A small molecule-kinase interaction map for clinical kinase inhibitors

Hijacking monopolar spindle 1 (MPS1) for various cancer types by small molecular inhibitors: Deep insights from a decade of research and patents

Monopolar spindle 1 (MPS1) has garnered significant attention due to its pivotal role in regulating the cell cycle. Anomalous expression and hyperactivation of MPS1 have been associated with the onset and advancement of diverse cancers, positioning it as a promising target for therapeutic interventions. This review focuses on MPS1 small molecule inhibitors from the past decade, exploring design strategies, structure-activity relationships (SAR), safety considerations, and clinical performance. Notably, we propose prospects for MPS1 degraders based on proteolysis targeting chimeras (PROTACs), as well as reversible covalent bonding as innovative MPS1 inhibitor design strategies. The objective is to provide valuable information for future development and novel perspectives on potential MPS1 inhibitors.

Pyridopyrimidinones as a new chemotype of calcium dependent protein kinase 1 (CDPK1) inhibitors for Cryptosporidium

The protozoan protein kinase calcium-dependent protein kinase 1 (CDPK1) has emerged as a potential therapeutic target for the treatment of cryptosporidiosis. A focused screen of known kinase inhibitors identified a pyridopyrimidinone as a new chemotype of Cryptosporidium parvum (Cp) CDPK1 inhibitors. Structural comparison of CpCDPK1 to two representative human kinases, RIPK2 and Src, revealed differences in the positioning of the αC-helix that was used in the design of a potent pyridopyrimidinone-based CpCDPK1 inhibitor 7 (a.k.a. UH15-16, IC50 = 10nM), which blocked the growth of three C. parvum strains (EC50 = 12-40nM) as well as C. hominis (EC50 = 85nM) in HCT-8 host cells. Pharmacokinetic and tissue distribution analyses indicated that 7 had low systemic exposure after oral administration, but high gastrointestinal concentration, as well as good Caco-2 cell permeability. Finally, 7 demonstrated partial efficacy in an IL-12 knock-out mouse model of acute cryptosporidiosis.

CK1δ/ε kinases regulate TDP-43 phosphorylation and are therapeutic targets for ALS-related TDP-43 hyperphosphorylation

Hyperphosphorylated TAR DNA-binding protein 43 (TDP-43) aggregates in the cytoplasm of neurons is the neuropathological hallmark of amyotrophic lateral sclerosis (ALS) and a group of neurodegenerative diseases collectively referred to as TDP-43 proteinopathies that includes frontotemporal dementia, Alzheimer's disease, and limbic onset age-related TDP-43 encephalopathy. The mechanism of TDP-43 phosphorylation is poorly understood. Previously we reported casein kinase 1 epsilon gene (CSNK1E gene encoding CK1ε protein) as being tightly correlated with phosphorylated TDP-43 (pTDP-43) pathology. Here we pursued studies to investigate in cellular models and in vitro how CK1ε and CK1δ (a closely related family sub-member) mediate TDP-43 phosphorylation in disease. We first validated the binding interaction between TDP-43 and either CK1δ and CK1ε using kinase activity assays and predictive bioinformatic database. We utilized novel inducible cellular models that generated translocated phosphorylated TDP-43 (pTDP-43) and cytoplasmic aggregation. Reducing CK1 kinase activity with siRNA or small molecule chemical inhibitors resulted in significant reduction of pTDP-43, in both soluble and insoluble protein fractions. We also established CK1δ and CK1ε are the primary kinases that phosphorylate TDP-43 compared to CK2α, CDC7, ERK1/2, p38α/MAPK14, and TTBK1, other identified kinases that have been implicated in TDP-43 phosphorylation. Throughout our studies, we were careful to examine both the soluble and insoluble TDP-43 protein fractions, the critical protein fractions related to protein aggregation diseases. These results identify CK1s as critical kinases involved in TDP-43 hyperphosphorylation and aggregation in cellular models and in vitro, and in turn are potential therapeutic targets by way of CK1δ/ε inhibitors.

Toward structure-multiple activity relationships (SMARts) using computational approaches: A polypharmacological perspective

In the current era of biological big data, which are rapidly populating the biological chemical space, in silico polypharmacology drug design approaches help to decode structure-multiple activity relationships (SMARts). Current computational methods can predict or categorize multiple properties simultaneously, which aids the generation, identification, curation, prioritization, optimization, and repurposing of molecules. Computational methods have generated opportunities and challenges in medicinal chemistry, pharmacology, food chemistry, toxicology, bioinformatics, and chemoinformatics. It is anticipated that computer-guided SMARts could contribute to the full automatization of drug design and drug repurposing campaigns, facilitating the prediction of new biological targets, side and off-target effects, and drug-drug interactions.

Decoding Arabidopsis thaliana CPK/SnRK Superfamily Kinase Client Signaling Networks Using Peptide Library and Mass Spectrometry

Members of the calcium-dependent protein kinase (CDPK/CPK) and SNF-related protein kinase (SnRK) superfamilies are commonly found in plants and some protists. Our knowledge of client specificity of the members of this superfamily is fragmentary. As this family is represented by over 30 members in Arabidopsis thaliana, the identification of kinase-specific and overlapping client relationships is crucial to our understanding the nuances of this large family of kinases as directed towards signal transduction pathways. Herein, we used the kinase client (KiC) assay-a relative, quantitative, high-throughput mass spectrometry-based in vitro phosphorylation assay-to identify and characterize potential CPK/SnRK targets of Arabidopsis. Eight CPKs (1, 3, 6, 8, 17, 24, 28, and 32), four SnRKs (subclass 1 and 2), and PPCK1 and PPCK2 were screened against a synthetic peptide library that contains 2095 peptides and 2661 known phosphorylation sites. A total of 625 in vitro phosphorylation sites corresponding to 203 non-redundant proteins were identified. The most promiscuous kinase, CPK17, had 105 candidate target proteins, many of which had already been discovered. Sequence analysis of the identified phosphopeptides revealed four motifs: LxRxxS, RxxSxxR, RxxS, and LxxxxS, that were significantly enriched among CPK/SnRK clients. The results provide insight into both CPK- and SnRK-specific and overlapping signaling network architectures and recapitulate many known in vivo relationships validating this large-scale approach towards discovering kinase targets.

Discovery and Preclinical Characterization of BIIB129, a Covalent, Selective, and Brain-Penetrant BTK Inhibitor for the Treatment of Multiple Sclerosis

Multiple sclerosis (MS) is a chronic disease with an underlying pathology characterized by inflammation-driven neuronal loss, axonal injury, and demyelination. Bruton's tyrosine kinase (BTK), a nonreceptor tyrosine kinase and member of the TEC family of kinases, is involved in the regulation, migration, and functional activation of B cells and myeloid cells in the periphery and the central nervous system (CNS), cell types which are deemed central to the pathology contributing to disease progression in MS patients. Herein, we describe the discovery of BIIB129 (25), a structurally distinct and brain-penetrant targeted covalent inhibitor (TCI) of BTK with an unprecedented binding mode responsible for its high kinome selectivity. BIIB129 (25) demonstrated efficacy in disease-relevant preclinical in vivo models of B cell proliferation in the CNS, exhibits a favorable safety profile suitable for clinical development as an immunomodulating therapy for MS, and has a low projected total human daily dose.

