High-throughput kinase profiling: a more efficient approach toward the discovery of new kinase inhibitors

Structure-based development of potent and selective type-II kinase inhibitors of RIPK1

Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) functions as a key regulator in inflammation and cell death and is involved in mediating a variety of inflammatory or degenerative diseases. A number of allosteric RIPK1 inhibitors (RIPK1i) have been developed, and some of them have already advanced into clinical evaluation. Recently, selective RIPK1i that interact with both the allosteric pocket and the ATP-binding site of RIPK1 have started to emerge. Here, we report the rational development of a new series of type-II RIPK1i based on the rediscovery of a reported but mechanistically atypical RIPK3i. We also describe the structure-guided lead optimization of a potent, selective, and orally bioavailable RIPK1i, 62, which exhibits extraordinary efficacies in mouse models of acute or chronic inflammatory diseases. Collectively, 62 provides a useful tool for evaluating RIPK1 in animal disease models and a promising lead for further drug development.

Death by a thousand cuts through kinase inhibitor combinations that maximize selectivity and enable rational multitargeting

Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. However, the high sequence and structural conservation of the catalytic kinase domain complicate the development of selective kinase inhibitors. Inhibition of off-target kinases makes it difficult to study the mechanism of inhibitors in biological systems. Current efforts focus on the development of inhibitors with improved selectivity. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target effects. We develop a multicompound-multitarget scoring (MMS) method that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables optimization of inhibitor combinations for multiple on-targets. Using MMS with published kinase inhibitor datasets we determine potent inhibitor combinations for target kinases with better selectivity than the most selective single inhibitor and validate the predicted effect and selectivity of inhibitor combinations using in vitro and in cellulo techniques. MMS greatly enhances selectivity in rational multitargeting applications. The MMS framework is generalizable to other non-kinase biological targets where compound selectivity is a challenge and diverse compound libraries are available.

Design, Synthesis, and Evaluation of (R)-8-((Tetrahydrofuran-2-yl)methyl)pyrido[2,3-d]pyrimidin-7-ones as Novel Selective ACK1 Inhibitors to Combat Acquired Resistance to the Third-Generation EGFR Inhibitor

Activated Cdc42-associated kinase 1 (ACK1) alterations have been considered to mediate bypass acquired resistance to the third-generation EGFR inhibitors (ASK120067 and osimertinib) in NSCLC. Despite many efforts to develop ACK1 small molecule inhibitors, no selective inhibitors have entered clinical trials. We used structure-based drug design to obtain a series of (R)-8-((tetrahydrofuran-2-yl)methyl)pyrido [2,3-d]pyrimidin-7-ones as novel selective ACK1 inhibitors. One of the representative compounds, 10zi, potently inhibited ACK1 kinase with an IC₅₀ of 2.1 nM, while sparing SRC kinase (IC₅₀ = 218.7 nM). Further, 10zi displayed good kinome selectivity in a profiling of 468 kinases. In the ASK120067-resistant lung cancer cell line (67R), 10zi dose-dependently inhibited the phosphorylation of ACK1 and downstream AKT pathway and showed a strong synergistic anti-tumor effect in combination with ASK120067 in vitro. Additionally, 10zi also exhibited reasonable PK profiles with an oral bioavailability of 19.8% at the dose of 10 mg/kg, which provided a promising lead for further development of new anticancer drugs.

Biochemical Discovery, Intracellular Evaluation, and Crystallographic Characterization of Synthetic and Natural Product Adenosine 3',5'-Cyclic Monophosphate-Dependent Protein Kinase A (PKA) Inhibitors

The recent demonstration that adenosine 3',5'-cyclic monophosphate (cAMP)-dependent protein kinase A (PKA) plays an oncogenic role in a number of important cancers has led to a renaissance in drug development interest targeting this kinase. We therefore have established a suite of biochemical, cell-based, and structural biology assays for identifying and evaluating new pharmacophores for PKA inhibition. This discovery process started with a 384-well high-throughput screen of more than 200,000 substances, including fractionated natural product extracts. Identified active compounds were further prioritized in biochemical, biophysical, and cell-based assays. Priority lead compounds were assessed in detail to fully characterize several previously unrecognized PKA pharmacophores including the generation of new X-ray crystallography structures demonstrating unique interactions between PKA and bound inhibitor molecules.

Human Polo-like Kinase Inhibitors as Antiplasmodials

Protein kinases have proven to be a very productive class of therapeutic targets, and over 90 inhibitors are currently in clinical use primarily for the treatment of cancer. Repurposing these inhibitors as antimalarials could provide an accelerated path to drug development. In this study, we identified BI-2536, a known potent human polo-like kinase 1 inhibitor, with low nanomolar antiplasmodial activity. Screening of additional PLK1 inhibitors revealed further antiplasmodial candidates despite the lack of an obvious orthologue of PLKs in Plasmodium. A subset of these inhibitors was profiled for their in vitro killing profile, and commonalities between the killing rate and inhibition of nuclear replication were noted. A kinase panel screen identified PfNEK3 as a shared target of these PLK1 inhibitors; however, phosphoproteome analysis confirmed distinct signaling pathways were disrupted by two structurally distinct inhibitors, suggesting PfNEK3 may not be the sole target. Genomic analysis of BI-2536-resistant parasites revealed mutations in genes associated with the starvation-induced stress response, suggesting BI-2536 may also inhibit an aminoacyl-tRNA synthetase.

Artificial intelligence to guide precision anticancer therapy with multitargeted kinase inhibitors

BACKGROUND

Vast amounts of rapidly accumulating biological data related to cancer and a remarkable progress in the field of artificial intelligence (AI) have paved the way for precision oncology. Our recent contribution to this area of research is CancerOmicsNet, an AI-based system to predict the therapeutic effects of multitargeted kinase inhibitors across various cancers. This approach was previously demonstrated to outperform other deep learning methods, graph kernel models, molecular docking, and drug binding pocket matching.

