Trends in kinase drug discovery: targets, indications and inhibitor design

Synthesis and Antiproliferative Potential of Thiazole and 4-Thiazolidinone Containing Motifs as Dual Inhibitors of EGFR and BRAFV600E

Thiazole and thiazolidinone recur in a wide range of biologically active compounds that reach different targets within the context of tumors and represent a promising starting point to access potential candidates for treating metastatic cancer. Therefore, searching for new lead compounds that show the highest anticancer potency with the fewest adverse effects is a major drug-discovery challenge. Because the thiazole ring is present in dasatinib, which is currently used in anticancer therapy, it is important to highlight the ring. In this study, cycloalkylidenehydrazinecarbothioamides (cyclopentyl, cyclohexyl, cyclooctyl, dihydronapthalenylidene, flurine-9-ylidene, and indolinonyl) reacted with 2-bromoacetophenone and diethylacetylenedicarboxylate to yield thiazole and 4-thiazolidinone derivatives. The structure of the products was confirmed by using infrared (IR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and single-crystal X-ray analyses. The antiproliferative activity of the newly synthesized compounds was evaluated. The most effective inhibitory compounds were further tested in vitro against both epidermal growth factor receptor (EGFR) and B-Raf proto-oncogene, serine/threonine kinase (BRAFV600E) targets. Additionally, molecular docking analysis examined how these molecules bind to the active sites of EGFR and BRAFV600E.

Targeting EPHA2 with Kinase Inhibitors in Colorectal Cancer

The ephrin type-A 2 receptor tyrosine kinase (EPHA2) is involved in the development and progression of various cancer types, including colorectal cancer (CRC). There is also evidence that EPHA2 plays a key role in the development of resistance to the endothelial growth factor receptor (EGFR) monoclonal antibody Cetuximab used clinically in CRC. Despite the promising pharmacological potential of EPHA2, only a handful of specific inhibitors are currently available. In this concept paper, general strategies for EPHA2 inhibition with molecules of low molecular weight (small molecules) are described. Furthermore, available examples of inhibiting EPHA2 in CRC using small molecules are summarized, highlighting the potential of this approach.

Multimodal multi-task deep neural network framework for kinase-target prediction

Kinase plays a significant role in various disease signaling pathways. Due to the highly conserved sequence of kinase family members, understanding the selectivity profile of kinase inhibitors remains a priority for drug discovery. Previous methods for kinase selectivity identification use biochemical assays, which are very useful but limited by the protein available. The lack of kinase selectivity can exert benefits but also can cause adverse effects. With the explosion of the dataset for kinase activities, current computational methods can achieve accuracy for large-scale selectivity predictions. Here, we present a multimodal multi-task deep neural network model for kinase selectivity prediction by calculating the fingerprint and physiochemical descriptors. With the multimodal inputs of structure and physiochemical properties information, the multi-task framework could accurately predict the kinome map for selectivity analysis. The proposed model displays better performance for kinase-target prediction based on system evaluations.

Allosteric inhibition of myosin by phenamacril: a synergistic mechanism revealed by computational and experimental approaches

BACKGROUND

Myosin plays a crucial role in cellular processes, while its dysfunction can lead to organismal malfunction. Phenamacril (PHA), a highly species-specific and non-competitive inhibitor of myosin I (FgMyoI) from Fusarium graminearum, has been identified as an effective fungicide for controlling plant diseases caused by partial Fusarium pathogens, such as wheat scab and rice bakanae. However, the molecular basis of its action is still unclear.

RESULTS

This study used multiple computational approaches first to elucidate the allosteric inhibition mechanism of FgMyoI by PHA at the atomistic level. The results indicated the increase of adenosine triphosphate (ATP) binding affinity upon PHA binding, which might impede the release of hydrolysis products. Furthermore, simulations revealed a broadened outer cleft and a significantly more flexible interface for actin binding, accompanied by a decrease in signaling transduction from the catalytic center to the actin-binding interface. These various effects might work together to disrupt the actomyosin cycle and hinder the ability of motor to generate force. Our experimental results further confirmed that PHA reduces the enzymatic activity of myosin and its binding with actin.

CONCLUSION

Therefore, our findings demonstrated that PHA might suppress the function of myosin through a synergistic mechanism, providing new insights into myosin allostery and offering new avenues for drug/fungicide discovery targeting myosin. © 2023 Society of Chemical Industry.

Protein kinases: drug targets for immunological disorders

Protein kinases play a major role in cellular activation processes, including signal transduction by diverse immunoreceptors. Given their roles in cell growth and death and in the production of inflammatory mediators, targeting kinases has proven to be an effective treatment strategy, initially as anticancer therapies, but shortly thereafter in immune-mediated diseases. Herein, we provide an overview of the status of small molecule inhibitors specifically generated to target protein kinases relevant to immune cell function, with an emphasis on those approved for the treatment of immune-mediated diseases. The development of inhibitors of Janus kinases that target cytokine receptor signalling has been a particularly active area, with Janus kinase inhibitors being approved for the treatment of multiple autoimmune and allergic diseases as well as COVID-19. In addition, TEC family kinase inhibitors (including Bruton's tyrosine kinase inhibitors) targeting antigen receptor signalling have been approved for haematological malignancies and graft versus host disease. This experience provides multiple important lessons regarding the importance (or not) of selectivity and the limits to which genetic information informs efficacy and safety. Many new agents are being generated, along with new approaches for targeting kinases.

Calibrated geometric deep learning improves kinase-drug binding predictions

Protein kinases regulate various cellular functions and hold significant pharmacological promise in cancer and other diseases. Although kinase inhibitors are one of the largest groups of approved drugs, much of the human kinome remains unexplored but potentially druggable. Computational approaches, such as machine learning, offer efficient solutions for exploring kinase-compound interactions and uncovering novel binding activities. Despite the increasing availability of three-dimensional (3D) protein and compound structures, existing methods predominantly focus on exploiting local features from one-dimensional protein sequences and two-dimensional molecular graphs to predict binding affinities, overlooking the 3D nature of the binding process. Here we present KDBNet, a deep learning algorithm that incorporates 3D protein and molecule structure data to predict binding affinities. KDBNet uses graph neural networks to learn structure representations of protein binding pockets and drug molecules, capturing the geometric and spatial characteristics of binding activity. In addition, we introduce an algorithm to quantify and calibrate the uncertainties of KDBNet's predictions, enhancing its utility in model-guided discovery in chemical or protein space. Experiments demonstrated that KDBNet outperforms existing deep learning models in predicting kinase-drug binding affinities. The uncertainties estimated by KDBNet are informative and well-calibrated with respect to prediction errors. When integrated with a Bayesian optimization framework, KDBNet enables data-efficient active learning and accelerates the exploration and exploitation of diverse high-binding kinase-drug pairs.

Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry

A primary challenge of high-throughput imaging flow cytometry (IFC) is to analyze the vast amount of imaging data, especially in applications where ground truth labels are unavailable or hard to obtain. We present an unsupervised deep embedding algorithm, the Deep Convolutional Autoencoder-based Clustering (DCAEC) model, to cluster label-free IFC images without any prior knowledge of input labels. The DCAEC model first encodes the input images into the latent representations and then clusters based on the latent representations. Using the DCAEC model, we achieve a balanced accuracy of 91.9% for human white blood cell (WBC) clustering and 97.9% for WBC/leukemia clustering using the 3D IFC images and 3D DCAEC model. Above all, although no human recognizable features can separate the clusters of cells with protein localization, we demonstrate the fused DCAEC model can achieve a cluster balanced accuracy of 85.3% from the label-free 2D transmission and 3D side scattering images. To reveal how the neural network recognizes features beyond human ability, we use the gradient-weighted class activation mapping method to discover the cluster-specific visual patterns automatically. Evaluation results show that the automatically identified salient image regions have strong cluster-specific visual patterns for different clusters, which we believe is a stride for the interpretable neural network for cell analysis with high-throughput IFCs.