The state of the art in secondary pharmacology and its impact on the safety of new medicines

Secondary pharmacology screening of investigational small-molecule drugs for potentially adverse off-target activities has become standard practice in pharmaceutical research and development, and regulatory agencies are increasingly requesting data on activity against targets with recognized adverse effect relationships. However, the screening strategies and target panels used by pharmaceutical companies may vary substantially. To help identify commonalities and differences, as well as to highlight opportunities for further optimization of secondary pharmacology assessment, we conducted a broad-ranging survey across 18 companies under the auspices of the DruSafe leadership group of the International Consortium for Innovation and Quality in Pharmaceutical Development. Based on our analysis of this survey and discussions and additional research within the group, we present here an overview of the current state of the art in secondary pharmacology screening. We discuss best practices, including additional safety-associated targets not covered by most current screening panels, and present approaches for interpreting and reporting off-target activities. We also provide an assessment of the safety impact of secondary pharmacology screening, and a perspective on opportunities and challenges in this rapidly developing field.

Identification and characterization of a potent and selective HUNK inhibitor for treatment of HER2+ breast cancer

Human epidermal growth factor receptor 2 (HER2)-targeted agents have proven to be effective, however, the development of resistance to these agents has become an obstacle in treating HER2+ breast cancer. Evidence implicates HUNK as an anti-cancer target for primary and resistant HER2+ breast cancers. In this study, a selective inhibitor of HUNK is characterized alongside a phosphorylation event in a downstream substrate of HUNK as a marker for HUNK activity in HER2+ breast cancer. Rubicon has been established as a substrate of HUNK that is phosphorylated at serine (S) 92. Findings indicate that HUNK-mediated phosphorylation of Rubicon at S92 promotes both autophagy and tumorigenesis in HER2/neu+ breast cancer. HUNK inhibition prevents Rubicon S92 phosphorylation in HER2/neu+ breast cancer models and inhibits tumorigenesis. This study characterizes a downstream phosphorylation event as a measure of HUNK activity and identifies a selective HUNK inhibitor that has meaningful efficacy toward HER2+ breast cancer.

Psychoplastogenic DYRK1A Inhibitors with Therapeutic Effects Relevant to Alzheimer's Disease

Tauopathy, neuronal atrophy, and psychological impairments are hallmarks of neurodegenerative diseases, such as Alzheimer's disease, that currently lack efficacious clinical treatments capable of rectifying these issues. To address these unmet needs, we used rational drug design to combine the pharmacophores of DYRK1A inhibitors and isoDMTs to develop psychoplastogenic DYRK1A inhibitors. Using this approach, we discovered a nonhallucinogenic compound capable of promoting cortical neuron growth and suppressing tau hyperphosphorylation while also having the potential to mitigate the biological and psychological symptoms of dementia. Together, our results suggest that hybridization of the DYRK1A and psychoplastogen pharmacophores represents a promising strategy for identifying compounds that might address the cognitive as well as the behavioral and psychological symptoms of dementia.

Identification of potent pan-ephrin receptor kinase inhibitors using DNA-encoded chemistry technology

EPH receptors (EPHs), the largest family of tyrosine kinases, phosphorylate downstream substrates upon binding of ephrin cell surface-associated ligands. In a large cohort of endometriotic lesions from individuals with endometriosis, we found that EPHA2 and EPHA4 expressions are increased in endometriotic lesions relative to normal eutopic endometrium. Because signaling through EPHs is associated with increased cell migration and invasion, we hypothesized that chemical inhibition of EPHA2/4 could have therapeutic value. We screened DNA-encoded chemical libraries (DECL) to rapidly identify EPHA2/4 kinase inhibitors. Hit compound, CDD-2693, exhibited picomolar/nanomolar kinase activity against EPHA2 (Ki: 4.0 nM) and EPHA4 (Ki: 0.81 nM). Kinome profiling revealed that CDD-2693 bound to most EPH family and SRC family kinases. Using NanoBRET target engagement assays, CDD-2693 had nanomolar activity versus EPHA2 (IC50: 461 nM) and EPHA4 (IC50: 40 nM) but was a micromolar inhibitor of SRC, YES, and FGR. Chemical optimization produced CDD-3167, having picomolar biochemical activity toward EPHA2 (Ki: 0.13 nM) and EPHA4 (Ki: 0.38 nM) with excellent cell-based potency EPHA2 (IC50: 8.0 nM) and EPHA4 (IC50: 2.3 nM). Moreover, CDD-3167 maintained superior off-target cellular selectivity. In 12Z endometriotic epithelial cells, CDD-2693 and CDD-3167 significantly decreased EFNA5 (ligand) induced phosphorylation of EPHA2/4, decreased 12Z cell viability, and decreased IL-1β-mediated expression of prostaglandin synthase 2 (PTGS2). CDD-2693 and CDD-3167 decreased expansion of primary endometrial epithelial organoids from patients with endometriosis and decreased Ewing's sarcoma viability. Thus, using DECL, we identified potent pan-EPH inhibitors that show specificity and activity in cellular models of endometriosis and cancer.

Natural Compounds for Bone Remodeling: A Computational and Experimental Approach Targeting Bone Metabolism-Related Proteins

Osteoporosis, characterized by reduced bone density and increased fracture risk, affects over 200 million people worldwide, predominantly older adults and postmenopausal women. The disruption of the balance between bone-forming osteoblasts and bone-resorbing osteoclasts underlies osteoporosis pathophysiology. Standard treatment includes lifestyle modifications, calcium and vitamin D supplementation and specific drugs that either inhibit osteoclasts or stimulate osteoblasts. However, these treatments have limitations, including side effects and compliance issues. Natural products have emerged as potential osteoporosis therapeutics, but their mechanisms of action remain poorly understood. In this study, we investigate the efficacy of natural compounds in modulating molecular targets relevant to osteoporosis, focusing on the Mitogen-Activated Protein Kinase (MAPK) pathway and the gut microbiome's influence on bone homeostasis. Using an in silico and in vitro methodology, we have identified quercetin as a promising candidate in modulating MAPK activity, offering a potential therapeutic perspective for osteoporosis treatment.

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

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

Data-oriented protein kinase drug discovery

The continued growth of data from biological screening and medicinal chemistry provides opportunities for data-driven experimental design and decision making in early-phase drug discovery. Approaches adopted from data science help to integrate internal and public domain data and extract knowledge from historical in-house data. Protein kinase (PK) drug discovery is an exemplary area where large amounts of data are accumulating, providing a valuable knowledge base for discovery projects. Herein, the evolution of PK drug discovery and development of small molecular PK inhibitors (PKIs) is reviewed, highlighting milestone developments in the field and discussing exemplary studies providing a basis for increasing data orientation of PK discovery efforts.