METHODS

CancerOmicsNet integrates multiple heterogeneous data by utilizing a deep graph learning model with sophisticated attention propagation mechanisms to extract highly predictive features from cancer-specific networks. The AI-based system was devised to provide more accurate and robust predictions than data-driven therapeutic discovery using gene signature reversion.

RESULTS

Selected CancerOmicsNet predictions obtained for "unseen" data are positively validated against the biomedical literature and by live-cell time course inhibition assays performed against breast, pancreatic, and prostate cancer cell lines. Encouragingly, six molecules exhibited dose-dependent antiproliferative activities, with pan-CDK inhibitor JNJ-7706621 and Src inhibitor PP1 being the most potent against the pancreatic cancer cell line Panc 04.03.

CONCLUSIONS

CancerOmicsNet is a promising AI-based platform to help guide the development of new approaches in precision oncology involving a variety of tumor types and therapeutics.

Stereoselective synthesis of 3,4-dihydropyrrolo[1,2-a]pyrazin-1(2H)-one derivatives as PIM kinase inhibitors inspired from marine alkaloids

We previously demonstrated that natural product-inspired 3,4-dihydropyrrolo[1,2-a]pyrazin-1(2H)-ones derivatives delivered potent and selective PIM kinases inhibitors however with non-optimal ADME/PK properties and modest oral bioavailability. Herein, we describe a structure-based scaffold decoration and a stereoselective approach to this chemical class. The synthesis, structure-activity relationship studies, chiral analysis, and pharmacokinetic data of compounds from this inhibitor class are presented herein. Compound 20c demonstrated excellent potency on PIM1 and PIM2 with exquisite kinases selectivity and PK properties that efficiently and dose-dependently promoted c-Myc degradation and appear to be promising lead compounds for further development.

Structural features of the protein kinase domain and targeted binding by small-molecule inhibitors

Protein kinases are key components in cellular signaling pathways as they carry out the phosphorylation of proteins, primarily on Ser, Thr, and Tyr residues. The catalytic activity of protein kinases is regulated, and they can be thought of as molecular switches that are controlled through protein-protein interactions and post-translational modifications. Protein kinases exhibit diverse structural mechanisms of regulation and have been fascinating subjects for structural biologists from the first crystal structure of a protein kinase over 30 years ago, to recent insights into kinase assemblies enabled by the breakthroughs in cryo-EM. Protein kinases are high-priority targets for drug discovery in oncology and other disease settings, and kinase inhibitors have transformed the outcomes of specific groups of patients. Most kinase inhibitors are ATP competitive, deriving potency by occupying the deep hydrophobic pocket at the heart of the kinase domain. Selectivity of inhibitors depends on exploiting differences between the amino acids that line the ATP site and exploring the surrounding pockets that are present in inactive states of the kinase. More recently, allosteric pockets outside the ATP site are being targeted to achieve high selectivity and to overcome resistance to current therapeutics. Here, we review the key regulatory features of the protein kinase family, describe the different types of kinase inhibitors, and highlight examples where the understanding of kinase regulatory mechanisms has gone hand in hand with the development of inhibitors.

KOPI: Kinase inhibitOr Proteome Impact analysis

Kinase inhibitors often exert on/off-target effects, and efficient data analysis is essential for assessing these effects on the proteome. We developed a workflow for rapidly performing such a proteomic assessment, termed as kinase inhibitor proteome impact analysis (KOPI). We demonstrate KOPI’s utility with staurosporine (STS) on the leukemic K562 cell proteome. We identified systematically staurosporine’s non-kinome interactors, and showed for the first time that it caused paradoxical hyper- and biphasic phosphorylation.

1,3-diarylpyrazolones as potential anticancer agents for non-small cell lung cancer: Synthesis and antiproliferative activity evaluation

A series of pyrazolone compounds with different substitution patterns have been synthesized using microwave-assisted methods and evaluated their in vitro antiproliferative activity against human lung adenocarcinoma cell lines (A549 and NCI-H522). Among the tested compounds, the pyrazolone P7 exhibited high antiproliferative activity against both A549 and NCIH522 cancer cell lines while being 10 times less cytotoxic to non-cancerous cells. Moreover, our compounds P7 and P11 exhibited higher antiproliferative activity and selectivity against A549 and NCIH522 cells compared with the clinically approved drugs Afatinib and Gefitinib. The cell cycle analysis showed that the compound P7 and P11 arrests the cell cycle at G0/G1 phase, whereas the compounds P13 and P14 involved in G2/M phase arrest. The results from antiproliferative activity screening, cell cycle analysis, and kinase profiling indicate that the suitably substituted 1,3-diarylpyrazolones exhibit high antiproliferative activity against non-small cell lung cancer cells.

Systems toxicology approach explores target-pathway relationship and adverse health impacts of ubiquitous environmental pollutant bisphenol A

The effects of environmental chemicals on health outcomes may be underestimated due to deficiency of knowledge regarding the actions of compounds on toxico-pathogenic mechanisms underlying biological systems outcomes. In this regard, the current study aimed to explore the potential target-pathway-disease relationship attributed to bisphenol A (BPA) responses in target tissues. Computational methods including reverse pharmacophore mapping approach, structural similarity based search and kinome wide interaction profiling were employed with molecular docking validation. Gene ontology (GO) enrichment analysis and protein-protein interaction (PPI) network based illustrations were utilized to prioritize target-pathway and disease relationships. Data illustrated that BPA possessed multi-target nature since this chemical potentially interacted with various protein targets where many of these were validated through docking. Potential BPA targets were significantly enriched to various cellular signaling pathways including steroid biosynthesis, peroxisome proliferator-activated receptor gamma (PPARℽ) and cancer. Further, hypertension was prioritized as disease target. In addition, BPA targeted 17 cell signaling kinases encompassed in the human kinome. In addition, inflammatory (5-LO) and apoptosis regulators (Bcl-X and Bcl-2) were also explored as novel targets. Evidence indicates that the multi-target nature and plausible mechanisms underlying BPA actions in a system wide manner aids toward understanding of adverse effects. This observation may lead us to more precise method to elucidate the toxico-pathogenic mechanisms of BPA with an environmental health perspective.

