Discovery and optimization of narrow spectrum inhibitors of Tousled like kinase 2 (TLK2) using quantitative structure activity relationships.

The oxindole scaffold has been the center of several kinase drug discovery programs, some of which have led to approved medicines. A series of two oxindole matched pairs from the literature were identified where TLK2 was potently inhibited as an off-target kinase. The oxindole has long been considered a promiscuous kinase inhibitor template, but across these four specific literature oxindoles TLK2 activity was consistent, while the kinome profile was radically different ranging from narrow to broad spectrum kinome coverage. We synthesized a large series of analogues, utilizing quantitative structure-activity relationship (QSAR) analysis, water mapping of the kinase ATP binding sites, kinome profiling, and small-molecule x-ray structural analysis to optimize TLK2 inhibition and kinome selectivity. This resulted in the identification of several narrow spectrum, sub-family selective, chemical tool compounds including 128 (UNC-CA2-103) that could enable elucidation of TLK2 biology.

PIP4K2C inhibition reverses autophagic flux impairment induced by SARS-CoV-2.

In search for broad-spectrum antivirals, we discovered a small molecule inhibitor, RMC-113, that potently suppresses the replication of multiple RNA viruses including SARS-CoV-2 in human lung organoids. We demonstrated selective dual inhibition of the lipid kinases PIP4K2C and PIKfyve by RMC-113 and target engagement by its clickable analog. Advanced lipidomics revealed alteration of SARS-CoV-2-induced phosphoinositide signature by RMC-113 and linked its antiviral effect with functional PIP4K2C and PIKfyve inhibition. We discovered PIP4K2C's roles in SARS-CoV-2 entry, RNA replication, and assembly/egress, validating it as a druggable antiviral target. Integrating proteomics, single-cell transcriptomics, and functional assays revealed that PIP4K2C binds SARS-CoV-2 nonstructural protein 6 and regulates virus-induced impairment of autophagic flux. Reversing this autophagic flux impairment is a mechanism of antiviral action of RMC-113. These findings reveal virus-induced autophagy regulation via PIP4K2C, an understudied kinase, and propose dual inhibition of PIP4K2C and PIKfyve as a candidate strategy to combat emerging viruses.

Illuminating function of the understudied druggable kinome.

The human kinome, with more than 500 proteins, is crucial for cell signaling and disease. Yet, about one-third of kinases lack in-depth study. The Data and Resource Generating Center for Understudied Kinases has developed multiple resources to address this challenge including creation of a heavy amino acid peptide library for parallel reaction monitoring and quantitation of protein kinase expression, use of understudied kinases tagged with a miniTurbo-biotin ligase to determine interaction networks by proximity-dependent protein biotinylation, NanoBRET probe development for screening chemical tool target specificity in live cells, characterization of small molecule chemical tools inhibiting understudied kinases, and computational tools for defining kinome architecture. These resources are available through the Dark Kinase Knowledgebase, supporting further research into these understudied protein kinases.

Combined kinome inhibition states are predictive of cancer cell line sensitivity to kinase inhibitor combination therapies.

Protein kinases are a primary focus in targeted therapy development for cancer, owing to their role as regulators in nearly all areas of cell life. Recent strategies targeting the kinome with combination therapies have shown promise, such as trametinib and dabrafenib in advanced melanoma, but empirical design for less characterized pathways remains a challenge. Computational combination screening is an attractive alternative, allowing in-silico filtering prior to experimental testing of drastically fewer leads, increasing efficiency and effectiveness of drug development pipelines. In this work, we generated combined kinome inhibition states of 40,000 kinase inhibitor combinations from kinobeads-based kinome profiling across 64 doses. We then integrated these with transcriptomics from CCLE to build machine learning models with elastic-net feature selection to predict cell line sensitivity across nine cancer types, with accuracy R2 ∼ 0.75-0.9. We then validated the model by using a PDX-derived TNBC cell line and saw good global accuracy (R2 ∼ 0.7) as well as high accuracy in predicting synergy using four popular metrics (R2 ∼ 0.9). Additionally, the model was able to predict a highly synergistic combination of trametinib and omipalisib for TNBC treatment, which incidentally was recently in phase I clinical trials. Our choice of tree-based models for greater interpretability allowed interrogation of highly predictive kinases in each cancer type, such as the MAPK, CDK, and STK kinases. Overall, these results suggest that kinome inhibition states of kinase inhibitor combinations are strongly predictive of cell line responses and have great potential for integration into computational drug screening pipelines. This approach may facilitate the identification of effective kinase inhibitor combinations and accelerate the development of novel cancer therapies, ultimately improving patient outcomes.