Design and Synthesis of Novel Macrocyclic Derivatives as Potent and Selective Cyclin-Dependent Kinase 7 Inhibitors

The duality of function (cell cycle regulation and gene transcription) of cyclin-dependent kinase 7 (CDK7) makes it an attractive oncology target and the discovery of CDK7 inhibitors has been a long-term pursuit by academia and pharmaceutical companies. However, achieving selective leading compounds is still difficult owing to the similarities among the ATP binding pocket. Herein, we detail the design and synthesis of a series of macrocyclic derivatives with pyrazolo[1,5-a]-1,3,5-triazine core structure as potent and selective CDK7 inhibitors. The diverse manners of macrocyclization led to distinguished selectivity profiles of the CDK family. Molecular dynamics (MD) simulation explained the binding difference between 15- and 16-membered macrocyclic compounds. Further optimization generated compound 37 exhibiting good CDK7 inhibitory activity and high selectivity over other CDKs. This work clearly demonstrated macrocyclization is a versatile method to finely tune the selectivity profile of small molecules and MD simulation can be a valuable tool in prioritizing designs of the macrocycle.

Evolution of Minimally Invasive and Non-Invasive Preimplantation Genetic Testing: An Overview

Preimplantation genetic testing (PGT) has become a common supplementary diagnοstic/testing tοol for in vitro fertilization (ΙVF) cycles due to a significant increase in cases of PGT fοr mοnogenic cοnditions (ΡGT-M) and de novο aneuplοidies (ΡGT-A) over the last ten years. This tendency is mostly attributable to the advancement and application of novel cytogenetic and molecular techniques in clinical practice that are capable of providing an efficient evaluation of the embryonic chromosomal complement and leading to better IVF/ICSI results. Although PGT is widely used, it requires invasive biopsy of the blastocyst, which may harm the embryo. Non-invasive approaches, like cell-free DNA (cfDNA) testing, have lower risks but have drawbacks in consistency and sensitivity. This review discusses new developments and opportunities in the field of preimplantation genetic testing, enhancing the overall effectiveness and accessibility of preimplantation testing in the framework of developments in genomic sequencing, bioinformatics, and the integration of artificial intelligence in the interpretation of genetic data.

NIBR-LTSi is a selective LATS kinase inhibitor activating YAP signaling and expanding tissue stem cells in vitro and in vivo

The YAP/Hippo pathway is an organ growth and size regulation rheostat safeguarding multiple tissue stem cell compartments. LATS kinases phosphorylate and thereby inactivate YAP, thus representing a potential direct drug target for promoting tissue regeneration. Here, we report the identification and characterization of the selective small-molecule LATS kinase inhibitor NIBR-LTSi. NIBR-LTSi activates YAP signaling, shows good oral bioavailability, and expands organoids derived from several mouse and human tissues. In tissue stem cells, NIBR-LTSi promotes proliferation, maintains stemness, and blocks differentiation in vitro and in vivo. NIBR-LTSi accelerates liver regeneration following extended hepatectomy in mice. However, increased proliferation and cell dedifferentiation in multiple organs prevent prolonged systemic LATS inhibition, thus limiting potential therapeutic benefit. Together, we report a selective LATS kinase inhibitor agonizing YAP signaling and promoting tissue regeneration in vitro and in vivo, enabling future research on the regenerative potential of the YAP/Hippo pathway.

Regorafenib and glioblastoma: a literature review of preclinical studies, molecular mechanisms and clinical effectiveness

Glioblastoma IDH wild type (GBM) is a very aggressive brain tumour, characterised by an infiltrative growth pattern and by a prominent neoangiogenesis. Its prognosis is unfortunately dismal, and the median overall survival of GBM patients is short (15 months). Clinical management is based on bulk tumour removal and standard chemoradiation with the alkylating drug temozolomide, but the tumour invariably recurs leading to patient's death. Clinical options for GBM patients remained unaltered for almost two decades until the encouraging results obtained by the phase II REGOMA trial allowed the introduction of the multikinase inhibitor regorafenib as a preferred regimen in relapsed GBM treatment by the National Comprehensive Cancer Network (NCCN) 2020 Guideline. Regorafenib, a sorafenib derivative, targets kinases associated with angiogenesis (VEGFR 1-3), as well as oncogenesis (c-KIT, RET, FGFR) and stromal kinases (FGFR, PDGFR-b). It was already approved for metastatic colorectal cancers and hepatocellular carcinomas. The aim of the present review is to focus on both the molecular and clinical knowledge collected in these first three years of regorafenib use in GBM.

QSAR analysis of VEGFR-2 inhibitors based on machine learning, Topomer CoMFA and molecule docking

VEGFR-2 kinase inhibitors are clinically approved drugs that can effectively target cancer angiogenesis. However, such inhibitors have adverse effects such as skin toxicity, gastrointestinal reactions and hepatic impairment. In this study, machine learning and Topomer CoMFA, which is an alignment-dependent, descriptor-based method, were employed to build structural activity relationship models of potentially new VEGFR-2 inhibitors. The prediction ac-curacy of the training and test sets of the 2D-SAR model were 82.4 and 80.1%, respectively, with KNN. Topomer CoMFA approach was then used for 3D-QSAR modeling of VEGFR-2 inhibitors. The coefficient of q2 for cross-validation of the model 1 was greater than 0.5, suggesting that a stable drug activity-prediction model was obtained. Molecular docking was further performed to simulate the interactions between the five most promising compounds and VEGFR-2 target protein and the Total Scores were all greater than 6, indicating that they had a strong hydrogen bond interactions were present. This study successfully used machine learning to obtain five potentially novel VEGFR-2 inhibitors to increase our arsenal of drugs to combat cancer.

First-in-class MKK4 inhibitors enhance liver regeneration and prevent liver failure

Diminished hepatocyte regeneration is a key feature of acute and chronic liver diseases and after extended liver resections, resulting in the inability to maintain or restore a sufficient functional liver mass. Therapies to restore hepatocyte regeneration are lacking, making liver transplantation the only curative option for end-stage liver disease. Here, we report on the structure-based development and characterization (nuclear magnetic resonance [NMR] spectroscopy) of first-in-class small molecule inhibitors of the dual-specificity kinase MKK4 (MKK4i). MKK4i increased liver regeneration upon hepatectomy in murine and porcine models, allowed for survival of pigs in a lethal 85% hepatectomy model, and showed antisteatotic and antifibrotic effects in liver disease mouse models. A first-in-human phase I trial (European Union Drug Regulating Authorities Clinical Trials [EudraCT] 2021-000193-28) with the clinical candidate HRX215 was conducted and revealed excellent safety and pharmacokinetics. Clinical trials to probe HRX215 for prevention/treatment of liver failure after extensive oncological liver resections or after transplantation of small grafts are warranted.