Graphene Oxide-Mediated Regulation of Volume Exclusion and Wettability in Biomimetic Phosphorylation-Responsive Ionic Gates

Replicating phosphorylation-responsive ionic gates via artificial fluidic systems is essential for biomolecular detection and cellular communication research. However, current approaches to governing the gates primarily rely on volume exclusion or surface charge modulation. To overcome this limitation and enhance ion transport controllability, we introduce graphene oxide (GO) into nanochannel systems, simultaneously regulating the volume exclusion and wettability. Moreover, inspired by (cAMP)-dependent protein kinase A (PKA)-regulated L-type Ca2+ channels, we employ peptides for phosphorylation which preserves them as nanoadhesives to coat nanochannels with GO. The coating boosts steric hindrance and diminishes wettability, creating a substantial ion conduction barrier, which represents a significant advancement in achieving precise ion transport regulation in abiotic nanochannels. Leveraging the mechanism, we also fabricated a sensitive biosensor for PKA activity detection and inhibition exploration. The combined regulation of volume exclusion and wettability offers an appealing strategy for controlled nanofluidic manipulation with promising biomedical applications in diagnosis and drug discovery.

Discovery of a selective TC-PTP degrader for cancer immunotherapy

T-cell protein tyrosine phosphatase (TC-PTP), encoded by PTPN2, has emerged as a promising target for cancer immunotherapy. TC-PTP deletion in B16 melanoma cells promotes tumor cell antigen presentation, while loss of TC-PTP in T-cells enhances T-cell receptor (TCR) signaling and stimulates cell proliferation and activation. Therefore, there is keen interest in developing TC-PTP inhibitors as novel immunotherapeutic agents. Through rational design and systematic screening, we discovered the first highly potent and selective TC-PTP PROTAC degrader, TP1L, which induces degradation of TC-PTP in multiple cell lines with low nanomolar DC50s and >110-fold selectivity over the closely related PTP1B. TP1L elevates the phosphorylation level of TC-PTP substrates including pSTAT1 and pJAK1, while pJAK2, the substrate of PTP1B, is unaffected by the TC-PTP degrader. TP1L also intensifies interferon gamma (IFN-γ) signaling and increases MHC-I expression. In Jurkat cells, TP1L activates TCR signaling through increased phosphorylation of LCK. Furthermore, in a CAR-T cell and KB tumor cell co-culture model, TP1L enhances CAR-T cell mediated tumor killing efficacy through activation of the CAR-T cells. Thus, we surmise that TP1L not only provides a unique opportunity for in-depth interrogation of TC-PTP biology but also serves as an excellent starting point for the development of novel immunotherapeutic agents targeting TC-PTP.

How Ligands Interact with the Kinase Hinge

ATP-competitive kinase inhibitors form hydrogen bond interactions with the kinase hinge region at the adenine binding site. Thus, it is crucial to explore hinge-ligand recognition as part of a rational drug design strategy. Here, harnessing known ligand-bound kinase structures and experimental assay resources, we first created a kinase structure-assay database (KSAD) containing 2705 nM ligand-bound kinase complexes. Then, using KSAD, we systematically investigate hinge-ligand binding patterns using interaction fingerprints, thereby delineating 15 different hydrogen-bond interaction modes. We believe these results will be valuable for de novo drug design and/or scaffold hopping of kinase-targeted drugs.

Waterborne Tebuconazole Exposure Induces Male-Biased Sex Differentiation in Zebrafish (Danio rerio) Larvae via Aromatase Inhibition

Tebuconazole is a widely used fungicide for various crops that targets sterol 14-α-demethylase (CYP51) in fungi. However, attention has shifted to aromatase (CYP19) due to limited research indicating its reproductive impact on aquatic organisms. Herein, zebrafish were exposed to 0.5 mg/L tebuconazole at different developmental stages. The proportion of males increased significantly after long-term exposure during the sex differentiation phase (0-60, 5-60, and 19-60 days postfertilization (dpf)). Testosterone levels increased and 17β-estradiol and cyp19a1a expression levels decreased during the 5-60 dpf exposure, while the sex ratio was equally distributed on coexposure with 50 ng/L 17β-estradiol. Chemically activated luciferase gene expression bioassays determined that the male-biased sex differentiation was not caused by tebuconazole directly binding to sex hormone receptors. Protein expression and phosphorylation levels were specifically altered in the vascular endothelial growth factor signaling pathway despite excluding the possibility of tebuconazole directly interacting with kinases. Aromatase was selected for potential target analysis. Molecular docking and aromatase activity assays demonstrated the interactions between tebuconazole and aromatase, highlighting that tebuconazole poses a threat to fish populations by inducing a gender imbalance.

Real-time monitoring of the reaction of KRAS G12C mutant specific covalent inhibitor by in vitro and in-cell NMR spectroscopy

KRAS mutations are major drivers of various cancers. Recently, allele-specific inhibitors of the KRAS G12C mutant were developed that covalently modify the thiol of Cys12, thereby trapping KRAS in an inactive GDP-bound state. To study the mechanism of action of the covalent inhibitors in both in vitro and intracellular environments, we used real-time NMR to simultaneously observe GTP hydrolysis and inhibitor binding. In vitro NMR experiments showed that the rate constant of ARS-853 modification is identical to that of GTP hydrolysis, indicating that GTP hydrolysis is the rate-limiting step for ARS-853 modification. In-cell NMR analysis revealed that the ARS-853 reaction proceeds significantly faster than that in vitro, reflecting acceleration of GTP hydrolysis by endogenous GTPase proteins. This study demonstrated that the KRAS covalent inhibitor is as effective in the cell as in vitro and that in-cell NMR is a valuable validation tool for assessing the pharmacological properties of the drug in the intracellular context.

Cell-active, irreversible covalent inhibitors that selectively target the catalytic lysine of EGFR by using fluorosulfate-based SuFEx chemistry

EGFR signaling is involved in multiple cellular processes including cell proliferation, differentiation and development, making this protein kinase one of the most valuable drug targets for the treatment of non-small cell lung carcinomas (NSCLC). Herein, we describe the design and synthesis of a series of potential covalent inhibitors targeting the catalytically conserved lysine (K745) of EGFR on the basis of Erlotinib, an FDA-approved first-generation EGFR drug. Different amine-reactive electrophiles were introduced at positions on the Erlotinib scaffold proximal to K745 in EGFR. The optimized compound 26 (as well as its close analog 30), possessing a novel arylfluorosulfate group (ArOSO2F), showed excellent in vitro potency (as low as 0.19 nM in independent IC50 determination) and selectivity against EGFR and many of its drug-resistant mutants. Both intact protein mass spectrometry (MS) and site-mapping analysis revealed that compound 26 covalently bound to EGFR at K745 through the formation of a sulfamate. In addition, compound 26 displayed good anti-proliferative potency against EGFR-overexpressing HCC827 cells by inhibiting endogenous EGFR autophosphorylation. The pharmacokinetic studies of compound 26 demonstrated the druggable potential of other ArOSO2F-containing compounds. Finally, competitive activity-based protein profiling (ABPP), cellular thermal shift assay (CETSA), as well as cellular wash-out experiments, all showed compound 26 to be the first cell-active, fluorosulfate-based targeted covalent inhibitor (TCI) of protein kinases capable of covalently engaging the catalytically conserved lysine of its target in live mammalian cells.

