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Stephan C. Schürer

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Jul 2026

Abstract B085: Selective oral STK17A inhibitor UMF814A targets a previously unrecognized dark kinase vulnerability in spliceosome-mutant MDS and AML

Myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML) remain therapeutically challenging, particularly in patients with spliceosome-mutant disease, where effective targeted options are lacking. Mutations in SF3B1, SRSF2, and U2AF1 define a biologically distinct subset associated with aberrant RNA splicing and poor clinical outcomes. Through integrated functional and transcriptomic analyses, we identified the dark kinase, STK17A, as a selectively upregulated and targetable kinase dependency in spliceosome-mutant malignancies. Here, we report the discovery and preclinical validation of first-in-class, orally bioavailable STK17A inhibitors with potent and selective activity in genetically defined MDS/AML models. A quinazoline-based lead scaffold was selected based on potency, kinase selectivity, and favorable drug metabolism and pharmacokinetic (DMPK) properties. Medicinal chemistry optimization focused on three peripheral regions while preserving the quinazoline and aminopyrimidine cores. Structure–activity relationship studies, kinome-wide selectivity profiling, and orthogonal counterscreens guided compound refinement. Antiproliferative activity was assessed across AML cell lines and engineered spliceosome-mutant models. Pharmacodynamic effects were evaluated by immunoblotting of downstream signaling nodes. In vivo pharmacokinetics were determined following oral dosing in C57BL/6 mice, and efficacy was evaluated in cell line–derived xenografts and patient-derived xenograft (PDX) models harboring spliceosome mutations. Lead compound UMF814A demonstrated nanomolar potency across AML models, with enhanced activity in spliceosome-mutant contexts. Notably, GI50 values were 283.0 nM, 827.0 nM and 197.3 nM in SF3B1-, SRSF2-, and U2AF1-mutant K562 cells. Mechanistically, pharmacologic inhibition of STK17A increased lipid peroxidation in spliceosome-mutant vs. WT K562 cells (∼2-fold, p≤0.01), consistent with induction of ferroptosis preferentially in spliceosome-mutant cells. Primary MDS and AML samples harboring splicing mutations were preferentially sensitive to UMF814A compared with control CD34+ cells (p≤0.0001). Following oral dosing (10 mg/kg), UMF814A demonstrated favorable pharmacokinetics, with a half-life of 7 h, Tmax of 1 h, Cmax ∼1 μM, and AUC of 9.7 μM·h. The compound was well tolerated, with no acute toxicity observed up to 300 mg/kg. In vivo, in an SF3B1-mutant CMML PDX model, 10 mg/kg oral daily dosing prevented leukemic engraftment (>10% human CD45+ cells) without weight loss over 42 days, and extended survival compared to single-agent azacitidine treatment, demonstrating robust activity in the preclinical setting. These studies establish STK17A as a previously unrecognized, druggable vulnerability via ferroptosis induction in spliceosome-mutant myeloid malignancies and position UMF814A as a novel therapeutic candidate. This work supports continued development toward IND-enabling studies to allow testing in clinical trials in patients with high-risk MDS/AML with spliceosome mutations. Eric Spinetti, Claudia C. Pastrana, Eduardo Bravo, Avni Bhalgat, Sana Chaudhry, Rabia Khursid, Stephan Schürer, Justin Watts, Yangbo Feng, Justin Taylor. Selective oral STK17A inhibitor UMF814A targets a previously unrecognized dark kinase vulnerability in spliceosome-mutant MDS and AML [abstract]. In: Proceedings of AACR Drug Discovery and Development (AACR D3) Conference; 2026 Jul 21-24; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(14_Suppl):Abstract nr B085.

E. Spinetti, C. C. Pastrana, E. Bravo et al. · 0 citations
Open access Jul 2026

From Ternary Modeling to Predictive PROTAC Design: A Computational Perspective

Proteolysis-targeting chimeras (PROTACs) are heterobifunctional small molecules that induce targeted protein degradation by recruiting an E3 ligase to a protein of interest. Since 2019, publication volume has accelerated, and computational methods have expanded from isolated demonstrations into practical tools for modeling PROTAC-induced ternary complexes, designing linkers, and forecasting degradation-related outcomes. Here, we present a Perspective on computational PROTAC methodologies published from 2019 to the present, organizing the field into two complementary streams: (i) constraint-driven, physics-based workflows that assemble and refine ternary complex models by enforcing geometric feasibility and evaluating pose stability using docking and molecular simulation; and (ii) data-driven workflows, including deep learning predictors and generative models that predict ternary complex structure, degradation end points, or linker chemistry from structural and assay data. We highlight representative approaches spanning restrained/tethered docking, MD-based refinement and dynamic stability scoring, coarse-grained free-energy modeling, SE(3)/E(3)-equivariant structure prediction, supervised degradation efficacy prediction, and generative linker design. We close by emphasizing persistent gaps, fragmented benchmarking, score robustness across targets and E3 ligases, and nonstandard molecular representations that currently limit generalization and reproducible, pipeline-ready deployment.

Joseph M. Schulz, R. Reynolds, Stephan C. Schürer · 0 citations

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