Identification of Collagen-Suppressive Agents in Keloidal Fibroblasts Using a High-Content, Phenotype-Based Drug Screen

Keloids are characterized by excessive extracellular collagen and exaggerated scarring. Large-volume lesions can be functionally debilitating, therapeutically intractable, and psychologically devastating. A key barrier to translational momentum for novel antikeloid agents is the lack of a faithful high-content screen. We devised, to our knowledge, a previously unreported phenotype-based assay that measures secreted collagen by keloidal fibroblasts in tissue hypoxic conditions (1% oxygen). Four keloidal fibroblasts and 1 normal dermal fibroblast line were exposed to 199 kinase inhibitors. Of 199 kinase inhibitors, 41 (21%) and 71 (36%) increased and decreased the CI ¯ norm (mean collagen inhibition normalized to viability) by more than 10%, respectively. The most collagen suppressive agents were CGP60474 (CI ¯ norm = 0.36), KIN001-244 (CI ¯ norm = 0.55), and RAF265 (CI ¯ norm = 0.58). The top candidate, CGP60474, consistently abolished collagens I and VII production, exhibited minimal global toxicity, and induced a fivefold increase in phosphorylated extracellular signal-regulated kinase. This proof-of-concept high-content screen can identify drugs that appear to target critical keloidal pathophysiology-collagen secretion.

A drug-resistant mutation in plant target of rapamycin validates the specificity of ATP-competitive TOR inhibitors in vivo

Kinases are major components of cellular signaling pathways, regulating key cellular activities through phosphorylation. Kinase inhibitors are efficient tools for studying kinase targets and functions, however assessing their kinase specificity in vivo is essential. The identification of resistant kinase mutants has been proposed to be the most convincing approach to achieve this goal. Here, we address this issue in plants via a pharmacogenetic screen for mutants resistant to the ATP-competitive TOR inhibitor AZD-8055. The eukaryotic TOR (Target of Rapamycin) kinase is emerging as a major hub controlling growth responses in plants largely thanks to the use of ATP-competitive inhibitors. We identified a dominant mutation in the DFG motif of the Arabidopsis TOR kinase domain that leads to very strong resistance to AZD-8055. This resistance was characterized by measuring root growth, photosystem II (PSII) activity in leaves and phosphorylation of YAK1 (Yet Another Kinase 1) and RPS6 (Ribosomal protein S6), a direct and an indirect target of TOR respectively. Using other ATP-competitive TOR inhibitors, we also show that the dominant mutation is particularly efficient for resistance to drugs structurally related to AZD-8055. Altogether, this proof-of-concept study demonstrates that a pharmacogenetic screen in Arabidopsis can be used to successfully identify the target of a kinase inhibitor in vivo and therefore to demonstrate inhibitor specificity. Thanks to the conservation of kinase families in eukaryotes, and the possibility of creating amino acid substitutions by genome editing, this work has great potential for extending studies on the evolution of signaling pathways in eukaryotes.

Identification of novel ureido benzothiophenes as dual VEGFR-2/EGFR anticancer agents

Presently, dual-targeting by a single small molecule stands out as a fruitful cancer-fighting strategy. Joining the global effort to fight cancer, a leading cause of death worldwide, we report in this study a novel set for benzothiophene-based aryl urea derivatives as potential anti-proliferative candidates endowed with dual VEGFR-2/EGFR inhibitory activities. The prepared ureido benzothiophenes 6a-r have been evaluated for their anticancer action on a panel of tumor cell lines, namely PanC-1, MCF-7, and HepG2 cells. Most newly synthesized benzo[b]thiophene ureas disclosed effective cytotoxic activities against the examined cancer cell lines. In particular, compound 6q, with an appended 4-trifluoromethoxy group on the terminal phenyl ring, exhibited the most significant cytotoxic activity in MCF-7 with IC50 3.86 ± 0.72 ug/mL; IC50 of 3.65 ± 0.18 ug/ml in PanC-1 cell line and an IC50 of 4.78 ± 0.06 ug/ml in HepG2. After that, derivatives that exhibited the most potent cytotoxic activities (6g, 6j, 6q, and 6r) were further evaluated as VEGFR-2 and EGFR inhibitors. Fortunately, they displayed low nanomolar IC50 values against both enzymes, where compound 6q emerged to possess superior inhibitory effects towards both EGFR and VEGFR-2 with IC50 46.6 nM and 11.3 nM simultaneously compared to the reference medications Erlotinib and Sorafenib, respectively. The docked structure of 6q within the catalytic region of VEGFR-2 and EGFR kinases was acquired and studied so that we could investigate potential binding mechanisms for the target ureido benzothiophenes. Hence, the benzothiophene-based aryl urea scaffold has great potential for advancing the development of highly effective dual inhibitors targeting both EGFR and VEGFR-2, which can serve as effective candidates for anticancer therapy.

Recent drug design strategies and identification of key heterocyclic scaffolds for promising anticancer targets

Cancer, a noncommunicable disease, is the leading cause of mortality worldwide and is anticipated to rise by 75% in the next two decades, reaching approximately 25 million cases. Traditional cancer treatments, such as radiotherapy and surgery, have shown limited success in reducing cancer incidence. As a result, the focus of cancer chemotherapy has switched to the development of novel small molecule antitumor agents as an alternate strategy for combating and managing cancer rates. Heterocyclic compounds are such agents that bind to specific residues in target proteins, inhibiting their function and potentially providing cancer treatment. This review focuses on privileged heterocyclic pharmacophores with potent activity against carbonic anhydrases and kinases, which are important anticancer targets. Evaluation of ongoing pre-clinical and clinical research of heterocyclic compounds with potential therapeutic value against a variety of malignancies as well as the provision of a concise summary of the role of heterocyclic scaffolds in various chemotherapy protocols have also been discussed. The main objective of the article is to highlight key heterocyclic scaffolds involved in recent anticancer drug design that demands further attention from the drug development community to find more effective and safer targeted small-molecule anticancer agents.

Degradation by Design: New Cyclin K Degraders from Old CDK Inhibitors

Small molecules that induce protein degradation hold the potential to overcome several limitations of the currently available inhibitors. Monovalent or molecular glue degraders, in particular, enable the benefits of protein degradation without the disadvantages of high molecular weight and the resulting challenge in drug development that are associated with bivalent molecules like Proteolysis Targeting Chimeras. One key challenge in designing monovalent degraders is how to build in the degrader activity─how can we convert an inhibitor into a degrader? If degradation activity requires very specific molecular features, it will be difficult to find new degraders and challenging to optimize those degraders toward drugs. Herein, we demonstrate that an unexpectedly wide range of modifications to the degradation-inducing group of the cyclin K degrader CR8 are tolerated, including both aromatic and nonaromatic groups. We used these findings to convert the pan-CDK inhibitors dinaciclib and AT-7519 to Cyclin K degraders, leading to a novel dinaciclib-based compound with improved degradation activity compared to CR8 and confirm the mechanism of degradation. These results suggest that general design principles can be generated for the development and optimization of monovalent degraders.