Quinazoline-based VEGFR-2 inhibitors as potential anti-angiogenic agents: A contemporary perspective of SAR and molecular docking studies

Angiogenesis, the formation of new blood vessels from the existing vasculature, is pivotal in the migration, growth, and differentiation of endothelial cells in normal physiological conditions. In various types of tumour microenvironments, dysregulated angiogenesis plays a crucial role in supplying oxygen and nutrients to cancerous cells, leading to tumour size growth. VEGFR-2 tyrosine kinase has been extensively studied as a critical regulator of angiogenesis; thus, inhibition of VEGFR-2 has been widely used for cancer treatments in recent years. Quinazoline nucleus is a privileged and versatile scaffold with a broad range of pharmacological activity, especially in the field of tyrosine kinase inhibitors with more than twenty small molecule inhibitors approved by the US Food and Drug Administration in the last two decades. As of now, the U.S. FDA has approved eleven small chemical inhibitors of VEGFR-2 for various types of malignancies, with a prime example being vandetanib, a quinazoline derivative, which is a multi targeted kinase inhibitor used for the treatment of late-stage medullary thyroid cancer. Despite of prosperous discovery and development of VEGFR-2 down regulator drugs, there still exists limitations in clinical efficacy, adverse effects, a high rate of clinical discontinuation and drug resistance. Therefore, there is an urgent need for the design and synthesis of more selective and effective inhibitors to tackle these challenges. Through the gathering of this review, we have strived to broaden the extent of our view over the entire scope of quinazoline-based VEGFR-2 inhibitors. Herein, we give an overview of the importance and advancement status of reported structures, highlighting the SAR, biological evaluations and their binding modes.

DCLK1 and tuft cells: Immune-related functions and implications for cancer immunotherapy

DCLK1, a tuft cell marker, is widely expressed in various tumors. Its high expression levels are closely linked to malignant tumor progression, making it a potential tumor-related marker. Recent studies have shed light on the critical roles of DCLK1 and tuft cells in the immune response and the maintenance of epithelial homeostasis, as well as targeted immune escape mechanisms in the tumor microenvironment. This review aims to comprehensively examine the current understanding of immune-related functions mediated by DCLK1 and tuft cells in epithelial tissues, including the roles of relevant cells and important factors involved. Additionally, this review will discuss recent advances in anti-tumor immunity mediated by DCLK1/tuft cells and their potential as immunotherapeutic targets. Furthermore, we will consider the potential impact of DCLK1 targeted therapy in cancer immunotherapy, particularly DCLK1 kinase inhibitors as potential therapeutic drugs in anti-tumor immunity, providing a new perspective and reference for future research.

Representation of older patients in the safety analysis of protein kinase inhibitor registration studies

INTRODUCTION

Older patients (≥65 years old) make up the majority of the cancer population. Older patients seem to experience more adverse events (AEs) from protein kinase inhibitors (PKIs) in clinical practice. Yet they are underrepresented in clinical trials. We aimed to evaluate whether age-related safety differences were described at authorization of PKIs. Representation of older patients in registration studies was also evaluated.

MATERIALS AND METHODS

European Public Assessment Reports (EPARs) of PKIs authorized between 2010 and 2015 were evaluated for the description of age-related safety- and pharmacokinetic differences. The International Council for Harmonization of Technical Requirement for Pharmaceuticals for Human Use (ICH) E7 guideline was applied to EPARs to assess the representation of older patients. Study results were presented descriptively.

RESULTS

Eighteen PKIs with 19 EPARs were analyzed. Age-related safety differences were described in 14 out of 19 EPARs, and age-related pharmacokinetic differences in 1 out of 19 EPARs. More than 100 older patients were included in half of the studies. Older patients were not excluded solely by age, although other inclusion and exclusion criteria negatively influenced enrollment of older patients. None of the PKIs met all criteria from the ICH E7 guideline.

DISCUSSION

Age-related safety differences are described for most PKIs. Older patients were underrepresented in PKI registration studies. Adequate representation of older patients in clinical trials for PKIs is vital, since they make up most of the cancer population.

Reversing pathological cell states: the road less travelled can extend the therapeutic horizon

Acquisition of omics data advances at a formidable pace. Yet, our ability to utilize these data to control cell phenotypes and design interventions that reverse pathological states lags behind. Here, we posit that cell states are determined by core networks that control cell-wide networks. To steer cell fate decisions, core networks connecting genotype to phenotype must be reconstructed and understood. A recent method, cell state transition assessment and regulation (cSTAR), applies perturbation biology to quantify causal connections and mechanistically models how core networks influence cell phenotypes. cSTAR models are akin to digital cell twins enabling us to purposefully convert pathological states back to physiologically normal states. While this capability has a range of applications, here we discuss reverting oncogenic transformation.

Discovery and Synthesis of a Naturally Derived Protein Kinase Inhibitor that Selectively Inhibits Distinct Classes of Serine/Threonine Kinases

The DNAJB1-PRKACA oncogenic gene fusion results in an active kinase enzyme, J-PKAcα, that has been identified as an attractive antitumor target for fibrolamellar hepatocellular carcinoma (FLHCC). A high-throughput assay was used to identify inhibitors of J-PKAcα catalytic activity by screening the NCI Program for Natural Product Discovery (NPNPD) prefractionated natural product library. Purification of the active agent from a single fraction of an Aplidium sp. marine tunicate led to the discovery of two unprecedented alkaloids, aplithianines A (1) and B (2). Aplithianine A (1) showed potent inhibition against J-PKAcα with an IC50 of ∼1 μM in the primary screening assay. In kinome screening, 1 inhibited wild-type PKA with an IC50 of 84 nM. Further mechanistic studies including cocrystallization and X-ray diffraction experiments revealed that 1 inhibited PKAcα catalytic activity by competitively binding to the ATP pocket. Human kinome profiling of 1 against a panel of 370 kinases revealed potent inhibition of select serine/threonine kinases in the CLK and PKG families with IC50 values in the range ∼11-90 nM. An efficient, four-step total synthesis of 1 has been accomplished, enabling further evaluation of aplithianines as biologically relevant kinase inhibitors.

Synthesis and evaluation of potent (iso)ellipticine-based inhibitors of MYLK4 accessed via expeditious synthesis from isoquinolin-5-ol

The K2S2O8-mediated generation of p-iminoquinone contributed to the regioselective substitution of isoquinolin-5,8-dione. This hydroxyl group-guided substitution was also applied to selected heterocycles and addressed the regioselectivity issue of quinones. This study has provided an expeditious pathway from isoquinolin-5-ol (5) to ellipticine (1) and isoellipticine (2), which benefits the comprehensive comparison of their activity. Compounds 1 and 2 displayed marked MYLK4 inhibitory activity with IC50 values of 7.1 and 6.1 nM, respectively. In the cellular activity of AML cells (MV-4-11 and MOLM-13), compound 1 showed better AML activity than compound 2.

Predicting protein and pathway associations for understudied dark kinases using pattern-constrained knowledge graph embedding

The 534 protein kinases encoded in the human genome constitute a large druggable class of proteins that include both well-studied and understudied "dark" members. Accurate prediction of dark kinase functions is a major bioinformatics challenge. Here, we employ a graph mining approach that uses the evolutionary and functional context encoded in knowledge graphs (KGs) to predict protein and pathway associations for understudied kinases. We propose a new scalable graph embedding approach, RegPattern2Vec, which employs regular pattern constrained random walks to sample diverse aspects of node context within a KG flexibly. RegPattern2Vec learns functional representations of kinases, interacting partners, post-translational modifications, pathways, cellular localization, and chemical interactions from a kinase-centric KG that integrates and conceptualizes data from curated heterogeneous data resources. By contextualizing information relevant to prediction, RegPattern2Vec improves accuracy and efficiency in comparison to other random walk-based graph embedding approaches. We show that the predictions produced by our model overlap with pathway enrichment data produced using experimentally validated Protein-Protein Interaction (PPI) data from both publicly available databases and experimental datasets not used in training. Our model also has the advantage of using the collected random walks as biological context to interpret the predicted protein-pathway associations. We provide high-confidence pathway predictions for 34 dark kinases and present three case studies in which analysis of meta-paths associated with the prediction enables biological interpretation. Overall, RegPattern2Vec efficiently samples multiple node types for link prediction on biological knowledge graphs and the predicted associations between understudied kinases, pseudokinases, and known pathways serve as a conceptual starting point for hypothesis generation and testing.