Combined kinome inhibition states are predictive of cancer cell line sensitivity to kinase inhibitor combination therapies.

Protein kinases are a primary focus in targeted therapy development for cancer, owing to their role as regulators in nearly all areas of cell life. Kinase inhibitors are one of the fastest growing drug classes in oncology, but resistance acquisition to kinase-targeting monotherapies is inevitable due to the dynamic and interconnected nature of the kinome in response to perturbation. Recent strategies targeting the kinome with combination therapies have shown promise, such as the approval of Trametinib and Dabrafenib in advanced melanoma, but similar empirical combination design for less characterized pathways remains a challenge. Computational combination screening is an attractive alternative, allowing in-silico screening prior to in-vitro or in-vivo testing of drastically fewer leads, increasing efficiency and effectiveness of drug development pipelines. In this work, we generate combined kinome inhibition states of 40,000 kinase inhibitor combinations from kinobeads-based kinome profiling across 64 doses. We then integrated these with baseline transcriptomics from CCLE to build robust machine learning models to predict cell line sensitivity from NCI-ALMANAC across nine cancer types, with model accuracy R2 ~ 0.75-0.9 after feature selection using elastic-net regression. We further validated the model's ability to extend to real-world examples by using the best-performing breast cancer model to generate predictions for kinase inhibitor combination sensitivity and synergy in a PDX-derived TNBC cell line and saw reasonable global accuracy in our experimental validation (R2 ~ 0.7) as well as high accuracy in predicting synergy using four popular metrics (R2 ~ 0.9). Additionally, the model was able to predict a highly synergistic combination of Trametinib (MEK inhibitor) and Omipalisib (PI3K inhibitor) for TNBC treatment, which incidentally was recently in phase I clinical trials for TNBC. Our choice of tree-based models over networks for greater interpretability also allowed us to further interrogate which specific kinases were highly predictive of cell sensitivity in each cancer type, and we saw confirmatory strong predictive power in the inhibition of MAPK, CDK, and STK kinases. Overall, these results suggest that kinome inhibition states of kinase inhibitor combinations are strongly predictive of cell line responses and have great potential for integration into computational drug screening pipelines. This approach may facilitate the identification of effective kinase inhibitor combinations and accelerate the development of novel cancer therapies, ultimately improving patient outcomes.

Combined CDK4/6 and ERK1/2 Inhibition Enhances Antitumor Activity in NF1-Associated Plexiform Neurofibroma.