Preclinical characterization of CPL304110 as a potent and selective inhibitor of fibroblast growth factor receptors 1, 2, and 3 for gastric, bladder, and squamous cell lung cancer

Fibroblast Growth Factor Receptors (FGFRs) are a family of receptor tyrosine kinases expressed on a plethora of cell membranes. They play crucial roles in both embryonic development and adult tissue functions. There is an increasing amount of evidence that FGFR-mediated oncogenesis is mainly related to gene amplification, activating mutations, or translocation in tumors of various histological types. Dysregulation of FGFRs has been implicated in a wide variety of neoplasms, such as bladder, gastric, and lung cancers. Given their functional significance, FGFRs emerge as promising targets for cancer therapy. Here, we introduce CPL304100, an innovative and highly potent FGFR1-3 kinase inhibitor demonstrating excellent in vitro biological activity. Comprehensive analyses encompassed kinase assays, cell line evaluations, PK/PD studies surface plasmon resonance studies, molecular docking, and in vivo testing in mouse xenografts. CPL304110 exhibited a distinctive binding profile to FGFR1/2/3 kinase domains, accompanied by a good safety profile and favorable ADMET parameters. Selective inhibition of tumor cell lines featuring active FGFR signaling was observed, distinguishing it from cell lines lacking FGFR aberrations (FGFR1, 2, and 3). CPL304110 demonstrated efficacy in both FGFR-dependent cell lines and patient-derived tumor xenograft (PDTX) in vivo models. Comparative analyses with FDA-approved FGFR inhibitors, erdafitinib and pemigatinib, revealed certain advantages of CPL304110 in both in vitro and in vivo assessments. Encouraging preclinical results led the way for the initiation of a Phase I clinical trial (01FGFR2018; NCT04149691) to further evaluate CPL304110 as a novel anticancer therapy.

Structure-guided design of a selective inhibitor of the methyltransferase KMT9 with cellular activity

Inhibition of epigenetic regulators by small molecules is an attractive strategy for cancer treatment. Recently, we characterised the role of lysine methyltransferase 9 (KMT9) in prostate, lung, and colon cancer. Our observation that the enzymatic activity was required for tumour cell proliferation identified KMT9 as a potential therapeutic target. Here, we report the development of a potent and selective KMT9 inhibitor (compound 4, KMI169) with cellular activity through structure-based drug design. KMI169 functions as a bi-substrate inhibitor targeting the SAM and substrate binding pockets of KMT9 and exhibits high potency, selectivity, and cellular target engagement. KMT9 inhibition selectively downregulates target genes involved in cell cycle regulation and impairs proliferation of tumours cells including castration- and enzalutamide-resistant prostate cancer cells. KMI169 represents a valuable tool to probe cellular KMT9 functions and paves the way for the development of clinical candidate inhibitors as therapeutic options to treat malignancies such as therapy-resistant prostate cancer.

Small-molecule inhibition of kinesin KIF18A reveals a mitotic vulnerability enriched in chromosomally unstable cancers

Chromosomal instability (CIN) is a hallmark of cancer, caused by persistent errors in chromosome segregation during mitosis. Aggressive cancers like high-grade serous ovarian cancer (HGSOC) and triple-negative breast cancer (TNBC) have a high frequency of CIN and TP53 mutations. Here, we show that inhibitors of the KIF18A motor protein activate the mitotic checkpoint and selectively kill chromosomally unstable cancer cells. Sensitivity to KIF18A inhibition is enriched in TP53-mutant HGSOC and TNBC cell lines with CIN features, including in a subset of CCNE1-amplified, CDK4-CDK6-inhibitor-resistant and BRCA1-altered cell line models. Our KIF18A inhibitors have minimal detrimental effects on human bone marrow cells in culture, distinct from other anti-mitotic agents. In mice, inhibition of KIF18A leads to robust anti-cancer effects with tumor regression observed in human HGSOC and TNBC models at well-tolerated doses. Collectively, our results provide a rational therapeutic strategy for selective targeting of CIN cancers via KIF18A inhibition.

Chemical, Biochemical, Cellular, and Physiological Characterization of Leucettinib-21, a Down Syndrome and Alzheimer's Disease Drug Candidate

Leucettinibs are substituted 2-aminoimidazolin-4-ones (inspired by the marine sponge natural product Leucettamine B) developed as pharmacological inhibitors of DYRK1A (dual-specificity, tyrosine phosphorylation-regulated kinase 1A), a therapeutic target for indications such as Down syndrome and Alzheimer's disease. Leucettinib-21 was selected as a drug candidate following extensive structure/activity studies and multiparametric evaluations. We here report its physicochemical properties (X-ray powder diffraction, differential scanning calorimetry, stability, solubility, crystal structure) and drug-like profile. Leucettinib-21's selectivity (analyzed by radiometric, fluorescence, interaction, thermal shift, residence time assays) reveals DYRK1A as the first target but also some "off-targets" which may contribute to the drug's biological effects. Leucettinib-21 was cocrystallized with CLK1 and modeled in the DYRK1A structure. Leucettinib-21 inhibits DYRK1A in cells (demonstrated by direct catalytic activity and phosphorylation levels of Thr286-cyclin D1 or Thr212-Tau). Leucettinib-21 corrects memory disorders in the Down syndrome mouse model Ts65Dn and is now entering safety/tolerance phase 1 clinical trials.

Pharmacological approaches to understanding protein kinase signaling networks

Protein kinases play vital roles in controlling cell behavior, and an array of kinase inhibitors are used successfully for treatment of disease. Typical drug development pipelines involve biological studies to validate a protein kinase target, followed by the identification of small molecules that effectively inhibit this target in cells, animal models, and patients. However, it is clear that protein kinases operate within complex signaling networks. These networks increase the resilience of signaling pathways, which can render cells relatively insensitive to inhibition of a single kinase, and provide the potential for pathway rewiring, which can result in resistance to therapy. It is therefore vital to understand the properties of kinase signaling networks in health and disease so that we can design effective multi-targeted drugs or combinations of drugs. Here, we outline how pharmacological and chemo-genetic approaches can contribute to such knowledge, despite the known low selectivity of many kinase inhibitors. We discuss how detailed profiling of target engagement by kinase inhibitors can underpin these studies; how chemical probes can be used to uncover kinase-substrate relationships, and how these tools can be used to gain insight into the configuration and function of kinase signaling networks.

A covalent fragment-based strategy targeting a novel cysteine to inhibit activity of mutant EGFR kinase

Several generations of ATP-competitive anti-cancer drugs that inhibit the activity of the intracellular kinase domain of the epidermal growth factor receptor (EGFR) have been developed over the past twenty years. The first-generation of drugs such as gefitinib bind reversibly and were followed by a second-generation such as dacomitinib that harbor an acrylamide moiety that forms a covalent bond with C797 in the ATP binding pocket. Resistance emerges through mutation of the T790 gatekeeper residue to methionine, which introduces steric hindrance to drug binding and increases the Km for ATP. A third generation of drugs, such as osimertinib were developed which were effective against T790M EGFR in which an acrylamide moiety forms a covalent bond with C797, although resistance has emerged by mutation to S797. A fragment-based screen to identify new starting points for an EGFR inhibitor serendipitously identified a fragment that reacted with C775, a previously unexploited residue in the ATP binding pocket for a covalent inhibitor to target. A number of acrylamide containing fragments were identified that selectively reacted with C775. One of these acrylamides was optimized to a highly selective inhibitor with sub-1 μM activity, that is active against T790M, C797S mutant EGFR independent of ATP concentration, providing a potential new strategy for pan-EGFR mutant inhibition.

