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Results for “Structural druggability”

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PubMed2025

From genetic causality to druggable targets: A multiomics framework identifies ZSCAN16 in gout pathogenesis.

ObjectiveGout is a prevalent form of inflammatory arthritis in which many patients respond suboptimally to current therapies. Drug development is hampered by a lack of genetically validated targets, leading to high clinical trial attrition. This study aimed to systematically identify and prioritize novel, druggable targets for gout via a multilayered genetic and functional genomics approach.MethodsWe performed two-sample Mendelian randomization (MR) using cis-expression quantitative trait locus (cis-eQTL) data and dual independent gout genome-wide association study (GWAS) cohorts (openGWAS and FinnGen). The candidate genes were subjected to a rigorous validation pipeline including Bayesian colocalization, phenome-wide association studies (PheWASs) to assess pleiotropy and on-target safety, and single-cell RNA sequencing (scRNA-seq) to delineate the cellular context. Molecular docking was used to evaluate the structural druggability of prioritized targets.ResultsMR analysis revealed 15 genes causally associated with gout. Colocalization analysis (PPH4 > 0.8) prioritized two targets: ZSCAN16 (risk-increasing, OR = 1.04, 95% CI [1.02-1.06]) and TRIM10 (protective, OR = 0.96, 95% CI [0.94-0.98]). Crucially, PheWAS revealed that ZSCAN16 is highly specific to gout, whereas TRIM10 exhibited extensive pleiotropy with hematological and cardiometabolic traits, indicating significant safety risks. Single-cell analysis provided orthogonal validation, demonstrating flare-specific upregulation of ZSCAN16 in cytotoxic T/NK cells. Molecular docking confirmed ZSCAN16 as a structurally druggable target, showing high-affinity binding with known compounds (e.g. digoxin, binding energy = -9.6 kcal/mol).ConclusionsOur study identifies ZSCAN16 as a high-potential, druggable therapeutic target for gout, highlighting its genetic influence on specific immune cell activities during acute flares. Conversely, TRIM10 was deprioritized owing to substantial pleiotropic liabilities and poor chemical tractability. These findings suggest that ZSCAN16 could play a crucial role in the pathogenesis of gout and may provide a valuable lead for future drug discovery efforts.

Humans↗
PubMed2026

CRISPR screens for the discovery of novel ferroptosis targets: progress and perspectives.

Ferroptosis is a distinct, iron-dependent form of regulated cell death characterized by lipid peroxidation. Despite its growing significance in physiology and disease, the molecular networks that govern ferroptosis are not yet fully understood. Genome-wide CRISPR screens have broadened the regulatory landscape of ferroptosis by revealing both conserved and context-dependent mechanisms. In this review, we summarize recent advances in CRISPR-based ferroptosis screens, highlighting a transition from in vitro CRISPR screens to in vivo platforms and single-cell CRISPR screens. We also discuss the potential translation of key targets, focusing on their structural druggability and therapeutic potential. By outlining objective-driven screening strategies, this review seeks to provide options for exploring the distinct mechanisms of ferroptosis and to accelerate its translation into therapeutic opportunities for various diseases.

CRISPR screens↗
PubMed2026

Cryo-EM structures of Candida albicans chitin synthase Chs1 reveal a druggable translocation channel.

Invasive candidiasis is a leading cause of hospital-acquired bloodstream infections with high mortality. While the fungal cell wall is an excellent therapeutic target, inhibitor development against the essential chitin synthase (Chs) has been hampered by the absence of structural and mechanistic understanding of class II Chs, which contribute to fungal viability. Here we present cryo-electron microscopy structures of Candida albicans class II Chs (CaChs1) at 2.93-3.38 Å resolution, providing insights into its mechanisms of early elongation, chito-oligomer translocation and inhibition by the CaChs1-specific non-competitive inhibitor diynyl arylamine (DA). Chitin elongation and translocation are coupled to coordinated motion of the glycosyltransferase domain and the dimer interface. Notably, DA binds within the chitin translocation channel where a regulatory lipid resides and inhibits the enzyme by occluding product polymer extrusion. Importantly, DA showed potent synergy with the class I Chs inhibitor nikkomycin Z against C. albicans and Candida auris. These findings establish the chitin translocation channel as a druggable site for rational antifungal design.