PURPOSE: Plexiform neurofibromas (PNF) are peripheral nerve sheath tumors that cause significant morbidity in persons with neurofibromatosis type 1 (NF1), yet treatment options remain limited. To identify novel therapeutic targets for PNF, we applied an integrated multi-omic approach to quantitatively profile kinome enrichment in a mouse model that has predicted therapeutic responses in clinical trials for NF1-associated PNF with high fidelity. EXPERIMENTAL DESIGN: Utilizing RNA sequencing combined with chemical proteomic profiling of the functionally enriched kinome using multiplexed inhibitor beads coupled with mass spectrometry, we identified molecular signatures predictive of response to CDK4/6 and RAS/MAPK pathway inhibition in PNF. Informed by these results, we evaluated the efficacy of the CDK4/6 inhibitor, abemaciclib, and the ERK1/2 inhibitor, LY3214996, alone and in combination in reducing PNF tumor burden in Nf1flox/flox;PostnCre mice. RESULTS: Converging signatures of CDK4/6 and RAS/MAPK pathway activation were identified within the transcriptome and kinome that were conserved in both murine and human PNF. We observed robust additivity of the CDK4/6 inhibitor, abemaciclib, in combination with the ERK1/2 inhibitor, LY3214996, in murine and human NF1(Nf1) mutant Schwann cells. Consistent with these findings, the combination of abemaciclib (CDK4/6i) and LY3214996 (ERK1/2i) synergized to suppress molecular signatures of MAPK activation and exhibited enhanced antitumor activity in Nf1flox/flox;PostnCre mice in vivo. CONCLUSIONS: These findings provide rationale for the clinical translation of CDK4/6 inhibitors alone and in combination with therapies targeting the RAS/MAPK pathway for the treatment of PNF and other peripheral nerve sheath tumors in persons with NF1.

Small-molecule inhibition of the archetypal UbiB protein COQ8.

Small-molecule tools have enabled mechanistic investigations and therapeutic targeting of the protein kinase-like (PKL) superfamily. However, such tools are still lacking for many PKL members, including the highly conserved and disease-related UbiB family. Here, we sought to develop and characterize an inhibitor for the archetypal UbiB member COQ8, whose function is essential for coenzyme Q (CoQ) biosynthesis. Guided by crystallography, activity assays and cellular CoQ measurements, we repurposed the 4-anilinoquinoline scaffold to selectively inhibit human COQ8A in cells. Our chemical tool promises to lend mechanistic insights into the activities of these widespread and understudied proteins and to offer potential therapeutic strategies for human diseases connected to their dysfunction.

Discovery and Optimization of Narrow Spectrum Inhibitors of Tousled Like Kinase 2 (TLK2) Using Quantitative Structure Activity Relationships.

The oxindole scaffold has been the center of several kinase drug discovery programs, some of which have led to approved medicines. A series of two oxindole matched pairs from the literature were identified where TLK2 was a potent off-target kinase. The oxindole has long been considered a promiscuous inhibitor template, but across these 4 specific literature oxindoles TLK2 activity was consistent, while the kinome profile was radically different from narrow to broad spectrum coverage. We synthesized a large series of analogues and through quantitative structure-activity relationship (QSAR) analysis, water mapping of the kinase ATP binding sites, small-molecule x-ray structural analysis and kinome profiling, narrow spectrum, sub-family selective, chemical tool compounds were identified to enable elucidation of TLK2 biology.

FDA Approaches in Monitoring Drug Quality, Forces Impacting the Drug Quality, and Recent Alternative Strategies to Assess Quality in the US Drug Supply.

Since the US Food and Drug Administration (FDA) began monitoring the quality of pharmaceutical manufacturing by enforcing current good manufacturing practices roughly 60 years ago, forces related to the global economy have changed, rendering the task of monitoring quality more difficult. Alternative strategies by groups like Valisure, LLC, and the University of Kentucky Drug Quality Study to monitor the quality of the currently circulated US drug supply through end-product testing and screening have resulted in several concerning findings. Given the successful approaches of identifying quality defects in pharmaceuticals by non-regulatory bodies, and considering the changing landscape and pressures on manufacturing, the FDA, large buying groups, and the US Department of Defense should consider these alternative strategies as a means to augment current regulatory activities.