Therapeutic targeting of EP300/CBP by bromodomain inhibition in hematologic malignancies

CCS1477 (inobrodib) is a potent, selective EP300/CBP bromodomain inhibitor which induces cell-cycle arrest and differentiation in hematologic malignancy model systems. In myeloid leukemia cells, it promotes rapid eviction of EP300/CBP from an enhancer subset marked by strong MYB occupancy and high H3K27 acetylation, with downregulation of the subordinate oncogenic network and redistribution to sites close to differentiation genes. In myeloma cells, CCS1477 induces eviction of EP300/CBP from FGFR3, the target of the common (4; 14) translocation, with redistribution away from IRF4-occupied sites to TCF3/E2A-occupied sites. In a subset of patients with relapsed or refractory disease, CCS1477 monotherapy induces differentiation responses in AML and objective responses in heavily pre-treated multiple myeloma. In vivo preclinical combination studies reveal synergistic responses to treatment with standard-of-care agents. Thus, CCS1477 exhibits encouraging preclinical and early-phase clinical activity by disrupting recruitment of EP300/CBP to enhancer networks occupied by critical transcription factors.

Docking for EP4R antagonists active against inflammatory pain

The lipid prostaglandin E2 (PGE2) mediates inflammatory pain by activating G protein-coupled receptors, including the prostaglandin E2 receptor 4 (EP4R). Nonsteroidal anti-inflammatory drugs (NSAIDs) reduce nociception by inhibiting prostaglandin synthesis, however, the disruption of upstream prostanoid biosynthesis can lead to pleiotropic effects including gastrointestinal bleeding and cardiac complications. In contrast, by acting downstream, EP4R antagonists may act specifically as anti-inflammatory agents and, to date, no selective EP4R antagonists have been approved for human use. In this work, seeking to diversify EP4R antagonist scaffolds, we computationally dock over 400 million compounds against an EP4R crystal structure and experimentally validate 71 highly ranked, de novo synthesized molecules. Further, we show how structure-based optimization of initial docking hits identifies a potent and selective antagonist with 16 nanomolar potency. Finally, we demonstrate favorable pharmacokinetics for the discovered compound as well as anti-allodynic and anti-inflammatory activity in several preclinical pain models in mice.

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.

PERK Inhibition by HC-5404 Sensitizes Renal Cell Carcinoma Tumor Models to Antiangiogenic Tyrosine Kinase Inhibitors

PURPOSE

Tumors activate protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK, also called EIF2AK3) in response to hypoxia and nutrient deprivation as a stress-mitigation strategy. Here, we tested the hypothesis that inhibiting PERK with HC-5404 enhances the antitumor efficacy of standard-of-care VEGF receptor tyrosine kinase inhibitors (VEGFR-TKI).

EXPERIMENTAL DESIGN

HC-5404 was characterized as a potent and selective PERK inhibitor, with favorable in vivo properties. Multiple renal cell carcinoma (RCC) tumor models were then cotreated with both HC-5404 and VEGFR-TKI in vivo, measuring tumor volume across time and evaluating tumor response by protein analysis and IHC.

RESULTS

VEGFR-TKI including axitinib, cabozantinib, lenvatinib, and sunitinib induce PERK activation in 786-O RCC xenografts. Cotreatment with HC-5404 inhibited PERK in tumors and significantly increased antitumor effects of VEGFR-TKI across multiple RCC models, resulting in tumor stasis or regression. Analysis of tumor sections revealed that HC-5404 enhanced the antiangiogenic effects of axitinib and lenvatinib by inhibiting both new vasculature and mature tumor blood vessels. Xenografts that progress on axitinib monotherapy remain sensitive to the combination treatment, resulting in ∼20% tumor regression in the combination group. When tested across a panel of 18 RCC patient-derived xenograft (PDX) models, the combination induced greater antitumor effects relative to monotherapies. In this single animal study, nine out of 18 models responded with ≥50% tumor regression from baseline in the combination group.

CONCLUSIONS

By disrupting an adaptive stress response evoked by VEGFR-TKI, HC-5404 presents a clinical opportunity to improve the antitumor effects of well-established standard-of-care therapies in RCC.

A twenty year perspective on melanoma therapy

Melanoma had long been considered to be particularly addressable with immunotherapy, but that reputation was built on modestly effective cytokine-based immunotherapy. CTLA-4 antibody therapy reinforced this legacy, but PD-1 antibodies transformed the melanoma treatment landscape and lead the way for immunotherapy to become standard treatment for more than half of the advanced cancer population. BRAF mutations were discovered in 8% of all cancer and nearly 50% of melanomas. Successful development of BRAF inhibitors and BRAF/MEK combination therapy in melanoma preceded regulatory approval across all cancer types. No cancer type saw outcomes improved by the same margin as melanoma in the decade of the 2010s.

Antiangiogenics in Malignant Granular Cell Tumors: Review of the Literature

Granular cell tumors (GCT) represent 0.5% of all soft tissue sarcomas (STS), and when metastatic, they exhibit aggressive behavior and determine limited survival. Metastatic GCTs are relatively chemo-resistant; however, there is growing evidence of the benefit of using pazopanib and other targeted therapies in this histology. This is a review of the role of pazopanib and other targeted therapies in the treatment of GCTs, along with some insights on pathology and molecular biology described in GCTs. From 256 articles found in our search, 10 case-report articles met the inclusion criteria. Pazopanib was the most employed systemic therapy. The median reported time on therapy with pazopanib was seven months. Eight out of ten patients (80%) experienced disease control with pazopanib, while four out of ten (40%) patients achieved an objective RECIST response. Molecular studies suggested that antitumoral effects of pazopanib in GCT might be due to a loss-of-function of ATP6AP1/2 genes which consequently enhance signaling through several molecular pathways, such as SFKs, STAT5a/b, and PDGFR-β. Other reported targeted therapies for malignant GCTs included pazopanib in combination with crizotinib, which showed disease control for four months in one patient, and a PI3K inhibitor which achieved disease control for nine months in another patient. Dasatinib and megestrol were ineffective in two other different patients. Pazopanib has been demonstrated to be active in advanced GCTs and may be considered as a preferable treatment option.

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.

Iterative machine learning-based chemical similarity search to identify novel chemical inhibitors

Machine learning-based chemical screening has made substantial progress in recent years. However, these predictions often have low accuracy and high uncertainty when identifying new active chemical scaffolds. Hence, a high proportion of retrieved compounds are not structurally novel. In this study, we proposed a strategy to address this issue by iteratively optimizing an evolutionary chemical binding similarity (ECBS) model using experimental validation data. Various data update and model retraining schemes were tested to efficiently incorporate new experimental data into ECBS models, resulting in a fine-tuned ECBS model with improved accuracy and coverage. To demonstrate the effectiveness of our approach, we identified the novel hit molecules for the mitogen-activated protein kinase kinase 1 (MEK1). These molecules showed sub-micromolar affinity (Kd 0.1-5.3 μM) to MEKs and were distinct from previously-known MEK1 inhibitors. We also determined the binding specificity of different MEK isoforms and proposed potential docking models. Furthermore, using de novo drug design tools, we utilized one of the new MEK inhibitors to generate additional drug-like molecules with improved binding scores. This resulted in the identification of several potential MEK1 inhibitors with better binding affinity scores. Our results demonstrated the potential of this approach for identifying novel hit molecules and optimizing their binding affinities.

