Biology subjects

Ohmayer, U.

Publications and source records attributed to Ohmayer, U..

6 recordsLinked to original sources

bioRxiv2026

Discovery of CDK4-selective molecular glue degraders by high-throughput proteomics

Molecular glue degraders (MGDs) are proximity-inducing molecules that promote the destruction of disease-causing proteins by stabilizing novel interfaces between E3 ubiquitin ligases and target proteins. The rational design of MGDs remains exceptionally challenging, historically relying on serendipitous discoveries. Here, we deployed a high-throughput, mass spectrometry (MS)-based screen evaluating thousands of cereblon (CRBN)-directed compounds to expedite the identification of novel neosubstrates. This workflow led to the discovery of NE26394, a first-in-class MGD that selectively eliminates cyclin-dependent kinase 4 (CDK4), a critical oncogenic driver of cell cycle progression. Mechanistically, NE26394-induced CDK4 recognition by CRBN depends on the co-recruitment of endogenous INK4 family proteins. In CDK4-dependent cancer models, NE26394 effectively mimics the anti-proliferative RB-E2F pathway perturbations induced by clinical CDK4 inhibitors, rendering it an attractive candidate for further preclinical development.

biochemistry↗

bioRxiv2026

Integrated proteomic screening reveals design principles of CRBN molecular glue degraders

Cereblon (CRBN)-based molecular glue degraders (MGDs) induce the degradation of diverse disease-relevant proteins, underscoring their broad therapeutic potential. Here we systematically expand the CRBN neosubstrate landscape using a target-agnostic discovery approach. By integrating deep proteomic and ubiquitinomic profiling of a 960-compound library, we identify compound-induced ubiquitination and depletion of over 230 endogenous proteins. Among these, 124 represent previously unreported CRBN neosubstrates, with over half lacking a predicted G-loop degron. We provide this dataset via an interactive resource, NeosubstratesDB. Complementary cellular and biochemical assays mechanistically define the interaction domain of IRAK1 and establish G-loop-dependent degradation for BCL6. Interpretable machine learning (iML) integrating proteomic profiles with chemical structures highlights key molecular fingerprints driving neosubstrate selectivity for targets such as CSNK1A1, ZFP91 and WEE1. Together, these findings significantly expand the repertoire of CRBN neosubstrates and provide a framework for rational design of next-generation MGDs.

biochemistry↗

bioRxiv2026

Developing Potent and Selective TBK1 Molecular Glue Degraders for Cancer Immunotherapy

Immune checkpoint blockade (ICB) has transformed cancer therapy across multiple tumour types, yet primary and acquired resistance remain major barriers to durable benefit. TANK-binding kinase 1 (TBK1) has emerged as an attractive target to enhance anti-tumour immunity, acting as a serine/threonine kinase that restrains immunogenic cell death and downstream immune activation. Here we report the discovery of a first-in-class TBK1 molecular glue degrader (MGD), CCT412020, identified through high-throughput proteomics screening of a next-generation molecular glue library. CCT412020 induces rapid, potent and selective TBK1 degradation across a panel of breast cancer cell lines. A cryo-EM structure of CCT412020 in complex with CRBN/{Delta}BPB-DDB1 and TBK1-homodimer reveals an unexpected binding mode that bypasses the canonical G-loop and instead engages an unconventional site at the TBK1 homodimer interface. Functionally, TBK1 loss via CCT412020 sensitises tumour cells to TNF- and interferon-driven responses and reduced viability across a broad range of cancer cell lines. Together, these findings establish CCT412020 as a mechanistically distinct TBK1 degrader and provide a framework for developing TBK1-targeted degraders as immunomodulatory anti-cancer agents to overcome ICB resistance.

cancer biology↗

bioRxiv2024

Unbiased mapping of cereblon neosubstrate landscape by high-throughput proteomics