Efficient Hit-to-Lead Searching of Kinase Inhibitor Chemical Space via Computational Fragment Merging

In early-stage drug discovery, the hit-to-lead optimization (or "hit expansion") stage entails starting from a newly identified active compound and improving its potency or other properties. Traditionally, this process relies on synthesizing and evaluating a series of analogues to build up structure-activity relationships. Here, we describe a computational strategy focused on kinase inhibitors, intended to expedite the process of identifying analogues with improved potency. Our protocol begins from an inhibitor of the target kinase and generalizes the synthetic route used to access it. By searching for commercially available replacements for the individual building blocks used to make the parent inhibitor, we compile an enumerated library of compounds that can be accessed using the same chemical transformations; these huge libraries can exceed many millions─or billions─of compounds. Because the resulting libraries are much too large for explicit virtual screening, we instead consider alternate approaches to identify the top-scoring compounds. We find that contributions from individual substituents are well described by a pairwise additivity approximation, provided that the corresponding fragments position their shared core in precisely the same way relative to the binding site. This key insight allows us to determine which fragments are suitable for merging into single new compounds and which are not. Further, the use of pairwise approximation allows interaction energies to be assigned to each compound in the library without the need for any further structure-based modeling: interaction energies instead can be reliably estimated from the energies of the component fragments, and the reduced computational requirements allow for flexible energy minimizations that allow the kinase to respond to each substitution. We demonstrate this protocol using libraries built from six representative kinase inhibitors drawn from the literature, which target five different kinases: CDK9, CHK1, CDK2, EGFR^T790M, and ACK1. In each example, the enumerated library includes additional analogues reported by the original study to have activity, and these analogues are successfully prioritized within the library. We envision that the insights from this work can facilitate the rapid assembly and screening of increasingly large libraries for focused hit-to-lead optimization. To enable adoption of these methods and to encourage further analyses, we disseminate the computational tools needed to deploy this protocol.

Small Molecules Targeting Activated Cdc42-Associated Kinase 1 (ACK1/TNK2) for the Treatment of Cancers

Activated Cdc42-associated kinase 1 (ACK1/TNK2) is a nonreceptor tyrosine kinase with a unique structure. It not only can act as an activated transmembrane effector of receptor tyrosine kinases (RTKs) to transmit various RTK signals but also can play a corresponding role in epigenetic regulation. A number of studies have shown that ACK1 is a carcinogenic factor. Blockage of ACK1 has been proven to be able to inhibit cancer cell survival, proliferation, migration, and radiation resistance. Thus, ACK1 is a promising potential antitumor target. To date, despite many efforts to develop ACK1 inhibitors, no specific small molecule inhibitors have entered clinical trials. This Perspective provides an overview of the structural features, biological functions, and association with diseases of ACK1 and in vitro and in vivo activities, selectivity, and therapeutic potential of small molecule ACK1 inhibitors with different chemotypes.

Abemaciclib is a potent inhibitor of DYRK1A and HIP kinases involved in transcriptional regulation

Homeodomain-interacting protein kinases (HIPKs) belong to the CMGC kinase family and are closely related to dual-specificity tyrosine phosphorylation-regulated kinases (DYRKs). HIPKs are regulators of various signaling pathways and involved in the pathology of cancer, chronic fibrosis, diabetes, and multiple neurodegenerative diseases. Here, we report the crystal structure of HIPK3 in its apo form at 2.5 Å resolution. Recombinant HIPKs and DYRK1A are auto-activated and phosphorylate the negative elongation factor SPT5, the transcription factor c-Myc, and the C-terminal domain of RNA polymerase II, suggesting a direct function in transcriptional regulation. Based on a database search, we identified abemaciclib, an FDA-approved Cdk4/Cdk6 inhibitor used for the treatment of metastatic breast cancer, as potent inhibitor of HIPK2, HIPK3, and DYRK1A. We determined the crystal structures of HIPK3 and DYRK1A bound to abemaciclib, showing a similar binding mode to the hinge region of the kinase as observed for Cdk6. Remarkably, DYRK1A is inhibited by abemaciclib to the same extent as Cdk4/Cdk6 in vitro, raising the question of whether targeting of DYRK1A contributes to the transcriptional inhibition and therapeutic activity of abemaciclib.

Structural basis for small molecule targeting of Doublecortin Like Kinase 1 with DCLK1-IN-1

Doublecortin-like kinase 1 (DCLK1) is an understudied bi-functional kinase with a proven role in tumour growth and development. However, the presence of tissue-specific spliced DCLK1 isoforms with distinct biological functions have challenged the development of effective strategies to understand the role of DCLK1 in oncogenesis. Recently, DCLK1-IN-1 was reported as a highly selective DCLK1 inhibitor, a powerful tool to dissect DCLK1 biological functions. Here, we report the crystal structures of DCLK1 kinase domain in complex with DCLK1-IN-1 and its precursors. Combined, our data rationalises the structure-activity relationship that informed the development of DCLK1-IN-1 and provides the basis for the high selectivity of DCLK1-IN-1, with DCLK1-IN-1 inducing a drastic conformational change of the ATP binding site. We demonstrate that DCLK1-IN-1 binds DCLK1 long isoforms but does not prevent DCLK1's Microtubule-Associated Protein (MAP) function. Together, our work provides an invaluable structural platform to further the design of isoform-specific DCLK1 modulators for therapeutic intervention.