LIMS-Kinase provides sensitive and generalizable label-free in vitro measurement of kinase activity using mass spectrometry

Measurements of kinase activity are important for kinase-directed drug development, analysis of inhibitor structure and function, and understanding mechanisms of drug resistance. Sensitive, accurate, and miniaturized assay methods are crucial for these investigations. Here, we describe a label-free, high-throughput mass spectrometry-based assay for studying individual kinase enzymology and drug discovery in a purified system, with a focus on validated drug targets as benchmarks. We demonstrate that this approach can be adapted to many known kinase substrates and highlight the benefits of using mass spectrometry to measure kinase activity in vitro, including increased sensitivity. We speculate that this approach to measuring kinase activity will be generally applicable across most of the kinome, enabling research on understudied kinases and kinase drug discovery.

Investigation of the Host Kinome Response to Coronavirus Infection Reveals PI3K/mTOR Inhibitors as Betacoronavirus Antivirals

Host kinases play essential roles in the host cell cycle, innate immune signaling, the stress response to viral infection, and inflammation. Previous work has demonstrated that coronaviruses specifically target kinase cascades to subvert host cell responses to infection and rely upon host kinase activity to phosphorylate viral proteins to enhance replication. Given the number of kinase inhibitors that are already FDA approved to treat cancers, fibrosis, and other human disease, they represent an attractive class of compounds to repurpose for host-targeted therapies against emerging coronavirus infections. To further understand the host kinome response to betacoronavirus infection, we employed multiplex inhibitory bead mass spectrometry (MIB-MS) following MERS-CoV and SARS-CoV-2 infection of human lung epithelial cell lines. Our MIB-MS analyses revealed activation of mTOR and MAPK signaling following MERS-CoV and SARS-CoV-2 infection, respectively. SARS-CoV-2 host kinome responses were further characterized using paired phosphoproteomics, which identified activation of MAPK, PI3K, and mTOR signaling. Through chemogenomic screening, we found that clinically relevant PI3K/mTOR inhibitors were able to inhibit coronavirus replication at nanomolar concentrations similar to direct-acting antivirals. This study lays the groundwork for identifying broad-acting, host-targeted therapies to reduce betacoronavirus replication that can be rapidly repurposed during future outbreaks and epidemics. The proteomics, phosphoproteomics, and MIB-MS datasets generated in this study are available in the Proteomics Identification Database (PRIDE) repository under project identifiers PXD040897 and PXD040901.

Development of Kinase-Centric Drugs: A Computational Perspective

Kinases are prominent drug targets in the pharmaceutical and research community due to their involvement in signal transduction, physiological responses, and upon dysregulation, in diseases such as cancer, neurological and autoimmune disorders. Several FDA-approved small-molecule drugs have been developed to combat human diseases since Gleevec was approved for the treatment of chronic myelogenous leukemia. Kinases were considered "undruggable" in the beginning. Several FDA-approved small-molecule drugs have become available in recent years. Most of these drugs target ATP-binding sites, but a few target allosteric sites. Among kinases that belong to the same family, the catalytic domain shows high structural and sequence conservation. Inhibitors of ATP-binding sites can cause off-target binding. Because members of the same family have similar sequences and structural patterns, often complex relationships between kinases and inhibitors are observed. To design and develop drugs with desired selectivity, it is essential to understand the target selectivity for kinase inhibitors. To create new inhibitors with the desired selectivity, several experimental methods have been designed to profile the kinase selectivity of small molecules. Experimental approaches are often expensive, laborious, time-consuming, and limited by the available kinases. Researchers have used computational methodologies to address these limitations in the design and development of effective therapeutics. Many computational methods have been developed over the last few decades, either to complement experimental findings or to forecast kinase inhibitor activity and selectivity. The purpose of this review is to provide insight into recent advances in theoretical/computational approaches for the design of new kinase inhibitors with the desired selectivity and optimization of existing inhibitors.

Data sets of human and mouse protein kinase inhibitors with curated activity data including covalent inhibitors

Aim

Generation of high-quality data sets of protein kinase inhibitors (PKIs).

Methodology

Publicly available PKIs with reliable activity data were curated. PKIs with very weak activity were classified as inactive. Analogue series and PKIs containing reactive groups (warheads) enabling covalent inhibition were systematically identified.

Exemplary results & data

A total of 155,579 human and 3057 mouse PKIs were obtained. Human PKIs were active 440 kinases and included 13,949 covalent PKIs. The collection of qualifying PKIs and corresponding inactive compounds is made available as an open access deposition.

Limitations & next steps

Potential limitations include activity data incompleteness and assay variance. The data set can be used to investigate PKIs with alternative modes of action and calibrate computational methods.

Adjusting the Fitting of Fluorescence-Based Dose-Response Kinase Inhibition Assay to Account for Fluorescent Inhibitors

Fluorescence is routinely used to monitor kinase inhibition in commercial assays. Occasionally fluorescent compounds can interfere with the fluorescent reading. To address this issue, the problematic data are usually truncated to improve the fit, however, this approach raises ethical and reproducibility concerns. Instead, it is suggested to adjust the fitting formula, to account for the autofluorescence of the compounds and improve the fit of the data compared with a naive approach. Finally, it was noticed that truncating the data can result in a small underestimation of the IC50 values and should therefore be used carefully.

SGC-CLK-1: A chemical probe for the Cdc2-like kinases CLK1, CLK2, and CLK4

Small molecule modulators are important tools to study both basic biology and the complex signaling of protein kinases. The cdc2-like kinases (CLK) are a family of four kinases that have garnered recent interest for their involvement in a diverse set of diseases such as neurodegeneration, autoimmunity, and many cancers. Targeted medicinal chemistry around a CLK inhibitor hit identified through screening of a kinase inhibitor set against a large panel of kinases allowed us to identify a potent and selective inhibitor of CLK1, 2, and 4. Here, we present the synthesis, selectivity, and preliminary biological characterization of this compound - SGC-CLK-1 (CAF-170). We further show CLK2 has the highest binding affinity, and high CLK2 expression correlates with a lower IC50 in a screen of multiple cancer cell lines. Finally, we show that SGC-CLK-1 not only reduces serine arginine-rich (SR) protein phosphorylation but also alters SR protein and CLK2 subcellular localization in a reversible way. Therefore, we anticipate that this compound will be a valuable tool for increasing our understanding of CLKs and their targets, SR proteins, at the level of phosphorylation and subcellular localization.