Numb-associated kinases are required for SARS-CoV-2 infection and are cellular targets for antiviral strategies.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to pose serious threats to global health. We previously reported that AAK1, BIKE and GAK, members of the Numb-associated kinase family, control intracellular trafficking of multiple RNA viruses during viral entry and assembly/egress. Here, using both genetic and pharmacological approaches, we probe the functional relevance of NAKs for SARS-CoV-2 infection. siRNA-mediated depletion of AAK1, BIKE, GAK, and STK16, the fourth member of the NAK family, suppressed SARS-CoV-2 infection in human lung epithelial cells. Both known and novel small molecules with potent AAK1/BIKE, GAK or STK16 activity suppressed SARS-CoV-2 infection. Moreover, combination treatment with the approved anti-cancer drugs, sunitinib and erlotinib, with potent anti-AAK1/BIKE and GAK activity, respectively, demonstrated synergistic effect against SARS-CoV-2 infection in vitro. Time-of-addition experiments revealed that pharmacological inhibition of AAK1 and BIKE suppressed viral entry as well as late stages of the SARS-CoV-2 life cycle. Lastly, suppression of NAKs expression by siRNAs inhibited entry of both wild type and SARS-CoV-2 pseudovirus. These findings provide insight into the roles of NAKs in SARS-CoV-2 infection and establish a proof-of-principle that pharmacological inhibition of NAKs can be potentially used as a host-targeted approach to treat SARS-CoV-2 with potential implications to other coronaviruses.

Identification of 4-Anilinoquin(az)oline as a Cell-Active Protein Kinase Novel 3 (PKN3) Inhibitor Chemotype.

Deep annotation of a library of 4-anilinoquin(az)olines led to the identification of 7-iodo-N-(3,4,5-trimethoxyphenyl)quinolin-4-amine 16 as a potent inhibitor (IC50 =14 nM) of Protein Kinase Novel 3 (PKN3) with micromolar activity in cells. Compound 16 is a potential tool compound to study the cell biology of PKN3 and its role in pancreatic and prostate cancer and T-cell acute lymphoblastic leukemia. These 4-anilinoquin(az)olines may also be useful tools to uncover the therapeutic potential of PKN3 inhibition in a broad range of diseases.

Adaptive chromatin remodeling and transcriptional changes of the functional kinome in tumor cells in response to targeted kinase inhibition.

Pharmacological inhibition of protein kinases induces adaptive reprogramming of tumor cell regulatory networks by altering expression of genes that regulate signaling, including protein kinases. Adaptive responses are dependent on transcriptional changes resulting from remodeling of enhancer and promoter landscapes. Enhancer and promoter remodeling in response to targeted kinase inhibition is controlled by changes in open chromatin state and by activity of specific transcription factors, such as c-MYC. This review focuses on the dynamic plasticity of protein kinase expression of the tumor cell kinome and the resulting adaptive resistance to targeted kinase inhibition. Plasticity of the functional kinome has been shown in patient window trials where triple-negative and human epidermal growth factor receptor 2-positive breast cancer patient tumors were characterized by RNAseq after biopsies before and after 1 week of therapy. The expressed kinome changed dramatically during drug treatment, and these changes in kinase expression were shown in cell lines and xenografts in mice to be correlated with adaptive tumor cell drug resistance. The dynamic transcriptional nature of the kinome also differs for inhibitors targeting different kinase signaling pathways (e.g., BRAF-MEK-ERK versus PI3K-AKT) that are commonly activated in cancers. Heterogeneity arising from differences in gene regulation and mutations represents a challenge to therapeutic durability and prevention of clinical drug resistance with drug-tolerant tumor cell populations developing and persisting through treatment. We conclude that understanding the heterogeneity of kinase expression at baseline and in response to therapy is imperative for development of combinations and timing intervals of therapies making interventions durable.

PRM-LIVE with Trapped Ion Mobility Spectrometry and Its Application in Selectivity Profiling of Kinase Inhibitors.