Journal Article↗
PubMed2026

RPL32: From housekeeping gene to potential biomarker and therapeutic target in cancer and multiple system diseases.

Ribosomal protein L32 (RPL32) is a core component of the 60S ribosomal subunit and a stable reference gene. Mounting evidence shows that RPL32 is upregulated in hepatocellular carcinoma, lung cancer, breast cancer, prostate cancer, and other malignancies, correlating with poor prognosis. RPL32 promotes cancer cell proliferation, invasion, and progression partly through the MDM2-p53-autophagy axis, and its expression is regulated by promoter methylation, copy number variations, and transcription factors. RPL32 represents a promising prognostic biomarker and candidate intervention target for cancer. However, its clinical translation requires further validation regarding intervention efficacy, systemic toxicity, druggability, and companion diagnostics. This narrative review summarizes the structure, function, and regulatory mechanisms of RPL32, emphasizes its oncogenic roles and translational potential in cancer, and briefly describes its pathological implications in non-cancer diseases, providing a framework for future cancer research.

Humans↗
PubMed2017

Drug target ontology to classify and integrate drug discovery data.

BACKGROUND: One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome. RESULTS: As part of that effort, we have developed a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

Biological Ontologies↗
PubMed2026

An Application of Iterative Health Economic Evaluation: An Update on the Early Cost Effectiveness of Whole-Genome Sequencing in Advanced Non-small-Cell Lung Cancer.

OBJECTIVE: Whole genome sequencing (WGS) can identify more druggable targets than the standard of care (SoC) panels, however, its health effects and costs are highly uncertain. Given the rapidly evolving treatment landscape and pricing, an iterative approach is crucial to continuously reassess evidence and adapt economic models. Our objective was to update a previously developed economic model for WGS. METHODS: We used a structured approach to identify and report model elements requiring updates, based on established tools and methodological guidance, and applied it to the probabilistic decision model by Simons et al.(2021), which compared SoC, WGS, and SoC followed by WGS in patients with inoperable stage IIIB, C/IV NSCLC in the Dutch setting. RESULTS: Updates included a new treatment (sotorasib), revised drug and diagnostic costs, and adherence to the latest guidelines. Drug and WGS diagnostics costs fell by 8% and 26%, respectively. SoC diagnostic prices increased by 17%. We explored the impact of the prevalence of druggable targets, effectiveness of off-label treatments, (academic-specific) diagnostic costs, and price negotiations. The ICER of WGS versus SoC decreased from €737,197 to €419,053/QALY. WGS would become cost-effective if diagnostic costs descended from €2,180 to €1,246 or if additional druggable targets were identified in ≥3.3% of patients. CONCLUSION: Our structured approach effectively identified items in the original analysis requiring updates and provides a foundation for further developing a checklist to guide iterative HTA. Continued monitoring and assessment of new treatment options, the dynamic diagnostics and costs throughout the life-cycle remain necessary to determine when WGS can be considered cost-effective.

NSCLC↗
PubMed2025

Expanding the druggable zinc-finger proteome defines properties of drug-induced degradation.

Glutarimide analogs, such as thalidomide, redirect the E3 ubiquitin ligase CRL4CRBN to induce degradation of certain zinc finger (ZF) proteins. Although the core structural motif recognized by CRBN has been characterized, it does not fully explain substrate specificity. To explore the role of residues adjacent to this core motif, we constructed a comprehensive ZF reporter library of 9,097 reporters derived from 1,655 human ZF proteins and conducted a library-on-library screen with 29 glutarimide analogs to identify compounds that collectively degrade 38 ZF reporters. Cryo-electron microscopy and crystal structures of ZFs in complex with CRBN revealed the importance of interactions beyond the core ZF degron. We used systematic mutagenesis of ZFs and CRBN to identify modes of neosubstrate recruitment requiring distinct amino acids. Finally, we found subtle chemical variations in glutarimide analogs that alter target scope and selectivity, thus providing a roadmap for their rational design.

