the noncatalytic functions of the targeted kinases. We have analyzed the anti-triple-negative breast cancer (TNBC) activity of UM-164 in a comprehensive manner that includes in vitro cell proliferation, migration, and invasion assays (including a novel patient-derived xenograft cell line, VARI-068), along with in vivo TNBC xenografts. We demonstrate that UM-164 binds the inactive kinase conformation of c-Src. Kinome-wide profiling of UM-164 identified that Src and p38 kinase families were potently inhibited by UM-164. We further demonstrate that dual c-Src/p38 inhibition is superior to mono-inhibition of c-Src or p38 alone. We demonstrate that UM-164 alters the cell localization of c-Src in TNBC cells. In xenograft models of TNBC, UM-164 resulted in a significant decrease of tumor growth compared with controls, with limited in vivo toxicity. In contrast with c-Src kinase inhibitors used in the clinic (1, 2), we demonstrate in vivo efficacy in xenograft models of TNBC. Our results suggest that the dual activity drug UM-164 is a promising lead compound for developing the first targeted therapeutic strategy against TNBC. Clin Cancer Res; 22(20); 5087-96. ©2016 AACR.