Biology subjects

Koehler, A. N.

Publications and source records attributed to Koehler, A. N..

5 recordsLinked to original sources

bioRxiv2025

Chemical Probe Discovery for DEAD-box RNA Binding Protein DDX21 using Small Molecule Microarrays

The DEAD-box family of ATPases plays a critical role in nearly all stages of RNA metabolism, from transcription to degradation, and serves as a major regulator of biomolecular condensates. Dysregulation of DEAD-box proteins is well established in a variety of diseases, including cancer and neurodegenerative disorders, making them attractive therapeutic targets. However, their classification as "undruggable" has historically hindered small molecule-based modulation. In this study, we focus on DDX21, a member of the DEAD-box family involved in ribosome biogenesis and transcriptional regulation. As a proof of concept for targeting such RNA-binding proteins, we developed a lysate-based small molecule microarray platform to identify compounds that directly bind DDX21. This screen led to the discovery of KI-DX-014, a small molecule compound capable of inhibiting DDX21 interaction with RNA. KI-DX-014 modulated RNA-dependent functions of DDX21, including its ATPase activity and biomolecular condensate formation. Furthermore, KI-DX-014 attenuated the DDX21-dependent release of P-TEFb from the 7SK snRNP complex in vitro, suppressed P-TEFb-dependent phosphorylation of the RNA polymerase II CTD, and induced developmental defects in zebrafish embryos. These findings reveal a previously unexploited therapeutic avenue and establish KI-DX-014 as a valuable chemical probe for dissecting the biological functions of DDX21 in both normal physiology and disease states.

cancer biology↗

bioRxiv2025

Small Molecule Modulators of TOX protein to Re-invigorate T cell Activity

The TOX protein (thymocyte selection-associated high mobility group box) is a critical transcription factor implicated in both T acute lymphoblastic leukemia (T-ALL) and CD8+ T cell exhaustion. Gene perturbation studies suggest that inhibiting TOX may have therapeutic implications for both leukemia and T cell exhaustion. However, due to its complex molecular mechanisms and intrinsically disordered structure, TOX has not been effectively targeted by small molecules to date. In this study, we used small molecule microarray (SMM) screening and biochemical assays to identify a series of TOX protein-protein interaction (PPI) inhibitors. We identified KI-TOX-A3 as a TOX protein binder and potent TOX PPI inhibitor. In T-ALL, KI-TOX-A3 revealed selective cytotoxicity and proteosome-dependent TOX degradation. In CD8+ T cells, KI-TOX-A3 potently reversed T cell exhaustion by decreasing surface inhibitory receptors, increasing expression of effector cytokines, and enhancing cancer cell killing activity. We also demonstrate the utility of KI-TOX-A3 to probe potential epigenetic regulatory mechanisms of TOX via KAT7 acetylation in T cells.

biochemistry↗

bioRxiv2024

Targeted Degradation of CDK9 Potently Disrupts the MYC Transcriptional Network

Cyclin-dependent kinase 9 (CDK9) coordinates signaling events that regulate RNA polymerase II (Pol II) pause-release states. It is an important co-factor for transcription factors, such as MYC, that drive aberrant cell proliferation when their expression is deregulated. CDK9 modulation offers an approach for attenuating dysregulation in such transcriptional programs. As a result, numerous drug development campaigns to inhibit CDK9 kinase activity have been pursued. More recently, targeted degradation has emerged as an attractive approach. However, comprehensive evaluation of degradation versus inhibition is still critically needed to assess the biological contexts in which degradation might offer superior therapeutic benefits. We validated that CDK9 inhibition triggers a compensatory mechanism that dampens its effect on MYC expression and found that this feedback mechanism was absent when the kinase is degraded. Importantly, CDK9 degradation is more effective than its inhibition for disrupting MYC transcriptional regulatory circuitry likely through the abrogation of both enzymatic and scaffolding functions of CDK9. Highlights- KI-CDK9d-32 is a highly potent and selective CDK9 degrader. - KI-CDK9d-32 leads to rapid downregulation of MYC protein and mRNA transcripts levels. - KI-CDK9d-32 represses canonical MYC pathways and leads to a destabilization of nucleolar homeostasis. - Multidrug resistance ABCB1 gene emerged as the strongest resistance marker for the CDK9 PROTAC degrader.

cancer biology↗

bioRxiv2023

Rapid-kinetics degron benchmarking reveals off-target activities and mixed agonism-antagonism of MYB inhibitors

Attenuating aberrant transcriptional circuits holds great promise for the treatment of numerous diseases, including cancer. However, development of transcriptional inhibitors is hampered by the lack of a generally accepted functional cellular readout to characterize their target specificity and on-target activity. We benchmarked the direct gene-regulatory signatures of six agents reported as inhibitors of the oncogenic transcription factor MYB against targeted MYB degradation in a nascent transcriptomics assay. The inhibitors demonstrated partial specificity for MYB target genes but displayed significant off-target activity. Unexpectedly, the inhibitors displayed bimodal on-target effects, acting as mixed agonists-antagonists. Our data uncover unforeseen agonist effects of small molecules originally developed as TF inhibitors and argue that rapid-kinetics benchmarking against degron models should be used for functional characterization of transcriptional modulators.

molecular biology↗

bioRxiv2021

Massively parallel pooled screening reveals genomic determinants of nanoparticle-cell interactions

To accelerate the translation of cancer nanomedicine, we hypothesize that integrated genomic screens will improve understanding of the cellular processes governing nanoparticle trafficking. We developed a massively parallel high-throughput screening method leveraging barcoded, pooled cancer cell lines annotated with multi-omic data to investigate cell association patterns across a nanoparticle library spanning a range of formulations with clinical potential. This approach identified both the materials properties and cell-intrinsic features mediating nanoparticle-cell association. Coupling the data with machine learning algorithms, we constructed genomic nanoparticle trafficking networks and identified nanoparticle-specific biomarkers, including gene expression of SLC46A3. We engineered cell lines to validate SLC46A3 as a biomarker whose expression inversely predicts liposomal nanoparticle uptake both in vitro and in vivo. We further demonstrated the predictive capabilities extend beyond liposomal nanoparticles, regulating both uptake and transfection efficacy of solid lipid nanoparticles. Our work establishes the power of massively parallel pooled cell screens for nanoparticle delivery and enables the identification and utilization of biomarkers to rationally design nanoformulations for specific patient populations.

bioengineering↗