Humans↗
PubMed2026

Searching the druggable genome using large language models.

SUMMARY: The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is currently accessed through structured web interfaces and API calls, requiring users to translate natural-language questions into database-specific query patterns. To allow for the use of DGIdb through natural language, we developed the DGIdb Model Context Protocol (MCP) server, which allows large language models (LLMs) access to up-to-date information through the DGIdb API. We demonstrate that the MCP server improves an LLM's ability to answer questions requiring accurate, up-to-date biomedical knowledge drawn from structured external resources. AVAILABILITY AND IMPLEMENTATION: The DGIdb MCP server is detailed at https://github.com/dgidb/dgidb-mcp-server and includes instructions for accessing the server through the Claude desktop app.

Large Language Models↗
PubMed2026

Searching the Druggable Genome using Large Language Models.

SUMMARY: The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is currently accessed through structured web interfaces and API calls, requiring users to translate natural-language questions into database-specific query patterns. To allow for the use of DGIdb through natural language, we developed the DGIdb Model Context Protocol (MCP) server, which allows large language models (LLMs) access to up-to-date information through the DGIdb API. We demonstrate that the MCP server greatly enhances an LLM's ability to answer questions requiring accurate, up-to-date biomedical knowledge drawn from structured external resources. AVAILABILITY AND IMPLEMENTATION: The DGIdb MCP server is detailed at https://github.com/griffithlab/dgidb-mcp-server and includes instructions for accessing the server through the Claude desktop app.

Journal Article↗
PubMed2025

Genomics-informed drug-repurposing strategy identifies two therapeutic targets for preventing liver disease associated with metabolic dysfunction.

Identification of drug-repurposing targets with genetic and biological support is an economically and temporally efficient strategy for improving the treatment of diseases. We employed a cross-disciplinary approach to identify potential therapeutics for the prevention of metabolic-dysfunction-associated steatotic liver disease (MASLD) in at-risk individuals by using humans as a model organism. We identified 212 putative candidate genes associated with MASLD by using data from a large multi-ancestry genetic association study, of which 158 (74.5%) were previously unreported. From this set, we identified 57 genes that encode for druggable protein targets and for which the effects of increasing genetically predicted gene expression on MASLD risk align with the function of that drug on the protein target. We then used We then evaluated these potential targets for evidence of efficacy by using Mendelian randomization, pathway analysis, and protein structural modeling. Through these approaches, we present compelling evidence to suggest that the activation of FADS1 by icosapent ethyl, as well as S1PR2 by fingolimod, could be a promising therapeutic strategy for MASLD prevention.

Humans↗
PubMed2026

Genetic and biochemical screens identify MGAT1 as a druggable glycosyltransferase target in STK11-mutant lung cancer.

Checkpoint inhibitors are standard-of-care therapies for non-small cell lung cancer (NSCLC), but their efficacy is limited in tumors with STK11 mutations, highlighting the need for new therapeutic strategies. Here, we performed complementary in vivo and in vitro CRISPR-Cas9 functional genomic screens to identify genes whose loss restores sensitivity to anti-PD-1 therapy. We found that loss of MGAT1, a Golgi glycosyltransferase critical for the maturation of high-mannose N-glycans into hybrid and complex glycan structures, reversed resistance to anti-PD-1 treatment in syngeneic mouse tumor models harboring STK11 mutations. Parallel co-culture screens with antigen-matched CD8+ T cells further showed that disruption of N-glycosylation strongly sensitized tumor cells to T cell-mediated killing. Genetic rescue studies demonstrated that this immune-evasion phenotype depends on MGAT1 catalytic activity, supporting direct biochemical interrogation of the enzyme. Using purified human MGAT1 and a UDP-Glo™ glycosyltransferase assay, we established a tractable screening platform and performed a 500,000-compound biochemical high-throughput screen, identifying an initial hit (compound 1; IC50 = 197 μM). Subsequent medicinal chemistry optimization delivered progressively more potent analogs, including TNG-9333 (0.814 μM) and TNG-2673 (0.043 μM) and represented a >1000-fold improvement in biochemical potency from the starting hit. Crystal structures of human MGAT1 in apo, UDP-bound, UDP-GlcNAc-bound, and inhibitor-bound states, together with SPR and DSF analyses, revealed that this chemical series engages a previously unrecognized allosteric pocket and inhibits MGAT1 through a UDP-noncompetitive mechanism. Collectively, our work implicates N-glycosylation as a key mediator of immune evasion and establishes MGAT1 as a ligandable, structurally tractable target for small-molecule drug discovery.