The international clinical trials registry platform (ICTRP): data integrity and the trends in clinical trials, diseases, and drugs

Introduction: Clinical trials are the gold standard for testing new therapies. Databases like ClinicalTrials.gov provide access to trial information, mainly covering the US and Europe. In 2006, WHO introduced the global ICTRP, aggregating data from ClinicalTrials.gov and 17 other national registers, making it the largest clinical trial platform by June 2019. This study conducts a comprehensive global analysis of the ICTRP database and provides framework for large-scale data analysis, data preparation, curation, and filtering. Materials and methods: The trends in 689,793 records from the ICTRP database (covering trials registered from 1990 to 2020) were analyzed. Records were adjusted for duplicates and mapping of agents to drug classes was performed. Several databases, including DrugBank, MESH, and the NIH Drug Information Portal were used to investigate trends in agent classes. Results: Our novel approach unveiled that 0.5% of the trials we identified were hidden duplicates, primarily originating from the EUCTR database, which accounted for 82.9% of these duplicates. However, the overall number of hidden duplicates within the ICTRP seems to be decreasing. In total, 689 793 trials (478 345 interventional) were registered in the ICTRP between 1990 and 2020, surpassing the count of trials in ClinicalTrials.gov (362 500 trials by the end of 2020). We identified 4 865 unique agents in trials with DrugBank, whereas 2 633 agents were identified with NIH Drug Information Portal data. After the ClinicalTrials.gov, EUCTR had the most trials in the ICTRP, followed by CTRI, IRCT, CHiCTR, and ISRCTN. CHiCTR displayed a significant surge in trial registration around 2015, while CTRI experienced rapid growth starting in 2016. Conclusion: This study highlights both the strengths and weaknesses of using the ICTRP as a data source for analyzing trends in clinical trials, and emphasizes the value of utilizing multiple registries for a comprehensive analysis.

p90RSK2, a new MLCK mediates contractility in myosin light chain kinase null smooth muscle

Introduction: Phosphorylation of smooth muscle (SM) myosin regulatory light chain (RLC20) is a critical switch leading to SM contraction. The canonical view held that only the short isoform of myosin light chain kinase (MLCK1) catalyzed this reaction. It is now accepted that auxiliary kinases may contribute to vascular SM tone and contractility. We have previously reported that p90 ribosomal S6 kinase (RSK2) functions as such a kinase, in parallel with MLCK1, contributing ∼25% of the maximal myogenic force in resistance arteries. Thus, RSK2 may be instrumental in the regulation of basal vascular tone and blood pressure. Here, we take advantage of a MLCK1 null mouse (mylk1 -/-) to further test our hypothesis that RSK2 can function as an MLCK, playing a significant physiological role in SM contractility. Methods: Using fetal (E14.5-18.5) SM tissues, as embryos die at birth, we investigated the necessity of MLCK for contractility and fetal development and determined the ability of RSK2 kinase to compensate for the lack of MLCK and characterized its signaling pathway in SM. Results and Discussion: Agonists induced contraction and RLC20 phosphorylation in mylk1 -/- SM was attenuated by RSK2 inhibition. The pCa-tension relationships in permeabilized strips of bladder showed no difference in Ca2+ sensitivity in WT vs mylk1 -/- muscles, although the magnitude of force responses was considerably smaller in the absence of MLCK. The magnitude of contractile responses was similar upon addition of GTPγS to activate the RhoA/ROCK pathway or calyculinA to inhibit the myosin phosphatase. The Ca2+-dependent tyrosine kinase, Pyk2, contributed to RSK2-mediated contractility and RLC20 phosphorylation. Proximity-ligation and immunoprecipitation assays demonstrated an association of RSK2, PDK1 and ERK1/2 with MLCK and actin. RSK2, PDK1, ERK1/2 and MLCK formed a signaling complex on the actin filament, positioning them for interaction with adjacent myosin heads. The Ca2+-dependent component reflected the agonist mediated increases in Ca2+, which activated the Pyk2/PDK1/RSK2 signaling cascade. The Ca2+-independent component was through activation of Erk1/2/PDK1/RSK2 leading to direct phosphorylation of RLC20, to increase contraction. Overall, RSK2 signaling constitutes a new third signaling pathway, in addition to the established Ca2+/CaM/MLCK and RhoA/ROCK pathways to regulate SM contractility.

Linking ATP and allosteric sites to achieve superadditive binding with bivalent EGFR kinase inhibitors

Bivalent molecules consisting of groups connected through bridging linkers often exhibit strong target binding and unique biological effects. However, developing bivalent inhibitors with the desired activity is challenging due to the dual motif architecture of these molecules and the variability that can be introduced through differing linker structures and geometries. We report a set of alternatively linked bivalent EGFR inhibitors that simultaneously occupy the ATP substrate and allosteric pockets. Crystal structures show that initial and redesigned linkers bridging a trisubstituted imidazole ATP-site inhibitor and dibenzodiazepinone allosteric-site inhibitor proved successful in spanning these sites. The reengineered linker yielded a compound that exhibited significantly higher potency (~60 pM) against the drug-resistant EGFR L858R/T790M and L858R/T790M/C797S, which was superadditive as compared with the parent molecules. The enhanced potency is attributed to factors stemming from the linker connection to the allosteric-site group and informs strategies to engineer linkers in bivalent agent design.

An Updated Review on Developing Small Molecule Kinase Inhibitors Using Computer-Aided Drug Design Approaches

Small molecule kinase inhibitors (SMKIs) are of heightened interest in the field of drug research and development. There are 79 (as of July 2023) small molecule kinase inhibitors that have been approved by the FDA and hundreds of kinase inhibitor candidates in clinical trials that have shed light on the treatment of some major diseases. As an important strategy in drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods such as docking, molecular dynamic, quantum mechanics/molecular mechanics, pharmacophore, virtual screening, and quantitative structure-activity relationship have been applied to the design and optimization of small molecule kinase inhibitors. In this review, we provide an overview of recent advances in CADD and SMKIs and the application of CADD in the discovery of SMKIs.

PP2A-based triple-strike therapy overcomes mitochondrial apoptosis resistance in brain cancer cells

Mitochondrial glycolysis and hyperactivity of the phosphatidylinositol 3-kinase-protein kinase B (AKT) pathway are hallmarks of malignant brain tumors. However, kinase inhibitors targeting AKT (AKTi) or the glycolysis master regulator pyruvate dehydrogenase kinase (PDKi) have failed to provide clinical benefits for brain tumor patients. Here, we demonstrate that heterogeneous glioblastoma (GB) and medulloblastoma (MB) cell lines display only cytostatic responses to combined AKT and PDK targeting. Biochemically, the combined AKT and PDK inhibition resulted in the shutdown of both target pathways and priming to mitochondrial apoptosis but failed to induce apoptosis. In contrast, all tested brain tumor cell models were sensitive to a triplet therapy, in which AKT and PDK inhibition was combined with the pharmacological reactivation of protein phosphatase 2A (PP2A) by NZ-8-061 (also known as DT-061), DBK-1154, and DBK-1160. We also provide proof-of-principle evidence for in vivo efficacy in the intracranial GB and MB models by the brain-penetrant triplet therapy (AKTi + PDKi + PP2A reactivator). Mechanistically, PP2A reactivation converted the cytostatic AKTi + PDKi response to cytotoxic apoptosis, through PP2A-elicited shutdown of compensatory mitochondrial oxidative phosphorylation and by increased proton leakage. These results encourage the development of triple-strike strategies targeting mitochondrial metabolism to overcome therapy tolerance in brain tumors.

Validation of an LC-MS/MS assay for rapid and simultaneous quantification of 21 kinase inhibitors in human plasma and serum for therapeutic drug monitoring

Kinase inhibitors have revolutionized cancer treatment in the past 25 years and currently form the cornerstone of many treatments. Due to the increasing evidence for therapeutic drug monitoring (TDM) of kinase inhibitors, the need is growing for new assays to rapidly evaluate kinase inhibitor plasma concentrations. In this study, we developed an LC-MS/MS assay for the rapid and simultaneous quantification of 21 kinase inhibitors. First, a literature search was conducted to ensure that the linear ranges of the analytes were in line with the reported therapeutic windows and/or TDM reference values. Subsequently, the assay was validated according to FDA and EMA guidelines for linearity, selectivity, carry-over, accuracy, precision, dilution integrity, matrix effect, recovery, and stability. The assay was fast, with a short run-time of 2 min per sample. Sample pre-treatment consisted of protein precipitation with methanol enriched with stable isotope-labeled internal standards (SIL-IS), and the mixture was vortexed and centrifuged before sample injection. Separation was achieved using a C18 column (3 μm,50 × 2.1 mm) with a gradient of two mobile phases (ammonium formate buffer pH 3.5 and acetonitrile). Analyte detection was conducted in positive ionization mode using selected reaction monitoring. The assay was accurate and precise in plasma as well as in serum. Extraction recovery ranged between 95.0% and 106.0%, and the matrix effect was 95.7%-105.2%. The stability of the analytes varied at room temperature and in refrigerated conditions. However, all drugs were found to be stable for 7 days in the autosampler. The clinical applicability of the analytical method (486 analyzed samples between 1 July 2022-1 July 2023) as well as external quality control testing results were evaluated. Taken together, the results demonstrate that the analytical method was validated and applicable for routine analyses in clinical practice.