Parallel reaction monitoring (PRM) has emerged as a popular approach for targeted protein quantification. With high ion utilization efficiency and first-in-class acquisition speed, the timsTOF Pro provides a powerful platform for PRM analysis. However, sporadic chromatographic drift in peptide retention time represents a fundamental limitation for the reproducible multiplexing of targets across PRM acquisitions. Here, we present PRM-LIVE, an extensible, Python-based acquisition engine for the timsTOF Pro, which dynamically adjusts detection windows for reproducible target scheduling. In this initial implementation, we used iRT peptides as retention time standards and demonstrated reproducible detection and quantification of 1857 tryptic peptides from the cell lysate in a 60 min PRM-LIVE acquisition. As an application in functional proteomics, we use PRM-LIVE in an activity-based protein profiling platform to assess binding selectivity of small-molecule inhibitors against 220 endogenous human kinases.

Synthesis and Evaluation of Novel 1,2,6-Thiadiazinone Kinase Inhibitors as Potent Inhibitors of Solid Tumors.

A focused series of substituted 4H-1,2,6-thiadiazin-4-ones was designed and synthesized to probe the anti-cancer properties of this scaffold. Insights from previous kinase inhibitor programs were used to carefully select several different substitution patterns. Compounds were tested on bladder, prostate, pancreatic, breast, chordoma, and lung cancer cell lines with an additional skin fibroblast cell line as a toxicity control. This resulted in the identification of several low single digit micro molar compounds with promising therapeutic windows, particularly for bladder and prostate cancer. A number of key structural features of the 4H-1,2,6-thiadiazin-4-one scaffold are discussed that show promising scope for future improvement.

New strategies for targeting kinase networks in cancer.

Targeted strategies against specific driver molecules of cancer have brought about many advances in cancer treatment since the early success of the first small-molecule inhibitor Gleevec. Today, there are a multitude of targeted therapies approved by the Food and Drug Administration for the treatment of cancer. However, the initial efficacy of virtually every targeted treatment is often reversed by tumor resistance to the inhibitor through acquisition of new mutations in the target molecule, or reprogramming of the epigenome, transcriptome, or kinome of the tumor cells. At the core of this clinical problem lies the assumption that targeted treatments will only be efficacious if the inhibitors are used at their maximum tolerated doses. Such aggressive regimens create strong selective pressure on the evolutionary progression of the tumor, resulting in resistant cells. High-dose single agent treatments activate alternative mechanisms that bypass the inhibitor, while high-dose combinatorial treatments suffer from increased toxicity resulting in treatment cessation. Although there is an arsenal of targeted agents being tested clinically and preclinically, identifying the most effective combination treatment plan remains a challenge. In this review, we discuss novel targeted strategies with an emphasis on the recent cross-disciplinary studies demonstrating that it is possible to achieve antitumor efficacy without increasing toxicity by adopting low-dose multitarget approaches to treatment of cancer and metastasis.

High-content image-based analysis and proteomic profiling identifies Tau phosphorylation inhibitors in a human iPSC-derived glutamatergic neuronal model of tauopathy.

Mutations in MAPT (microtubule-associated protein tau) cause frontotemporal dementia (FTD). MAPT mutations are associated with abnormal tau phosphorylation levels and accumulation of misfolded tau protein that can propagate between neurons ultimately leading to cell death (tauopathy). Recently, a p.A152T tau variant was identified as a risk factor for FTD, Alzheimer's disease, and synucleinopathies. Here we used induced pluripotent stem cells (iPSC) from a patient carrying this p.A152T variant to create a robust, functional cellular assay system for probing pathophysiological tau accumulation and phosphorylation. Using stably transduced iPSC-derived neural progenitor cells engineered to enable inducible expression of the pro-neural transcription factor Neurogenin 2 (Ngn2), we generated disease-relevant, cortical-like glutamatergic neurons in a scalable, high-throughput screening compatible format. Utilizing automated confocal microscopy, and an advanced image-processing pipeline optimized for analysis of morphologically complex human neuronal cultures, we report quantitative, subcellular localization-specific effects of multiple kinase inhibitors on tau, including ones under clinical investigation not previously reported to affect tau phosphorylation. These results demonstrate the potential for using patient iPSC-derived ex vivo models of tauopathy as genetically accurate, disease-relevant systems to probe tau biochemistry and support the discovery of novel therapeutics for tauopathies.