CRISPR/Cas9 target discovery↗
PubMed2025

Identification and classification of ion-channels across the tree of life provide functional insights into understudied CALHM channels.

The ion channel (IC) genes encoded in the human genome play fundamental roles in cellular functions and disease and are one of the largest classes of druggable proteins. However, limited knowledge of the diverse molecular and cellular functions carried out by ICs presents a major bottleneck in developing selective chemical probes for modulating their functions in disease states. The wealth of sequence data available on ICs from diverse organisms provides a valuable source of untapped information for illuminating the unique modes of channel regulation and functional specialization. However, the extensive diversification of IC sequences and the lack of a unified resource present a challenge in effectively using existing data for IC research. Here, we perform integrative mining of available sequence, structure, and functional data on 419 human ICs across disparate sources, including extensive literature mining by leveraging advances in large language models to annotate and curate the full complement of the "channelome". We employ a well-established orthology inference approach to identify and extend the IC orthologs across diverse organisms to above 48,000. We show that the depth of conservation and taxonomic representation of IC sequences can further be translated to functional similarities by clustering them into functionally relevant groups, which can be used for downstream functional prediction on understudied members. We demonstrate this by delineating co-conserved patterns characteristic of the understudied family of the Calcium Homeostasis Modulator (CALHM) family of ICs. Through mutational analysis of co-conserved residues altered in human diseases and electrophysiological studies, we show that these evolutionarily-constrained residues play an important role in channel gating functions. Thus, by providing new tools and resources for performing large comparative analyses on ICs, this study addresses the unique needs of the IC community and provides the groundwork for accelerating the functional characterization of dark channels for therapeutic intervention.

CALHM1↗
PubMed2026

Disentangling adiposity-related and non-adiposity-related genetic pathways for type 2 diabetes.

OBJECTIVE: To identify circulating proteins associated with type 2 diabetes (T2D) risk through pathways not fully explained by body mass index (BMI), and to assess therapeutic actionability. RESEARCH DESIGN AND METHODS: We applied GWAS-by-subtraction within a genomic structural equation model to European ancestry summary statistics for T2D (74,124 cases, 824,006 controls) and BMI (n = 681,275), partitioning T2D liability into BMI-related and BMI-subtracted components. We then performed proteome-wide Mendelian randomization (MR) using cis-protein quantitative trait loci from four plasma proteomics cohorts: ARIC, deCODE, Fenland, and the UK Biobank Pharma Proteomics Project. Prioritized proteins passed sensitivity analyses with alternative MR methods and were supported by colocalization evidence. Tissue-resolution regulatory support was assessed using cis-eQTL colocalization across GTEx and pancreatic islet, subcutaneous adipose, and whole-blood resources. Actionability was evaluated using the druggable genome and Open Targets. RESULTS: GWAS-by-subtraction attenuated the genetic correlation between BMI and BMI-subtracted T2D from 0.54 (SE 0.02) to 0.35 (SE 0.02). Proteome-wide MR prioritized 29 proteins for BMI-subtracted T2D. Thirteen showed eQTL colocalization in at least one tissue, implicating liver and intermediary metabolism (GCDH, NOTCH2), pancreatic islet biology (CTRB2, MANBA), adipose and Wnt signaling (RSPO3, GALNT3), and whole blood regulatory signals (PAM, SNUPN). Sixteen proteins were classified within druggable-genome Tiers 1-3, and five had existing Open Targets compounds. CONCLUSIONS: Integrating GWAS-by-subtraction, proteome-wide MR, and colocalization nominated 29 proteins associated with T2D liability not fully explained by BMI. These findings highlight genetically supported targets for follow-up studies of T2D therapies that complement weight-centered approaches.