Pharmacological inhibition of TBK1/IKKε blunts immunopathology in a murine model of SARS-CoV-2 infection

TANK-binding kinase 1 (TBK1) is a key signalling component in the production of type-I interferons, which have essential antiviral activities, including against SARS-CoV-2. TBK1, and its homologue IκB kinase-ε (IKKε), can also induce pro-inflammatory responses that contribute to pathogen clearance. While initially protective, sustained engagement of type-I interferons is associated with damaging hyper-inflammation found in severe COVID-19 patients. The contribution of TBK1/IKKε signalling to these responses is unknown. Here we find that the small molecule idronoxil inhibits TBK1/IKKε signalling through destabilisation of TBK1/IKKε protein complexes. Treatment with idronoxil, or the small molecule inhibitor MRT67307, suppresses TBK1/IKKε signalling and attenuates cellular and molecular lung inflammation in SARS-CoV-2-challenged mice. Our findings additionally demonstrate that engagement of STING is not the major driver of these inflammatory responses and establish a critical role for TBK1/IKKε signalling in SARS-CoV-2 hyper-inflammation.

A Hybrid Structure-Based Machine Learning Approach for Predicting Kinase Inhibition by Small Molecules

Kinases have been the focus of drug discovery programs for three decades leading to over 70 therapeutic kinase inhibitors and biophysical affinity measurements for over 130,000 kinase-compound pairs. Nonetheless, the precise target spectrum for many kinases remains only partly understood. In this study, we describe a computational approach to unlocking qualitative and quantitative kinome-wide binding measurements for structure-based machine learning. Our study has three components: (i) a Kinase Inhibitor Complex (KinCo) data set comprising in silico predicted kinase structures paired with experimental binding constants, (ii) a machine learning loss function that integrates qualitative and quantitative data for model training, and (iii) a structure-based machine learning model trained on KinCo. We show that our approach outperforms methods trained on crystal structures alone in predicting binary and quantitative kinase-compound interaction affinities; relative to structure-free methods, our approach also captures known kinase biochemistry and more successfully generalizes to distant kinase sequences and compound scaffolds.

Exploring the Druggable Conformational Space of Protein Kinases Using AI-Generated Structures

Protein kinase function and interactions with drugs are controlled in part by the movement of the DFG and ɑC-Helix motifs, which enable kinases to adopt various conformational states. Small molecule ligands elicit therapeutic effects with distinct selectivity profiles and residence times that often depend on the kinase conformation(s) they bind. However, the limited availability of experimentally determined structural data for kinases in inactive states restricts drug discovery efforts for this major protein family. Modern AI-based structural modeling methods hold potential for exploring the previously experimentally uncharted druggable conformational space for kinases. Here, we first evaluated the currently explored conformational space of kinases in the PDB and models generated by AlphaFold2 (AF2) (1) and ESMFold (2), two prominent AI-based structure prediction methods. We then investigated AF2's ability to predict kinase structures in different conformations at various multiple sequence alignment (MSA) depths, based on this parameter's ability to explore conformational diversity. Our results showed a bias within the PDB and predicted structural models generated by AF2 and ESMFold toward structures of kinases in the active state over alternative conformations, particularly those conformations controlled by the DFG motif. Finally, we demonstrate that predicting kinase structures using AF2 at lower MSA depths allows the exploration of the space of these alternative conformations, including identifying previously unobserved conformations for 398 kinases. The results of our analysis of structural modeling by AF2 create a new avenue for the pursuit of new therapeutic agents against a notoriously difficult-to-target family of proteins.

Significance Statement

Greater abundance of kinase structural data in inactive conformations, currently lacking in structural databases, would improve our understanding of how protein kinases function and expand drug discovery and development for this family of therapeutic targets. Modern approaches utilizing artificial intelligence and machine learning have potential for efficiently capturing novel protein conformations. We provide evidence for a bias within AlphaFold2 and ESMFold to predict structures of kinases in their active states, similar to their overrepresentation in the PDB. We show that lowering the AlphaFold2 algorithm's multiple sequence alignment depth can help explore kinase conformational space more broadly. It can also enable the prediction of hundreds of kinase structures in novel conformations, many of whose models are likely viable for drug discovery.

PROX1 Inhibits PDGF-B Expression to Prevent Myxomatous Degeneration of Heart Valves

BACKGROUND

Cardiac valve disease is observed in 2.5% of the general population and 10% of the elderly people. Effective pharmacological treatments are currently not available, and patients with severe cardiac valve disease require surgery. PROX1 (prospero-related homeobox transcription factor 1) and FOXC2 (Forkhead box C2 transcription factor) are transcription factors that are required for the development of lymphatic and venous valves. We found that PROX1 and FOXC2 are expressed in a subset of valvular endothelial cells (VECs) that are located on the downstream (fibrosa) side of cardiac valves. Whether PROX1 and FOXC2 regulate cardiac valve development and disease is not known.

METHODS

We used histology, electron microscopy, and echocardiography to investigate the structure and functioning of heart valves from Prox1ΔVEC mice in which Prox1 was conditionally deleted from VECs. Isolated valve endothelial cells and valve interstitial cells were used to identify the molecular mechanisms in vitro, which were tested in vivo by RNAScope, additional mouse models, and pharmacological approaches. The significance of our findings was tested by evaluation of human samples of mitral valve prolapse and aortic valve insufficiency.

RESULTS

Histological analysis revealed that the aortic and mitral valves of Prox1ΔVEC mice become progressively thick and myxomatous. Echocardiography revealed that the aortic valves of Prox1ΔVEC mice are stenotic. FOXC2 was downregulated and PDGF-B (platelet-derived growth factor-B) was upregulated in the VECs of Prox1ΔVEC mice. Conditional knockdown of FOXC2 and conditional overexpression of PDGF-B in VECs recapitulated the phenotype of Prox1ΔVEC mice. PDGF-B was also increased in mice lacking FOXC2 and in human mitral valve prolapse and insufficient aortic valve samples. Pharmacological inhibition of PDGF-B signaling with imatinib partially ameliorated the valve defects of Prox1ΔVEC mice.

CONCLUSIONS

PROX1 antagonizes PDGF-B signaling partially via FOXC2 to maintain the extracellular matrix composition and prevent myxomatous degeneration of cardiac valves.