Brigatinib causes tumor shrinkage in both NF2-deficient meningioma and schwannoma through inhibition of multiple tyrosine kinases but not ALK.

Neurofibromatosis Type 2 (NF2) is an autosomal dominant genetic syndrome caused by mutations in the NF2 tumor suppressor gene resulting in multiple schwannomas and meningiomas. There are no FDA approved therapies for these tumors and their relentless progression results in high rates of morbidity and mortality. Through a combination of high throughput screens, preclinical in vivo modeling, and evaluation of the kinome en masse, we identified actionable drug targets and efficacious experimental therapeutics for the treatment of NF2 related schwannomas and meningiomas. These efforts identified brigatinib (ALUNBRIG®), an FDA-approved inhibitor of multiple tyrosine kinases including ALK, to be a potent inhibitor of tumor growth in established NF2 deficient xenograft meningiomas and a genetically engineered murine model of spontaneous NF2 schwannomas. Surprisingly, neither meningioma nor schwannoma cells express ALK. Instead, we demonstrate that brigatinib inhibited multiple tyrosine kinases, including EphA2, Fer and focal adhesion kinase 1 (FAK1). These data demonstrate the power of the de novo unbiased approach for drug discovery and represents a major step forward in the advancement of therapeutics for the treatment of NF2 related malignancies.

FOXA1 and adaptive response determinants to HER2 targeted therapy in TBCRC 036.

Inhibition of the HER2/ERBB2 receptor is a keystone to treating HER2-positive malignancies, particularly breast cancer, but a significant fraction of HER2-positive (HER2+) breast cancers recur or fail to respond. Anti-HER2 monoclonal antibodies, like trastuzumab or pertuzumab, and ATP active site inhibitors like lapatinib, commonly lack durability because of adaptive changes in the tumor leading to resistance. HER2+ cell line responses to inhibition with lapatinib were analyzed by RNAseq and ChIPseq to characterize transcriptional and epigenetic changes. Motif analysis of lapatinib-responsive genomic regions implicated the pioneer transcription factor FOXA1 as a mediator of adaptive responses. Lapatinib in combination with FOXA1 depletion led to dysregulation of enhancers, impaired adaptive upregulation of HER3, and decreased proliferation. HER2-directed therapy using clinically relevant drugs (trastuzumab with or without lapatinib or pertuzumab) in a 7-day clinical trial designed to examine early pharmacodynamic response to antibody-based anti-HER2 therapy showed reduced FOXA1 expression was coincident with decreased HER2 and HER3 levels, decreased proliferation gene signatures, and increased immune gene signatures. This highlights the importance of the immune response to anti-HER2 antibodies and suggests that inhibiting FOXA1-mediated adaptive responses in combination with HER2 targeting is a potential therapeutic strategy.

Limited inhibition of multiple nodes in a driver network blocks metastasis.

Metastasis suppression by high-dose, multi-drug targeting is unsuccessful due to network heterogeneity and compensatory network activation. Here, we show that targeting driver network signaling capacity by limited inhibition of core pathways is a more effective anti-metastatic strategy. This principle underlies the action of a physiological metastasis suppressor, Raf Kinase Inhibitory Protein (RKIP), that moderately decreases stress-regulated MAP kinase network activity, reducing output to transcription factors such as pro-metastastic BACH1 and motility-related target genes. We developed a low-dose four-drug mimic that blocks metastatic colonization in mouse breast cancer models and increases survival. Experiments and network flow modeling show limited inhibition of multiple pathways is required to overcome variation in MAPK network topology and suppress signaling output across heterogeneous tumor cells. Restricting inhibition of individual kinases dissipates surplus signal, preventing threshold activation of compensatory kinase networks. This low-dose multi-drug approach to decrease signaling capacity of driver networks represents a transformative, clinically relevant strategy for anti-metastatic treatment.