Drugging the Undruggable: How Isoquinolines and PKA Initiated the Era of Designed Protein Kinase Inhibitor Therapeutics

In 1984, Japanese researchers led by the biochemist Hiroyoshi Hidaka described the first synthetic protein kinase inhibitors based on an isoquinoline sulfonamide structure (Hidaka et al. Biochemistry, 1984 Oct 9; 23(21): 5036-41. doi: 10.1021/bi00316a032). These led to the first protein kinase inhibitor approved for medical use (fasudil), an inhibitor of the AGC subfamily Rho kinase. With potencies strong enough to compete against endogenous ATP, the isoquinoline compounds established the druggability of the ATP binding site. Crystal structures of their protein kinase complexes, including with cAMP-dependent protein kinase (PKA), showed interactions that, on the one hand, could mimic ATP but, on the other hand, could be optimized for high potency binding, kinase selectivity, and diversification away from adenosine. They also showed the flexibility of the glycine-rich loop, and PKA became a major prototype for crystallographic and nuclear magnetic resonance (NMR) studies of protein kinase mechanism and dynamic activity control. Since fasudil, more than 70 kinase inhibitors have been approved for clinical use, involving efforts that progressively have introduced new paradigms of data-driven drug discovery. Publicly available data alone comprise over 5000 protein kinase crystal structures and hundreds of thousands of binding data. Now, new methods, including artificial intelligence techniques and expansion of protein kinase targeting approaches, together with the expiration of patent protection for optimized inhibitor scaffolds, promise even greater advances in drug discovery. Looking back to the time of the first isoquinoline hinge binders brings the current state-of-the-art into stark contrast. Appropriately for this Perspective article, many of the milestone papers during this time were published in Biochemistry (now ACS Biochemistry).

Computational Approaches for the Design of (Mutant-)Selective Tyrosine Kinase Inhibitors: State-of-the-Art and Future Prospects

Kinases remain one of the major attractive therapeutic targets for a large number of indications such as cancer, rheumatoid arthritis, cardiac failure and many others. Design and development of kinase inhibitors (ATP-competitive, allosteric or covalent) is a clinically validated and successful strategy in the pharmaceutical industry. The perks come with limitations, particularly the development of resistance to highly potent and selective inhibitors. When this happens, the cycle needs to be repeated, i.e., the design and development of kinase inhibitors active against the mutated forms. The complexity of tumor milieu makes it awfully difficult for these molecularly-targeted therapies to work. Every year newer and better versions of these agents are introduced in the clinic. Several computational approaches such as structure-, ligand-based or hybrid ones continue to live up to their potential in discovering novel kinase inhibitors. New schools of thought in this area continue to emerge, e.g., development of dual-target kinase inhibitors. But there are fundamental issues with this approach. It is indeed difficult to selectively optimize binding at two entirely different or related kinases. In addition to the conventional strategies, modern technologies (machine learning, deep learning, artificial intelligence, etc.) started yielding the results and building success stories. Computational tools invariably played a critical role in catalysing the phenomenal progress in kinase drug discovery field. The present review summarized the progress in utilizing computational methods and tools for discovering (mutant-)selective tyrosine kinase inhibitor drugs in the last three years (2017-2019). Representative investigations have been discussed, while others are merely listed. The author believes that the enthusiastic reader will be inspired to dig out the cited literature extensively to appreciate the progress made so far and the future prospects of the field.

Highly selective inhibitors of protein kinases CLK and HIPK with the furo[3,2-b]pyridine core

The furo [3,2-b]pyridine motif represents a relatively underexplored central pharmacophore in the area of kinase inhibitors. Herein, we report flexible synthesis of 3,5-disubstituted furo [3,2-b]pyridines that relies on chemoselective couplings of newly prepared 5-chloro-3-iodofuro [3,2-b]pyridine. This methodology allowed efficient second-generation synthesis of the state-of-the-art chemical biology probe for CLK1/2/4 MU1210, and identification of the highly selective inhibitors of HIPKs MU135 and MU1787 which are presented and characterized in this study, including the X-ray crystal structure of MU135 in HIPK2. chemical biology probe.

A Chemical Probe for Dark Kinase STK17B Derives Its Potency and High Selectivity through a Unique P-Loop Conformation

STK17B is a member of the death-associated protein kinase family and has been genetically linked to the development of diverse diseases. However, the role of STK17B in normal and disease pathology is poorly defined. Here, we present the discovery of thieno[3,2-d] pyrimidine SGC-STK17B-1 (11s), a high-quality chemical probe for this understudied "dark" kinase. 11s is an ATP-competitive inhibitor that showed remarkable selectivity over other kinases including the closely related STK17A. X-ray crystallography of 11s and related thieno[3,2-d]pyrimidines bound to STK17B revealed a unique P-loop conformation characterized by a salt bridge between R41 and the carboxylic acid of the inhibitor. Molecular dynamic simulations of STK17B revealed the flexibility of the P-loop and a wide range of R41 conformations available to the apo-protein. The isomeric thieno[2,3-d]pyrimidine SGC-STK17B-1N (19g) was identified as a negative control compound. The >100-fold lower activity of 19g on STK17B was attributed to the reduced basicity of its pyrimidine N1.

Small molecule strategies to harness the unfolded protein response: where do we go from here?

The unfolded protein response (UPR) plays a central role in regulating endoplasmic reticulum (ER) and global cellular physiology in response to pathologic ER stress. The UPR is comprised of three signaling pathways activated downstream of the ER membrane proteins IRE1, ATF6, and PERK. Once activated, these proteins initiate transcriptional and translational signaling that functions to alleviate ER stress, adapt cellular physiology, and dictate cell fate. Imbalances in UPR signaling are implicated in the pathogenesis of numerous, etiologically-diverse diseases, including many neurodegenerative diseases, protein misfolding diseases, diabetes, ischemic disorders, and cancer. This has led to significant interest in establishing pharmacologic strategies to selectively modulate IRE1, ATF6, or PERK signaling to both ameliorate pathologic imbalances in UPR signaling implicated in these different diseases and define the importance of the UPR in diverse cellular and organismal contexts. Recently, there has been significant progress in the identification and characterization of UPR modulating compounds, providing new opportunities to probe the pathologic and potentially therapeutic implications of UPR signaling in human disease. Here, we describe currently available UPR modulating compounds, specifically highlighting the strategies used for their discovery and specific advantages and disadvantages in their application for probing UPR function. Furthermore, we discuss lessons learned from the application of these compounds in cellular and in vivo models to identify favorable compound properties that can help drive the further translational development of selective UPR modulators for human disease.