How many kinases are druggable? A review of our current understanding

There are over 500 human kinases ranging from very well-studied to almost completely ignored. Kinases are tractable and implicated in many diseases, making them ideal targets for medicinal chemistry campaigns, but is it possible to discover a drug for each individual kinase? For every human kinase, we gathered data on their citation count, availability of chemical probes, approved and investigational drugs, PDB structures, and biochemical and cellular assays. Analysis of these factors highlights which kinase groups have a wealth of information available, and which groups still have room for progress. The data suggest a disproportionate focus on the more well characterized kinases while much of the kinome remains comparatively understudied. It is noteworthy that tool compounds for understudied kinases have already been developed, and there is still untapped potential for further development in this chemical space. Finally, this review discusses many of the different strategies employed to generate selectivity between kinases. Given the large volume of information available and the progress made over the past 20 years when it comes to drugging kinases, we believe it is possible to develop a tool compound for every human kinase. We hope this review will prove to be both a useful resource as well as inspire the discovery of a tool for every kinase.

C-H Groups as Donors in Hydrogen Bonds: A Historical Overview and Occurrence in Proteins and Nucleic Acids

Hydrogen bonds constitute a unique type of non-covalent interaction, with a critical role in biology. Until fairly recently, the canonical view held that these bonds occur between electronegative atoms, typically O and N, and that they are mostly electrostatic in nature. However, it is now understood that polarized C-H groups may also act as hydrogen bond donors in many systems, including biological macromolecules. First recognized from physical chemistry studies, C-H…X bonds were visualized with X-ray crystallography sixty years ago, although their true significance has only been recognized in the last few decades. This review traces the origins of the field and describes the occurrence and significance of the most important C-H…O bonds in proteins and nucleic acids.

A target map of clinical combination therapies in oncology: an analysis of clinicaltrials.gov

Combination therapies have taken center stage for cancer treatment, however, there is a lack of a comprehensive portrait to quantitatively map the current clinical combination progress. This study aims to capture clinical combination therapies of the validated FDA-approved new oncology drugs by a macro data analysis and to summarize combination mechanisms and strategies in the context of the existing literature. A total of 72 new molecular entities or new therapeutic biological products for cancer treatment approved by the FDA from 2017 to 2021 were identified, and the data on their related 3334 trials were retrieved from the database of ClinicalTrials.gov. Moreover, these sampled clinical trials were refined by activity status and combination relevance and labeled with the relevant clinical arms and drug combinations, as well as drug targets and target pairs. Combination therapies are increasingly prevalent in clinical trials of new oncology drugs. From retrospective work, existing clinical combination therapies in oncology are driven by different patterns (i.e., rational design and industry trends). The former can be represented by mechanism-based or structure-based combinations, such as targeting different domains of HER2 protein or in-series co-targeting in RAF plus MEK inhibitors. The latter is an empirically driven strategy, including redundant combinations in hot targets, such as PD-1/PD-L1, PI3K, CDK4/6, and PARP. Because of an explosion in the number of clinical trials and the resultant shortage of available patients, it is essential to rationally design drug combinations.

Rigid Scaffolds Are Promising for Designing Macrocyclic Kinase Inhibitors

Macrocyclic kinase inhibitors (MKIs) are gaining attention due to their favorable selectivity and potential to overcome drug resistance, yet they remain challenging to design because of their novel structures. To facilitate the design and discovery of MKIs, we investigate MKI rational design starting from initial acyclic compounds by performing microsecond-scale atomistic simulations for multiple MKIs, constructing an MKI database, and analyzing MKIs using hierarchical cluster analysis. Our studies demonstrate that the binding modes of MKIs are like those of their corresponding acyclic counterparts against the same kinase targets. Importantly, within the respective binding sites, the MKI scaffolds retain the same conformations as their corresponding acyclic counterparts, demonstrating the rigidity of scaffolds before and after molecular cyclization. The MKI database includes 641 nanomole-level MKIs from 56 human kinases elucidating the features of rigid scaffolds and the core structures of MKIs. Collectively these results and resources can facilitate MKI development.

Leucettinibs, a Class of DYRK/CLK Kinase Inhibitors Inspired by the Marine Sponge Natural Product Leucettamine B

Dual-specificity, tyrosine phosphorylation-regulated kinases (DYRKs) and cdc2-like kinases (CLKs) recently attracted attention due to their central involvement in various pathologies. We here describe a family of DYRK/CLK inhibitors derived from Leucettines and the marine natural product Leucettamine B. Forty-five N2-functionalized 2-aminoimidazolin-4-ones bearing a fused [6 + 5]-heteroarylmethylene were synthesized. Benzothiazol-6-ylmethylene was selected as the most potent residue among 15 different heteroarylmethylenes. 186 N2-substituted 2-aminoimidazolin-4-ones bearing a benzothiazol-6-ylmethylene, collectively named Leucettinibs, were synthesized and extensively characterized. Subnanomolar IC50 (0.5-20 nM on DYRK1A) inhibitors were identified and one Leucettinib was modeled in DYRK1A and co-crystallized with CLK1 and the weaker inhibited off-target CSNK2A1. Kinase-inactive isomers of Leucettinibs (>3-10 μM on DYRK1A), named iso-Leucettinibs, were synthesized and characterized as suitable negative control compounds for functional experiments. Leucettinibs, but not iso-Leucettinibs, inhibit the phosphorylation of DYRK1A substrates in cells. Leucettinibs provide new research tools and potential leads for further optimization toward therapeutic drug candidates.

Clinical development of new drugs for adults and children with cancer, 2010-2020

BACKGROUND

Many new molecular entities enter clinical development to evaluate potential therapeutic benefits for oncology patients. We characterized adult and pediatric development of the set of new molecular entities that started clinical testing in 2010-2015 worldwide.

METHODS

We extracted data from AdisInsight, an extensive database of global pharmaceutical development, and the FDA.gov website. We followed the cohort of new molecular entities initiating first-in-human phase I clinical trials in 2010-2015 to the end of 2020. For each new molecular entity, we determined whether it was granted US Food and Drug Administration (FDA) approval, studied in a trial open to pediatric enrollment, or stalled during development. We characterized the cumulative incidence of these endpoints using statistical methods for censored data.

RESULTS

The 572 new molecular entities starting first-in-human studies in 2010-2015 were studied in 6142 trials by the end of 2020. Most new molecular entities were small molecules (n = 316, 55.2%), antibodies (n = 148, 25.9%), or antibody-drug conjugates (n = 44, 7.7%). After a mean follow-up of 8.0 years, 173 new molecular entities did not advance beyond first-in-human trials, and 39 were approved by the FDA. New molecular entities had a 10.4% estimated probability (95% confidence interval = 6.6% to 14.1%) of being approved by the FDA within 10 years of first-in-human trials. After a median of 4.6 years since start of first-in-human trials, 67 (11.7%) new molecular entities were tested in trials open to pediatric patients, and 5 (0.9%) were approved for pediatric indications.