Journal Article↗
PubMed2025

Potential therapeutic targets for ovarian hyperstimulation syndrome revealed by proteome-wide mendelian randomization and colocalization analysis.

Ovarian hyperstimulation syndrome (OHSS) is a severe complication associated with assisted reproductive technologies, characterized by metabolic, immune and vascular disorders. Understanding the molecular mechanisms underlying OHSS could reveal potential therapeutic targets and improve patient outcomes. In this study, We aimed to utilize proteome-wide Mendelian randomization (MR) and colocalization analysis to identify plasma proteins associated with OHSS and evaluate their potential as therapeutic targets through druggability assessment. We employed proteome-wide MR analysis summary data-based Mendelian randomization (SMR) analysis and phenome-wide association study (PheWAS) analysis to establish causal relationships between plasma proteins and OHSS. Colocalization analysis confirmed overlaps between proteins and genetic signals associated with OHSS. Pathway and network analyses were conducted to explore biological functions and protein interactions, while drug-target databases were queried for potential therapeutic interventions. Our results showed that 4 key proteins, including Suprabasin (SBSN), SLAMF4 (CD244), Enolase 3 (ENO3) and Thioredoxin domain-containing protein 12 (TXNDC12) were identified as significant contributors to OHSS. Pathway enrichment and interaction analyses further supported their involvement in metabolic, immune and structural pathways related to OHSS. Drug availability for colocalized proteins reveled potential drug targets for ENO3 (2-deoxy-D-glucose), CD244 (lenalidomide) and TXNDC12 (Auranofin), while no potential drug targets were identified for SBSN. Over all, our study identified15 plasma proteins, including SBSN, CD244, ENO3, and TXNDC12, as key contributors to the risk of OHSS through MR and colocalization analysis. These proteins were involved in metabolic regulation, immune response and antioxidant pathways, highlighting potential therapeutic targets and suggesting new directions for treatment strategies.

Humans↗
PubMed2026

Genomic insights into stroke recovery: cross-phenotype associations.

Stroke is a major cause of long-term disability with variable recovery. While clinical factors such as initial severity play a role, genetic factors are increasingly recognized as important contributors to stroke recovery. Genotype studies are generally focused on a single post-stroke behavioural domain, but some genes might relate to broad mechanisms of plasticity. This study therefore aimed to identify cross-phenotypic genetic variants associated across two or more stroke recovery domains. DNA from Stroke, Stress, Rehabilitation, and Genetics study participants was genotyped, resulting in 9 814 610 variants. In order to examine cross-phenotypic results, we first conducted genome-wide association studies on the six recovery domains: motor (grip force), cognition (Telephone Montreal Cognitive Assessment), depression (Patient Health Questionnaire-8), stress (Primary Care Post-Traumatic Stress Disorder Screen), functional status (Stroke Impact Scale-Activities of Daily Living), and disability (modified Rankin Scale 0-2 versus 3-6), some of which were tested longitudinally, yielding nine phenotypes. Models were adjusted for age, sex, initial severity (NIH Stroke Scale score), and ancestry. Cross-phenotype associations were identified by evaluating single nucleotide polymorphisms (SNPs) associated (P < 5e-5) with multiple phenotypes. To determine how these genetic variants may relate to biological mechanisms of recovery, we conducted gene enrichment analyses. Participants (n = 565, 59% male) had mild-moderate initial stroke severity (median acute NIH Stroke Scale score = 4). After accounting for the correlation structure among the nine phenotypes, we observed 319 cross-phenotypic SNPs, 3.45 times the expected number. Five of the cross-phenotypic SNPs were linked to genes relevant to neural development, function and plasticity, e.g. ERICH1 (rs11778883-C), FOX3 (rs55726768-G), LIFR-AS1 (rs76401391-T), RPS6KA2 (rs113518460-C) and TUBGCP2 (rs147150392-C), as were enrichments in RAB5-EEA1, CTNNA1-CTNNB1, CIN85-SH3GL2 and ELMO1-DOCK2 complexes. Multiple gene enrichments were found, e.g. Stroke Impact Scale-Activities of Daily Living and Patient Health Questionnaire 8 at 3 months were enriched for CREB phosphorylation, which is important for long-term potentiation. We identified cross-phenotypic SNPs associated with multiple behavioural domains of stroke recovery. Some of these genes encode, or regulate, druggable proteins. These genetic factors are not well captured by clinical or neuroimaging assessments and so provide a unique window into stroke recovery. These findings, if validated, suggest that some genes may be broadly important to stroke recovery.