Molecular glue degraders (MGDs) are small molecules that harness the ubiquitin-proteasome system to induce degradation of target proteins, including those lacking conventional druggable pockets. Given the challenges in their rational design, MGD discovery predominantly relies on screening-based approaches, such as cell viability assays. However, one potential limitation of such screening methods is the risk of overlooking non-essential neosubstrates of potential therapeutic value. To address this concern, we present a high-throughput proteome-wide MGD screening platform utilizing label-free, data-independent acquisition mass spectrometry (DIA-MS) for integrated proteomics and ubiquitinomics analysis. Processing a diverse set of 100 CRBN-ligands across two cancer cell lines reveals a broad array of neosubstrates, including 50 novel candidates validated by MS-based ubiquitinomics. These findings considerably expand the current landscape of CRBN-mediated neosubstrates. Comprehensive hit validation and structure-degradation relationship analyses guided by global proteomics, identifies highly selective and potent phenyl glutarimide-based degraders of novel neosubstrates, including KDM4B, G3BP2 and VCL, none of which contain the classical CRBN degron motif. This study demonstrates that comprehensive, high-throughput proteomic screening offers new opportunities in MGD drug discovery.

biochemistry↗

bioRxiv2024

High-throughput proteome profiling with low variation in a multi-center study using dia-PASEF

High throughput proteomics is gaining increasing traction as it facilitates screening of large sample cohorts required in clinical research and systems biology studies. Recent developments in mass spectrometry-based proteomics resulted in improved hardware and software providing deep proteome coverage, robustness, and scale accessible to a wide range of laboratories. Here, we benchmark dia-PASEF, a data-independent acquisition scheme that integrates trapped ion mobility with high scan speed, with a high-resolution time-of-flight mass analyzer (timsTOF HT) for the deep proteome analysis of a human cell line applying short 5-minute gradients. To show intra-and interlaboratory reproducibility, we performed a multi-laboratory study including 11 sites. We demonstrate that on average 7,072 protein groups and 99,835 peptides were identified in human chronic myelogenous leukemia cells on the timsTOF HT with low variation. Our results underline that dia-PASEF data acquisition combined with reproducible chromatography enables high robustness and data consistency across instruments and laboratories, which is a prerequisite for translational biomedical insights.

systems biology↗

bioRxiv2020

Molecular classification of the placebo effect in nausea

Numerous studies have shown that the mere expectation improvement can alleviate symptoms in various conditions. These placebo effects often include reliable changes in central and peripheral organ systems. Here, we tested for the first time whether placebo effects can be monitored and predicted by plasma proteins. In a randomized controlled design, 90 healthy participants were exposed to a 20-min vection stimulus on two separate days and were randomly allocated to placebo treatment or no treatment on the second day. Significant placebo effects on nausea, motion sickness, and gastric activity could be verified. Using state-of-the-art proteomics, 74 differentially regulated proteins were identified in placebo-treated participants as compared to no-treatment controls. Gene ontology (GO) enrichment analyses of these proteins revealed acute-phase proteins as well as microinflammatory proteins to be reliable plasma correlates of the placebo effect. Regression analyses showed that day-adjusted scores of nausea indices in the placebo group were predictable by the identified GO protein signatures. We next identified specific plasma proteins, for which a significant amount of variance could be explained by the experimental factors sex, group, nausea, or their interactions. GO enrichment analyses of these proteins identified grooming behavior as a prominent hit, based on neurexin-1 (NRXN1) and contactin-associated protein-like 4 (CNTNAP4). Finally, Receiver Operator Characteristics (ROC) allowed to identify specific plasma proteins differentiating placebo responders from non-responders. These comprised immunoglobulins (IGHM, IGKV1D-16, IGHV3-23, IGHG1) and MASP2, related to regulation of complement activation, as well as proteins involved in oxidation reduction processes (QSOX1, CP TXN). This proof-of-concept study indicates that plasma proteomics are a promising tool to identify molecular correlates and predictors of the placebo effect in humans.

neuroscience↗