CONCLUSIONS

More efficient clinical development strategies are needed to evaluate new cancer therapies, especially for children, and incorporate approaches to ensure knowledge gain from investigational products that stall in development.

Changes in Drug Clinical Trials of Thyroid Diseases in China, 2009-2022

OBJECTIVE

The incidence rate of thyroid diseases increased worldwide. This study aims to overview the changing landscape of drug clinical trials on thyroid disease during 2009-2022.

METHODS

The detailed information of thyroid disease drug trials registered on the National Medical Products Administration (NMPA) Registration and Information Disclosure Platform for Drug Clinical Studies was searched and collected. The thyroid drug clinical trials were analyzed by the characteristics, time trends, indications, and geographical distribution.

RESULTS

Sixty-five thyroid disease drug clinical trials were launched from 2009 to 2022 in China, which included 21 trials in nontumorous thyroid disease and 44 trials in thyroid carcinoma. The number of registered trials of thyroid diseases including thyroid carcinoma and nontumorous thyroid disease increased steadily from 2009 to 2020. Bioequivalence studies accounted for the largest proportion (32[49.2%]), while phase I and Phase II studies both only accounted for 18.5% (12/65). A significant difference was observed in the trials phase, and randomization between thyroid carcinoma and nontumorous thyroid disease. In terms of clinical indications and drug mechanisms, the number of trials in multi-target tyrosine kinase inhibitors for thyroid carcinoma (n=35) ranked first, followed by thyroid hormone for hypothyroidism (n=7), thyrotropin for thyroid carcinoma (n=6). Sixty-five trials were led by 36 principal investigator (PI) units, and more than 30% of PI-leading units were located in Shanghai (n=7) and Beijing (n=4).

CONCLUSION

During the past 13 years, the development of thyroid diseases drugs trials has achieved certain progress in thyroid carcinoma, especially the molecular targeted therapy, yet the development of drug trials on nontumorous thyroid disease was very slow.

Systematic Analysis of Covalent and Allosteric Protein Kinase Inhibitors

In drug discovery, protein kinase inhibitors (PKIs) are intensely investigated as drug candidates in different therapeutic areas. While ATP site-directed, non-covalent PKIs have long been a focal point in protein kinase (PK) drug discovery, in recent years, there has been increasing interest in allosteric PKIs (APKIs), which are expected to have high kinase selectivity. In addition, as compounds acting by covalent mechanisms experience a renaissance in drug discovery, there is also increasing interest in covalent PKIs (CPKIs). There are various reasons for this increasing interest such as the anticipated high potency, prolonged residence times compared to non-competitive PKIs, and other favorable pharmacokinetic properties. Due to the popularity of PKIs for therapeutic intervention, large numbers of PKIs and large volumes of activity data have accumulated in the public domain, providing a basis for large-scale computational analysis. We have systematically searched for CPKIs containing different reactive groups (warheads) and investigated their potency and promiscuity (multi-PK activity) on the basis of carefully curated activity data. For seven different warheads, sufficiently large numbers of CPKIs were available for detailed follow-up analysis. For only three warheads, the median potency of corresponding CPKIs was significantly higher than of non-covalent PKIs. However, for CKPIs with five of seven warheads, there was a significant increase in the median potency of at least 100-fold compared to PKI analogues without warheads. However, in the analysis of multi-PK activity, there was no general increase in the promiscuity of CPKIs compared to non-covalent PKIs. In addition, we have identified 29 new APKIs in X-ray structures of PK-PKI complexes. Among structurally characterized APKIs, 13 covalent APKIs in complexes with five PKs are currently available, enabling structure-based investigation of PK inhibition by covalent-allosteric mechanisms.

Control of human pancreatic beta cell kinome by glucagon-like peptide-1 receptor biased agonism

AIM

To determine the kinase activity profiles of human pancreatic beta cells downstream of glucagon-like peptide-1 receptor (GLP-1R) balanced versus biased agonist stimulations.

MATERIALS AND METHODS

This study analysed the kinomic profiles of human EndoC-βh1 cells following vehicle and GLP-1R stimulation with the pharmacological agonist exendin-4, as well as exendin-4-based biased derivatives exendin-phe1 and exendin-asp3 for acute (10-minute) versus sustained (120-minute) responses, using PamChip protein tyrosine kinase and serine/threonine kinase assays. The raw data were filtered and normalized using BioNavigator. The kinase analyses were conducted with R, mainly including kinase-substrate mapping and Kyoto Encyclopedia of Genes and Genomes pathway analysis.

RESULTS

The present analysis reveals that kinomic responses are distinct for acute versus sustained GLP-1R agonist exposure, with individual responses associated with agonists presenting specific bias profiles. According to pathway analysis, several kinases, including JNKs, PKCs, INSR and LKB1, are important GLP-1R signalling mediators, constituting potential targets for further research on biased GLP-1R downstream signalling.

CONCLUSION

The results from this study suggest that differentially biased exendin-phe1 and exendin-asp3 can modulate distinct kinase interaction networks. Further understanding of these mechanisms will have important implications for the selection of appropriate anti-type 2 diabetes therapies with optimized downstream kinomic profiles.

Second era of molecular-targeted cancer therapies in dogs

The development of molecular biology and bioinformatics using next-generation sequencing has dramatically advanced the identification of molecules involved in various diseases and the elucidation of their pathogenesis. Consequently, many molecular-targeted therapies have been developed in the medical field. In veterinary medicine, the world's first molecular-targeted drug for animals, masitinib, was approved in 2008, followed by the multikinase inhibitor toceranib in 2009. Toceranib was originally approved for mast cell tumors in dogs but has also been shown to be effective in other tumors because of its ability to inhibit molecules involved in angiogenesis. Thus, toceranib has achieved great success as a molecular-targeted cancer therapy for dogs. Although there has been no progress in the development and commercialization of new molecular-targeted drugs for the treatment of cancer since the success of toceranib, several clinical trials have recently reported the administration of novel agents in the research stage to dogs with tumors. This review provides an overview of molecular-targeted drugs for canine tumors, particularly transitional cell carcinomas, and presents some of our recent data.

An Intriguing Purview on the Design of Macrocyclic Inhibitors for Unexplored Protein Kinases through Their Binding Site Comparison

Kinases play an important role in regulating various intracellular signaling pathways that control cell proliferation, differentiation, survival, and other cellular processes, and their deregulation causes more than 400 diseases. Consequently, macrocyclization can be considered a noteworthy approach to developing new therapeutic agents for human diseases. Macrocyclization has emerged as an effective drug discovery strategy over the past decade to improve target selectivity and potency of small molecules. Small compounds with linear structures upon macrocyclization can lead to changes in their physicochemical and biological properties by firmly reducing conformational flexibility. A number of distinct protein kinases exhibit similar binding sites. Comparison of protein binding sites provides crucial insights for drug discovery and development. Binding site similarities are helpful in understanding polypharmacology, identifying potential off-targets, and repurposing known drugs. In this review, we focused on comparing the binding sites of those kinases for which macrocyclic inhibitors are available/studied so far. Furthermore, we calculated the volume of the binding site pocket for each targeted kinase and then compared it with the binding site pocket of the kinase for which only acyclic inhibitors were designed to date. Our review and analysis of several explored kinases might be useful in targeting new protein kinases for macrocyclic drug discovery.