GWAS↗
PubMed2026

CARM1 in human cancer: a multifunctional epigenetic node driving tumor plasticity and therapeutic vulnerability.

Coactivator-associated arginine methyltransferase 1 (CARM1/PRMT4) is a signal-responsive epigenetic regulator that couples oncogenic and stress signals to chromatin, transcription, RNA processing, metabolism, and genome maintenance. Its effects arise from both asymmetric arginine methylation of histone and non-histone substrates and methyltransferase-independent scaffolding activities. This review critically synthesizes the structural basis, substrate networks, methylarginine readers, and cancer-contextual functions of CARM1. We propose that its apparently opposing oncogenic and tumor-suppressive activities are determined by lineage-specific substrates, regulatory post-translational modifications, cofactor and chromatin availability, and stage- or microenvironment-dependent stress signals. We further evaluate CARM1-directed therapy using an evidence-graded framework. Catalytic inhibitors such as TP-064 and EZM2302 differ in binding mode and substrate coverage, whereas emerging degraders can remove scaffolding functions but remain constrained by delivery, E3-ligase heterogeneity, pharmacokinetics, and therapeutic-window uncertainties. Biomarker-guided synthetic-lethal and immunotherapy combinations may therefore offer the most tractable route to clinical translation. This framework positions CARM1 as a context-conditioned signal-to-chromatin translator rather than a uniformly druggable oncogene.

Humans↗
PubMed2026

Inhibition of the atypical kinase WNK1 as a therapeutic strategy in TAL-related T-cell acute lymphoblastic leukemia.

Driver mutations in T-cell acute lymphoblastic leukemia (T-ALL) rarely affect druggable kinases. However, these kinases can be aberrantly activated or repressed as secondary oncogenic events. Thus, integrating unbiased phosphoproteomics with genomic approaches may offer novel opportunities for target discovery and therapeutic interventions. In our study, we identified WNK1 (with no lysine [K]) as a potential target in T-ALL by pairing a list of vulnerable kinases with data from a phosphoproteomic screen of T-ALL cell lines. We subsequently validated WNK1 by loss-of-function-based studies and tested WNK inhibitors in several in vitro and in vivo T-ALL models and clinical T-ALL samples. We showed that therapeutic WNK1 repression promotes polyploidy, resulting in cell proliferation arrest, and morphometric changes, such as incomplete cell division or chromosome segregation through altered mitotic spindle assembly and abscission defects. Furthermore, we found that WNK1 is overexpressed in the TAL1/2-related subgroup, but not in normal thymus or lymph nodes, suggesting a potential translational area for clinical exploitation in poor-prognosis T-ALL carrying PTEN mutations and del(6q). Our work also reports a functional contribution of WNK1 in the leukemia establishment and progression. Structurally WNK1 is an atypical serine/threonine kinase that diverges from canonical kinases by lacking the conserved lysine in subdomain II, instead featuring a cysteine in subdomain I, which is critical for adenosine triphosphate (ATP) binding. This unusual structural configuration creates a distinct ATP-binding pocket with limited sequence similarity to conventional kinases, offering a unique opportunity to develop highly selective small molecules. Targeting this atypical ATP domain could thus provide a therapeutic advantage and broaden the treatment landscape for T-ALL.

WNK Lysine-Deficient Protein Kinase 1↗