Discovery of a series of benzopyrimidodiazepinone TNK2 inhibitors via scaffold morphing

The protein kinase TNK2 (ACK1) is an emerging drug target for a variety of indications, in particular for cancer where it plays a key role transmitting cell survival, growth and proliferative signals via modification of multiple downstream effectors by unique tyrosine phosphorylation events. Scaffold morphing based on our previous TNK2 inhibitor XMD8-87 identified urea 17 from which we developed the potent and selective compound 32. A co-crystal structure was obtained showing 32 interacting primarily with the main chain atoms of an alanine residue of the hinge region. Additional H-bonds exist between the urea NHs and the Thr205 and Asp270 residues.

Protein kinase inhibitors for amyotrophic lateral sclerosis therapy

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder that causes the progressive loss of motoneurons and, unfortunately, there is no effective treatment for this disease. Interconnecting multiple pathological mechanisms are involved in the neuropathology of this disease, including abnormal aggregation of proteins, neuroinflammation and dysregulation of the ubiquitin proteasome system. Such complex mechanisms, together with the lack of reliable animal models of the disease have hampered the development of drugs for this disease. Protein kinases, a key pharmacological target in several diseases, have been linked to ALS as they play a central role in the pathology of many diseases. Therefore several inhibitors are being currently trailed for clinical proof of concept in ALS patients. In this review, we examine the recent literature on protein kinase inhibitors currently in pharmaceutical development for this diseaseas future therapy for AS together with their involvement in the pathobiology of ALS. LINKED ARTICLES: This article is part of a themed issue on Neurochemistry in Japan. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.6/issuetoc.

Synthesis and Structure-Activity Relationships of DCLK1 Kinase Inhibitors Based on a 5,11-Dihydro-6H-benzo[e]pyrimido[5,4-b][1,4]diazepin-6-one Scaffold

Doublecortin-like kinase 1 (DCLK1) is a serine/threonine kinase that is overexpressed in gastrointestinal cancers, including esophageal, gastric, colorectal, and pancreatic cancers. DCLK1 is also used as a marker of tuft cells, which regulate type II immunity in the gut. However, the substrates and functions of DCLK1 are understudied. We recently described the first selective DCLK1/2 inhibitor, DCLK1-IN-1, developed to aid the functional characterization of this important kinase. Here we describe the synthesis and structure-activity relationships of 5,11-dihydro-6H-benzo[e]pyrimido[5,4-b][1,4]diazepin-6-one DCLK1 inhibitors, resulting in the identification of DCLK1-IN-1.

Discovery of a selective inhibitor of doublecortin like kinase 1

Doublecortin like kinase 1 (DCLK1) is an understudied kinase that is upregulated in a wide range of cancers, including pancreatic ductal adenocarcinoma (PDAC). However, little is known about its potential as a therapeutic target. We used chemoproteomic profiling and structure-based design to develop a selective, in vivo-compatible chemical probe of the DCLK1 kinase domain, DCLK1-IN-1. We demonstrate activity of DCLK1-IN-1 against clinically relevant patient-derived PDAC organoid models and use a combination of RNA-sequencing, proteomics and phosphoproteomics analysis to reveal that DCLK1 inhibition modulates proteins and pathways associated with cell motility in this context. DCLK1-IN-1 will serve as a versatile tool to investigate DCLK1 biology and establish its role in cancer.

GraphGR: A graph neural network to predict the effect of pharmacotherapy on the cancer cell growth.. [DOI: 10.1101/2020.05.20.107458]

Genomic profiles of cancer cells provide valuable information on genetic alterations in cancer. Several recent studies employed these data to predict the response of cancer cell lines to treatment with drugs. Nonetheless, due to the multifactorial phenotypes and intricate mechanisms of cancer, the accurate prediction of the effect of pharmacotherapy on a specific cell line based on the genetic information alone is problematic. High prediction accuracies reported in the literature likely result from significant overlaps among training, validation, and testing sets, making many predictors inapplicable to new data. To address these issues, we developed GraphGR, a graph neural network with sophisticated attention propagation mechanisms to predict the therapeutic effects of kinase inhibitors across various tumors. Emphasizing on the system-level complexity of cancer, GraphGR integrates multiple heterogeneous data, such as biological networks, genomics, inhibitor profiling, and genedisease associations, into a unified graph structure. In order to construct diverse and information-rich cancer-specific networks, we devised a novel graph reduction protocol based on not only the topological information, but also the biological knowledge. The performance of GraphGR, properly cross-validated at the tissue level, is 0.83 in terms of the area under the receiver operating characteristics, which is notably higher than those measured for other approaches on the same data. Finally, several new predictions are validated against the biomedical literature demonstrating that GraphGR generalizes well to unseen data, i.e. it can predict therapeutic effects across a variety of cancer cell lines and inhibitors. GraphGR is freely available to the academic community at https://github.com/pulimeng/GraphGR.

Macrophage Syk-PI3Kγ Inhibits Antitumor Immunity: SRX3207, a Novel Dual Syk-PI3K Inhibitory Chemotype Relieves Tumor Immunosuppression

Macrophages (MΦ) play a critical role in tumor growth, immunosuppression, and inhibition of adaptive immune responses in cancer. Hence, targeting signaling pathways in MΦs that promote tumor immunosuppression will provide therapeutic benefit. PI3Kγ has been recently established by our group and others as a novel immuno-oncology target. Herein, we report that an MΦ Syk-PI3K axis drives polarization of immunosuppressive MΦs that establish an immunosuppressive tumor microenvironment in in vivo syngeneic tumor models. Genetic or pharmacologic inhibition of Syk and/or PI3Kγ in MΦs promotes a proinflammatory MΦ phenotype, restores CD8+ T-cell activity, destabilizes HIF under hypoxia, and stimulates an antitumor immune response. Assay for transposase-accessible Chromatin using Sequencing (ATAC-seq) analyses on the bone marrow-derived macrophages (BMDM) show that inhibition of Syk kinase promotes activation and binding of NF-κB motif in SykMC-KO BMDMs, thus stimulating immunostimulatory transcriptional programming in MΦs to suppress tumor growth. Finally, we have developed in silico the "first-in-class" dual Syk/PI3K inhibitor, SRX3207, for the combinatorial inhibition of Syk and PI3K in one small molecule. This chemotype demonstrates efficacy in multiple tumor models and represents a novel combinatorial approach to activate antitumor immunity.