Characterization of the molecular interactions between resveratrol derivatives and death-associated protein kinase 1

Death-associated protein kinase 1 (DAPK1), a Ca2+/calmodulin-regulated serine/threonine kinase, regulates cell apoptosis and autophagy and has been implicated in the pathogenesis of Alzheimer's disease (AD). Targeting DAPK1 may be a promising approach for treating AD. In our previous study, we found that a natural polyphenol, resveratrol (1), is a moderate DAPK1 inhibitor. In the present study, we investigated the interactions between natural and synthetic derivatives of 1 and DAPK1. Binding assays including intrinsic fluorescence quenching, protein thermal shift and isothermal titration calorimetry indicated that oxyresveratrol (3), a hydroxylated derivative, and pinostilbene (5), a methoxylated derivative, bind to DAPK1 with comparable affinity to 1. The enzymatic assay showed that 3 more effectively inhibits the intrinsic ATPase activity of DAPK1 compared with 1. Crystallographic analysis revealed that the binding modes of the methoxylated derivatives were different from those of 1 and 3, resulting in a unique interaction. Our results suggest that 3 may be helpful in treating AD and provide a clue for the development of promising DAPK1 inhibitors.

Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks

Many therapies in clinical trials are based on single drug-single target relationships. To further extend this concept to multi-target approaches using multi-targeted drugs, we developed a machine learning pipeline to unravel the target landscape of kinase inhibitors. This pipeline, which we call 3D-KINEssence, uses a new type of protein fingerprints (3D FP) based on the structure of kinases generated through a 3D convolutional neural network (3D-CNN). These 3D-CNN kinase fingerprints were matched to molecular Morgan fingerprints to predict the targets of each respective kinase inhibitor based on available bioactivity data. The performance of the pipeline was evaluated on two test sets: a sparse drug-target set where each drug is matched in most cases to a single target and also on a densely-covered drug-target set where each drug is matched to most if not all targets. This latter set is more challenging to train, given its non-exclusive character. Our model's root-mean-square error (RMSE) based on the two datasets was 0.68 and 0.8, respectively. These results indicate that 3D FP can predict the target landscape of kinase inhibitors at around 0.8 log units of bioactivity. Our strategy can be utilized in proteochemometric or chemogenomic workflows by consolidating the target landscape of kinase inhibitors.

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.

Unlocking the Potential of Kinase Targets in Cancer: Insights from CancerOmicsNet, an AI-Driven Approach to Drug Response Prediction in Cancer

Deregulated protein kinases are crucial in promoting cancer cell proliferation and driving malignant cell signaling. Although these kinases are essential targets for cancer therapy due to their involvement in cell development and proliferation, only a small part of the human kinome has been targeted by drugs. A comprehensive scoring system is needed to evaluate and prioritize clinically relevant kinases. We recently developed CancerOmicsNet, an artificial intelligence model employing graph-based algorithms to predict the cancer cell response to treatment with kinase inhibitors. The performance of this approach has been evaluated in large-scale benchmarking calculations, followed by the experimental validation of selected predictions against several cancer types. To shed light on the decision-making process of CancerOmicsNet and to better understand the role of each kinase in the model, we employed a customized saliency map with adjustable channel weights. The saliency map, functioning as an explainable AI tool, allows for the analysis of input contributions to the output of a trained deep-learning model and facilitates the identification of essential kinases involved in tumor progression. The comprehensive survey of biomedical literature for essential kinases selected by CancerOmicsNet demonstrated that it could help pinpoint potential druggable targets for further investigation in diverse cancer types.

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.

Abrogating Metastatic Properties of Triple-Negative Breast Cancer Cells by EGFR and PI3K Dual Inhibitors

Triple-negative breast cancer (TNBC) is a devastating BC subtype. Its aggressiveness, allied to the lack of well-defined molecular targets, usually culminates in the appearance of metastases that account for poor prognosis, particularly when they develop in the brain. Nevertheless, TNBC has been associated with epidermal growth factor receptor (EGFR) overexpression, leading to downstream phosphoinositide 3-kinase (PI3K) signaling activation. We aimed to unravel novel drug candidates for TNBC treatment based on EGFR and/or PI3K inhibition. Using a highly metastatic TNBC cell line with brain tropism (MDA-MB-231 Br4) and a library of 27 drug candidates in silico predicted to inhibit EGFR, PI3K, or EGFR plus PI3K, and to cross the blood-brain barrier, we evaluated the effects on cell viability. The half maximal inhibitory concentration (IC50) of the most cytotoxic ones was established, and cell cycle and death, as well as migration and EGFR pathway intervenient, were further evaluated. Two dual inhibitors emerged as the most promising drugs, with the ability to modulate cell cycle, death, migration and proliferation, morphology, and PI3K/AKT cascade players such as myocyte enhancer factor 2C (MEF2C) and forkhead box P1 (FOXP1). This work revealed EGFR/PI3K dual inhibitors as strong candidates to tackle brain metastatic TNBC cells.

Characterization of Anticancer Effects of the Analogs of DJ4, a Novel Selective Inhibitor of ROCK and MRCK Kinases

The Rho associated coiled-coil containing protein kinase (ROCK1 and ROCK2) and myotonic dystrophy-related Cdc-42 binding kinases (MRCKα and MRCKβ) are critical regulators of cell proliferation and cell plasticity, a process intimately involved in cancer cell migration and invasion. Previously, we reported the discovery of a novel small molecule (DJ4) selective multi-kinase inhibitor of ROCK1/2 and MRCKα/β. Herein, we further characterized the anti-proliferative and apoptotic effects of DJ4 in non-small cell lung cancer and triple-negative breast cancer cells. To further optimize the ROCK/MRCK inhibitory potency of DJ4, we generated a library of 27 analogs. Among the various structural modifications, we identified four additional active analogs with enhanced ROCK/MRCK inhibitory potency. The anti-proliferative and cell cycle inhibitory effects of the active analogs were examined in non-small cell lung cancer, breast cancer, and melanoma cell lines. The anti-proliferative effectiveness of DJ4 and the active analogs was further demonstrated against a wide array of cancer cell types using the NCI-60 human cancer cell line panel. Lastly, these new analogs were tested for anti-migratory effects in highly invasive MDA-MB-231 breast cancer cells. Together, our results demonstrate that selective inhibitors of ROCK1/2 (DJE4, DJ-Allyl) inhibited cell proliferation and induced cell cycle arrest at G2/M but were less effective in cell death induction compared with dual ROCK1/2 and MRCKα/β (DJ4 and DJ110).

Understanding the process of angiogenesis in regenerating earthworm

Developing blood vessels from the existing vasculature is vital for the growth of the organism, as well as for systematic wound healing and the repair process. In this study, we investigated the role of angiogenesis during the regeneration process in the earthworm, Eudrilus eugeniae, animal model. Briefly, the morphological examination of blood vessels in juvenile and mature worms is documented, along with the development of new blood vessels in regenerating blastema. However, in vivo and in vitro experiments with juvenile worms revealed that geraniol retards blastemal regeneration growth with undeveloped blood vessels, as compared to the control. The results of qRT-PCR, western blotting, and immunohistochemistry confirmed a reduced expression of VEGFR2 and WNT5A in the day 3 regenerating blastema of geraniol-treated worms, as compared to the control. We conclude that geraniol acts as a potent natural inhibitor of angiogenesis, thereby retarding the regeneration process in earthworms. In addition, for studying angiogenesis and screening effective angiogenesis inhibitors as drug candidates, the earthworm is an ambient animal model system.