Deuterium in drug discovery: progress, opportunities and challenges

Substitution of a hydrogen atom with its heavy isotope deuterium entails the addition of one neutron to a molecule. Despite being a subtle change, this structural modification, known as deuteration, may improve the pharmacokinetic and/or toxicity profile of drugs, potentially translating into improvements in efficacy and safety compared with the non-deuterated counterparts. Initially, efforts to exploit this potential primarily led to the development of deuterated analogues of marketed drugs through a 'deuterium switch' approach, such as deutetrabenazine, which became the first deuterated drug to receive FDA approval in 2017. In the past few years, the focus has shifted to applying deuteration in novel drug discovery, and the FDA approved the pioneering de novo deuterated drug deucravacitinib in 2022. In this Review, we highlight key milestones in the field of deuteration in drug discovery and development, emphasizing recent and instructive medicinal chemistry programmes and discussing the opportunities and hurdles for drug developers, as well as the questions that remain to be addressed.

Advances in protein kinase drug discovery through targeting gatekeeper mutations

INTRODUCTION

Acquired resistance caused by gatekeeper mutations has become a major challenge for approved kinase inhibitors used in the clinic. Consequently, the development of new-generation inhibitors or degraders to overcome clinical resistance has become an important research focus for the field.

AREAS COVERED

This review summarizes the common gatekeeper mutations in druggable kinases and the constantly evolving inhibitors or degraders designed to overcome single or double mutations of gatekeeper residues. Furthermore, the authors provide their perspectives on the medicinal chemistry strategies for addressing clinical resistance with gatekeeper mutations.

EXPERT OPINION

The authors suggest optimizing kinase inhibitors to interact effectively with gatekeeper residues, altering the binding mode or binding pocket to avoid steric clashes, improving binding affinity with the target, utilizing protein degraders, and developing combination therapy. These approaches have the potential to be effective in overcoming resistance due to gatekeeper residues.

A human proteogenomic-cellular framework identifies KIF5A as a modulator of astrocyte process integrity with relevance to ALS

Genome-wide association studies identified several disease-causing mutations in neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). However, the contribution of genetic variants to pathway disturbances and their cell type-specific variations, especially in glia, is poorly understood. We integrated ALS GWAS-linked gene networks with human astrocyte-specific multi-omics datasets to elucidate pathognomonic signatures. It predicts that KIF5A, a motor protein kinesin-1 heavy-chain isoform, previously detected only in neurons, can also potentiate disease pathways in astrocytes. Using postmortem tissue and super-resolution structured illumination microscopy in cell-based perturbation platforms, we provide evidence that KIF5A is present in astrocyte processes and its deficiency disrupts structural integrity and mitochondrial transport. We show that this may underly cytoskeletal and trafficking changes in SOD1 ALS astrocytes characterised by low KIF5A levels, which can be rescued by c-Jun N-terminal Kinase-1 (JNK1), a kinesin transport regulator. Altogether, our pipeline reveals a mechanism controlling astrocyte process integrity, a pre-requisite for synapse maintenance and suggests a targetable loss-of-function in ALS.

A Novel FYVE Domain-Containing Protein Kinase, PsZFPK1, Plays a Critical Role in Vegetative Growth, Sporangium Formation, Oospore Production, and Virulence in Phytophthora sojae

Proteins containing both FYVE and serine/threonine kinase catalytic (STKc) domains are exclusive to protists. However, the biological function of these proteins in oomycetes has rarely been reported. In the Phytophthora sojae genome database, we identified five proteins containing FYVE and STKc domains, which we named PsZFPK1, PsZFPK2, PsZFPK3, PsZFPK4, and PsZFPK5. In this study, we characterized the biological function of PsZFPK1 using a CRISPR/Cas9-mediated gene replacement system. Compared with the wild-type strain, P6497, the PsZFPK1-knockout mutants exhibited significantly reduced growth on a nutrient-rich V8 medium, while a more pronounced defect was observed on a nutrient-poor Plich medium. The PsZFPK1-knockout mutants also showed a significant increase in sporangium production. Furthermore, PsZFPK1 was found to be essential for oospore production and complete virulence but dispensable for the stress response in P. sojae. The N-terminal region, FYVE and STKc domains, and T602 phosphorylation site were found to be vital for the function of PsZFPK1. Conversely, these domains were not required for the localization of PsZFPK1 protein in the cytoplasm. Our results demonstrate that PsZFPK1 plays a critical role in vegetative growth, sporangium formation, oospore production, and virulence in P. sojae.

In Silico Discovery of 5'-Modified 7-Deoxy-7-ethynyl-4'-thioadenosine as a HASPIN Inhibitor and Its Synergistic Anticancer Effect with the PLK1 Inhibitor

Despite genetic perturbations resulting in embryo lethality for most mitotic kinases, loss of the histone H3 mitotic kinase HASPIN reveals no adverse effect in mice models, establishing HASPIN as a promising target for anticancer therapy. However, developing a HASPIN inhibitor from conventional pharmacophores poses a technical challenge as this atypical kinase shares slight similarities with eukaryotic protein kinases. Chemically modifying a cytotoxic 4'-thioadenosine analogue through high genotoxicity yielded several novel nongenotoxic kinase inhibitors. In silico apporoaches utilizing transcriptomic and chemical similarities with known compounds and KINOMEscan profiles unveiled the HASPIN inhibitor LJ4827. LJ4827's specificity and potency as a HASPIN inhibitor were verified through in vitro kinase assay and X-ray crystallography. HASPIN inhibition by LJ4827 reduced histone H3 phosphorylation and impeded Aurora B recruitment in cancer cell centromeres but not in noncancer cells. Through transcriptome analysis of lung cancer patients, PLK1 was determined as a druggable synergistic partner to complement HASPIN inhibition. Chemical or genetic PLK1 perturbation with LJ4827 effectuated pronounced lung cancer cytotoxicity in vitro and in vivo. Therefore, LJ4827 is a novel anticancer therapeutic for selectively impeding cancer mitosis through potent HASPIN inhibition, and simultaneous HASPIN and PLK1 interference is a promising therapeutic strategy for lung cancer.

Affinity-Based Kinase-Catalyzed Crosslinking to Study Kinase-Substrate Pairs

Phosphorylation of proteins by kinase enzymes is a post-translational modification involved in a myriad of biological events, including cell signaling and disease development. Identifying the interactions between a kinase and its phosphorylated substrate(s) is necessary to characterize phosphorylation-mediated cellular events and encourage development of kinase-targeting drugs. One method for substrate-kinase identification utilizes photocrosslinking γ-phosphate-modified ATP analogues to covalently link kinases to their substrates for subsequent monitoring. Because photocrosslinking ATP analogues require UV light, which could influence cell biology, we report here two ATP analogues, ATP-aryl fluorosulfate (ATP-AFS) and ATP-hexanoyl bromide (ATP-HexBr), that crosslink kinase-substrate pairs via proximity-mediated reactions without the need for UV irradiation. Both ATP-AFS and ATP-HexBr acted as cosubstrates with a variety of kinases for affinity-based crosslinking, with ATP-AFS showing more robust complexes. Importantly, ATP-AFS promoted crosslinking in lysates, which demonstrates compatibility with complex cellular mixtures for future application to kinase-substrate identification.

Narrow funnel-like interaction energy distribution is an indicator of specific protein interaction partner

Protein interaction networks underlie countless biological mechanisms. However, most protein interaction predictions are based on biological evidence that are biased to well-known protein interaction or physical evidence that exhibits low accuracy for weak interactions and requires high computational power. In this study, a novel method has been suggested to predict protein interaction partners by investigating narrow funnel-like interaction energy distribution. In this study, it was demonstrated that various protein interactions including kinases and E3 ubiquitin ligases have narrow funnel-like interaction energy distribution. To analyze protein interaction distribution, modified scores of iRMS and TM-score are introduced. Then, using these scores, algorithm and deep learning model for prediction of protein interaction partner and substrate of kinase and E3 ubiquitin ligase were developed. The prediction accuracy was similar to or even better than that of yeast two-hybrid screening. Ultimately, this knowledge-free protein interaction prediction method will broaden our understanding of protein interaction networks.