Benzopyrimidodiazepinone inhibitors of TNK2

The SAR of a series of benzopyrimidodiazepinone inhibitors of TNK2 was developed, starting from the potent and selective compound XMD8-87. A diverse set of anilines was introduced in an effort to improve the in vivo PK profile and minimize the risk of quinone diimine formation.

[Ligand-receptor binding kinetics in drug design]

Traditionally, the thermodynamic values of affinity are considered as the main criterion for the development of new drugs. Usually, these values for drugs are measured <i>in vitro</i> at steady concentrations of the receptor and ligand, which are differed from <i>in vivo</i> environment. Recent studies have shown that the kinetics of the process of drug binding to its receptor make significant contribution in the drug effectiveness. This has increased attention in characterizing and predicting the rate constants of association and dissociation of the receptor ligand at the stage of preclinical studies of drug candidates. A drug with a long residence time can determine ligand-receptor selectivity (kinetic selectivity), maintain pharmacological activity of the drug at its low concentration in vivo. The paper discusses the theoretical basis of protein-ligand binding, molecular determinants that control the kinetics of the drug-receptor binding. Understanding the molecular features underlying the kinetics of receptor-ligand binding will contribute to the rational design of drugs with desired properties.

Kinase Chemodiversity from the Arctic: The Breitfussins

In this work, we demonstrate that the indole-oxazole-pyrrole framework of the breitfussin family of natural products is a promising scaffold for kinase inhibition. Six new halogenated natural products, breitfussin C-H (3 - 8) were isolated and characterized from the Arctic, marine hydrozoan Thuiaria breitfussi. The structures of two of the new natural products were also confirmed by total synthesis. Two of the breitfussins (3 and 4) were found to selectively inhibit the survival of several cancer cell lines, with the lowest IC₅₀ value of 340 nM measured against the drug-resistant triple negative breast cancer cell line MDA-MB-468, while leaving the majority of the tested cell lines not or significantly less affected. When tested against panels of protein kinases, 3 gave IC₅₀ and K_d values as low as 200 and 390 nM against the PIM1 and DRAK1 kinases, respectively. The activity was confirmed to be mediated through ATP competitive binding in the ATP binding pocket of the kinases. Furthermore, evaluation of potential off-target and toxicological effects, as well as relevant in vitro ADME parameters for 3 revealed that the breitfussin scaffold holds promise for the development of selective kinase inhibitors.

Discovery of Inhibitors of Aurora/PLK Targets as Anticancer Agents

Aurora and polo-like kinases control the G2/M phase in cell mitosis, which are both considered as crucial targets for cancer cell proliferations. Here, naphthalene-based Aurora/PLK coinhibitors as leading compounds were designed through in silico approach, and a total of 36 derivatives were synthesized. One candidate (AAPK-25) was selected under in vitro cell based high throughput screening with an IC50 value = 0.4 μM to human colon cancer cell HCT-116. A kinome scan assay showed that AAPK-25 was remarkably selective to both Aurora and PLK families. The relevant genome pathways were also depicted by microarray based gene expression analysis. Furthermore, validated from a set of in vitro and in vivo studies, AAPK-25 significantly inhibited the development of the colon cancer growth and prolonged the median survival time at the end of the administration (p < 0.05). To sum up, AAPK-25 has a great potential to be developed for a chemotherapeutic agent in clinical use.

Structural Insights into Characterizing Binding Sites in Epidermal Growth Factor Receptor Kinase Mutants

Over the last two decades epidermal growth factor receptor (EGFR) kinase has become an important target to treat nonsmall cell lung cancer (NSCLC). Currently, three generations of EGFR kinase-targeted small molecule drugs have been FDA approved. They nominally produce a response at the start of treatment and lead to a substantial survival benefit for patients. However, long-term treatment results in acquired drug resistance and further vulnerability to NSCLC. Therefore, novel EGFR kinase inhibitors that specially overcome acquired mutations are urgently needed. To this end, we carried out a comprehensive study of different EGFR kinase mutants using a structural systems pharmacology strategy. Our analysis shows that both wild-type and mutated structures exhibit multiple conformational states that have not been observed in solved crystal structures. We show that this conformational flexibility accommodates diverse types of ligands with multiple types of binding modes. These results provide insights for designing a new generation of EGFR kinase inhibitor that combats acquired drug-resistant mutations through a multiconformation-based drug design strategy.

In Silico Drug-Target Profiling

Pharmacological science is trying to establish the link between chemicals, targets, and disease-related phenotypes. A plethora of chemical proteomics and structural data have been generated, thanks to the target-based approach that has dominated drug discovery at the turn of the century. There is an invaluable source of information for in silico target profiling. Prediction is based on the principle of chemical similarity (similar drugs bind similar targets) or on first principles from the biophysics of molecular interactions. In the first case, compound comparison is made through ligand-based chemical similarity search or through classifier-based machine learning approach. The 3D techniques are based on 3D structural descriptors or energy-based scoring scheme to infer a binding affinity of a compound with its putative target. More recently, a new approach based on compound set metric has been proposed in which a query compound is compared with a whole of compounds associated with a target or a family of targets. This chapter reviews the different techniques of in silico target profiling and their main applications such as inference of unwanted targets, drug repurposing, or compound prioritization after phenotypic-based screening campaigns.

A High-Throughput Immune-Oncology Screen Identifies EGFR Inhibitors as Potent Enhancers of Antigen-Specific Cytotoxic T-lymphocyte Tumor Cell Killing

We developed a screening assay in which luciferized ID8 expressing OVA was cocultured with transgenic CD8+ T cells specifically recognizing the model antigen in an H-2b-restricted manner. The assay was screened with a small-molecule library to identify compounds that inhibit or enhance T cell-mediated killing of tumor cells. Erlotinib, an EGFR inhibitor, was the top compound that enhanced T-cell killing of tumor cells. Subsequent experiments with erlotinib and additional EGFR inhibitors validated the screen results. EGFR inhibitors increased both basal and IFNγ-induced MHC class-I presentation, which enhanced recognition and lysis of tumor cell targets by CD8+ cytotoxic T lymphocytes. The ID8 cell line was also transduced to constitutively express Cas9, and a pooled CRISPR screen, utilizing the same target tumor cell/T-cell assay, identified single-guide (sg)RNAs targeting EGFR that sensitized tumor cells to T cell-mediated killing. Combination of PD-1 blockade with EGFR inhibition showed significant synergistic efficacy in a syngeneic model, further validating EGFR inhibitors as immunomodulatory agents that enhance checkpoint blockade. This assay can be screened in high-throughput with small-molecule libraries and genome-wide CRISPR/Cas9 libraries to identify both compounds and target genes, respectively, that enhance or inhibit T-cell recognition and killing of tumor cells. Retrospective analyses of squamous-cell head and neck cancer (SCCHN) patients treated with the combination of afatinib and pembrolizumab demonstrated a rate of clinical activity exceeding that of each single agent. Prospective clinical trials evaluating the combination of an EGFR inhibitor and PD-1 blockade should be conducted.

Drug Discovery Maps, a Machine Learning Model That Visualizes and Predicts Kinome-Inhibitor Interaction Landscapes

The interpretation of high-dimensional structure-activity data sets in drug discovery to predict ligand-protein interaction landscapes is a challenging task. Here we present Drug Discovery Maps (DDM), a machine learning model that maps the activity profile of compounds across an entire protein family, as illustrated here for the kinase family. DDM is based on the t-distributed stochastic neighbor embedding (t-SNE) algorithm to generate a visualization of molecular and biological similarity. DDM maps chemical and target space and predicts the activities of novel kinase inhibitors across the kinome. The model was validated using independent data sets and in a prospective experimental setting, where DDM predicted new inhibitors for FMS-like tyrosine kinase 3 (FLT3), a therapeutic target for the treatment of acute myeloid leukemia. Compounds were resynthesized, yielding highly potent, cellularly active FLT3 inhibitors. Biochemical assays confirmed most of the predicted off-targets. DDM is further unique in that it is completely open-source and available as a ready-to-use executable to facilitate broad and easy adoption.

Structural and Atropisomeric Factors Governing the Selectivity of Pyrimido-benzodiazipinones as Inhibitors of Kinases and Bromodomains

Bromodomains have been pursued intensively over the past several years as emerging targets for the development of anticancer and anti-inflammatory agents. It has recently been shown that some kinase inhibitors are able to potently inhibit the bromodomains of BRD4. The clinical activities of PLK inhibitor BI-2536 and JAK2-FLT3 inhibitor TG101348 have been attributed to this unexpected polypharmacology, indicating that dual-kinase/bromodomain activity may be advantageous in a therapeutic context. However, for target validation and biological investigation, a more selective target profile is desired. Here, we report that benzo[e]pyrimido-[5,4- b]diazepine-6(11H)-ones, versatile ATP-site directed kinase pharmacophores utilized in the development of inhibitors of multiple kinases, including several previously reported kinase chemical probes, are also capable of exhibiting potent BRD4-dependent pharmacology. Using a dual kinase-bromodomain inhibitor of the kinase domains of ERK5 and LRRK2, and the bromodomain of BRD4 as a case study, we define the structure-activity relationships required to achieve dual kinase/BRD4 activity, as well as how to direct selectivity toward inhibition of either ERK5 or BRD4. This effort resulted in identification of one of the first reported kinase-selective chemical probes for ERK5 (JWG-071), a BET selective inhibitor with 1 μM BRD4 IC₅₀ (JWG-115), and additional inhibitors with rationally designed polypharmacology (JWG-047, JWG-069). Co-crystallography of seven representative inhibitors with the first bromodomain of BRD4 demonstrate that distinct atropisomeric conformers recognize the kinase ATP-site and the BRD4 acetyl lysine binding site, conformational preferences supported by rigid docking studies.

Role of Endogenous Metabolite Alterations in Neuropsychiatric Disease

The potential role in neuropsychiatric disease risk arising from alterations and derangements of endogenous small-molecule metabolites remains understudied. Alterations of endogenous metabolite concentrations can arise in multiple ways. Marked derangements of single endogenous small-molecule metabolites are found in a large group of rare genetic human diseases termed "inborn errors of metabolism", many of which are associated with prominent neuropsychiatric symptomology. Whether such metabolites act neuroactively to directly lead to distinct neural dysfunction has been frequently hypothesized but rarely demonstrated unequivocally. Here we discuss this disease concept in the context of our recent findings demonstrating that neural dysfunction arising from accumulation of the schizophrenia-associated metabolite l-proline is due to its structural mimicry of the neurotransmitter GABA that leads to alterations in GABA-ergic short-term synaptic plasticity. For cases in which a similar direct action upon neurotransmitter binding sites is suspected, we lay out a systematic approach that can be extended to assessing the potential disruptive action of such candidate disease metabolites. To address the potentially important and broader role in neuropsychiatric disease, we also consider whether the more subtle yet more ubiquitous variations in endogenous metabolites arising from natural allelic variation may likewise contribute to disease risk but in a more complex and nuanced manner.

Novel Scaffolds for Dual Specificity Tyrosine-Phosphorylation-Regulated Kinase (DYRK1A) Inhibitors

DYRK1A is one of five members of the dual-specificity tyrosine (Y) phosphorylation-regulated kinase (DYRK) family. The DYRK1A gene is located in the Down syndrome critical region and regulates cellular processes related to proliferation and differentiation of neuronal progenitor cells during early development. This has focused research on its role in neuronal degenerative diseases, including Alzheimer's and Down syndrome. Recent studies have also shown a possible role of DYRK1A in diabetes. Here we report a variety of scaffolds not generally known for DYRK1A inhibition, demonstrating their effects in in vitro assays and also in cell cultures. These inhibitors effectively block the tau phosphorylation that is a hallmark of Alzheimer's disease. The crystal structures of these inhibitors support the design of optimized and novel therapeutics.

Reconciling Selectivity Trends from a Comprehensive Kinase Inhibitor Profiling Campaign with Known Activity Data

Kinase inhibitors are among the most intensely investigated compounds in medicinal chemistry and drug development. Profiling experiments and kinome screens reveal binding characteristics of kinase inhibitors and lead to better understanding of selectivity and promiscuity patterns. However, only limited amounts of profiling data are publicly available. By contrast, a large body of activity data for inhibitors of human kinases has become available from medicinal chemistry. In this study, we have correlated selectivity assessment of clinical kinase inhibitors from the most comprehensive profiling campaign reported to date with systematic mining of activity data from other sources. The results of our comparative analysis reveal consistency of orthogonal approaches in the study of kinase inhibitor selectivity versus promiscuity and stress the importance of taking alternative data confidence criteria into account. Moreover, it is also shown that there are little if any detectable differences in selectivity between type I and II kinase inhibitors and that inhibitors designated as chemical probes have very different target profiles.

HIPK2-Mediated Transcriptional Control of NMDA Receptor Subunit Expression Regulates Neuronal Survival and Cell Death

NMDA receptors are critical for neuronal communication. Dysfunction in NMDA receptors has been implicated in neuropsychiatric diseases. While it is well recognized that the composition of NMDA receptors undergoes a GluN2B-to-GluN2A switch in early postnatal life, the mechanism regulating this switch remains unclear. Using transcriptomic and functional analyses in brain tissues from male and female Hipk2^+/+ and Hipk2^-/- mice, we showed that the HIPK2-JNK-c-Jun pathway is important in suppressing the transcription of Grin2a and Grin2c, which encodes the GluN2A and GluN2C subunits of the NMDA receptors, respectively. Loss of HIPK2 leads to a significant decrease in JNK-c-Jun signaling, which in turn derepresses the transcription of Grin2a and Grin2c mRNA and upregulates GluN2A and GluN2C protein levels. These changes result in a significant increase of GluN2A/GluN2B ratio in synapse and mitochondria, a persistent activation of the ERK-CREB pathway and the upregulation of synaptic activity-regulated genes, which collectively contribute to the resistance of Hipk2^-/- neurons to cell death induced by mitochondrial toxins.SIGNIFICANCE STATEMENT We identify HIPK2-JNK-c-Jun signaling as a key mechanism that regulates the transcription of NMDA receptor subunits GluN2A and GluN2C in vivo Our results provide insights into a previously unrecognized molecular mechanism that control the switch of NMDA receptor subunits in early postnatal brain development. Furthermore, we provide evidence that changes in the ratio of NMDA subunits GluN2A/GluN2B can also be detected in the synapse and mitochondria, which contributes to a persistent activation of the prosurvival ERK-CREB pathway and its downstream target genes. Collectively, these changes protect HIPK2 deficient neurons from mitochondrial toxins.

Kinase inhibitors: the road ahead

Receptor tyrosine kinase signalling pathways have been successfully targeted to inhibit proliferation and angiogenesis for cancer therapy. However, kinase deregulation has been firmly demonstrated to play an essential role in virtually all major disease areas. Kinase inhibitor drug discovery programmes have recently broadened their focus to include an expanded range of kinase targets and therapeutic areas. In this Review, we provide an overview of the novel targets, biological processes and disease areas that kinase-targeting small molecules are being developed against, highlight the associated challenges and assess the strategies and technologies that are enabling efficient generation of highly optimized kinase inhibitors.

Exploring Selectivity of Multikinase Inhibitors across the Human Kinome

Selectivity of kinase inhibitors, or the lack thereof, continues to be an intensely debated topic in drug discovery research. Especially, type I inhibitors, which represent most of the currently available kinase inhibitors, are often thought to lack selectivity because they target the largely conserved adenosine triphosphate-binding site in kinases. Herein, we present a large-scale analysis of potential selectivity among multikinase inhibitors, covering 141 human kinases and more than 10 000 qualifying compounds. By design, the analysis was focused on type I inhibitors and carried out at the level of systematically generated kinase pairs sharing inhibitors. Kinase pair category- and compound-based selectivity profiles identified in part highly selective inhibitors for many kinases. Sets of inhibitors associated with kinase pairs frequently contained nonselective as well as increasingly selective compounds. Selectivity of inhibitors did not result from gatekeeper residues settings or phylogenetic distance of kinases. Rather, it was most likely attributable to subtle differences between binding regions in kinases. Taken together, the results of our study reveal that many multikinase inhibitors are more selective than one might assume.

Progress with covalent small-molecule kinase inhibitors

With reduced risk of toxicity and high selectivity, covalent small-molecule kinase inhibitors (CSKIs) have emerged rapidly. Through the lens of structural system pharmacology, here we review this rapid progress by considering design strategies and the challenges and opportunities offered by current CSKIs.

Overcoming Resistance to the THZ Series of Covalent Transcriptional CDK Inhibitors

Irreversible inhibition of transcriptional cyclin-dependent kinases (CDKs) provides a therapeutic strategy for cancers that rely on aberrant transcription; however, lack of understanding of resistance mechanisms to these agents will likely impede their clinical evolution. Here, we demonstrate upregulation of multidrug transporters ABCB1 and ABCG2 as a major mode of resistance to THZ1, a covalent inhibitor of CDKs 7, 12, and 13 in neuroblastoma and lung cancer. To counter this obstacle, we developed a CDK inhibitor, E9, that is not a substrate for ABC transporters, and by selecting for resistance, determined that it exerts its cytotoxic effects through covalent modification of cysteine 1039 of CDK12. These results highlight the importance of considering this common mode of resistance in the development of clinical analogs of THZ1, identify a covalent CDK12 inhibitor that is not susceptible to ABC transporter-mediated drug efflux, and demonstrate that target deconvolution can be accomplished through selection for resistance.