Biology subjects

Schwalb, B.

Publications and source records attributed to Schwalb, B..

7 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↗

bioRxiv2020

Integrator is a genome-wide attenuator of non-productive transcription

Termination of RNA polymerase II (RNAPII) transcription in metazoans relies largely on the Cleavage and Polyadenylation (CPA) and Integrator (INT) complexes originally found to act at the ends of protein-coding and snRNA genes, respectively. Here we monitor CPA- and INT-dependent termination activities genome-wide, including over 8000 previously unannotated transcription units (TUs), that produce unstable RNA. We verify the global activity of CPA, that occurs at pA sites indiscriminately of their positioning relative to the TU promoter. We also identify a global activity of INT, which is, however, largely sequence-independent and restricted to a ~3 kb promoter-proximal region. Our analyses suggest two functions of genome-wide INT activity; it dampens transcriptional output from weak promoters and it provides quality-control of RNAPII complexes, that are unfavorably configured for transcriptional elongation. We suggest that the function of INT in stable snRNA production is an exception from its general cellular role, attenuation of non-productive transcription.

cell biology↗

bioRxiv2019

Transient transcriptome sequencing: computational pipeline to quantify genome-wide RNA kinetic parameters and transcriptional enhancer activity

In the accompanying chapter (Gressel, Lidschreiber, Cramer), we describe the detailed experimental protocol for transient transcriptome sequencing (TT-seq). TT-seq detects metabolically labeled, newly synthesized RNA fragments genome-wide in living cells. TT-seq can monitor gene activity and the dynamics of enhancer landscapes with great sensitivity, but this requires careful computational analysis of the data. In this manuscript, we present the bioinformatics workflow used to analyze TT-seq data. In particular, we describe pre-processing steps, including a reliable and robust normalization strategy, and several downstream analysis tools that enable the user to quantify RNA synthesis, splicing and degradation activities. Together, these tools form a comprehensive analysis pipeline that can be adapted to almost any TT-seq application.

molecular biology↗

bioRxiv2019

Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoforms

Eukaryotic genes often generate a variety of RNA isoforms that can lead to functionally distinct protein variants. The synthesis and stability of RNA isoforms is however poorly characterized. The reason for this is that current methods to quantify RNA metabolism use short-read sequencing that cannot detect RNA isoforms. Here we present nanopore sequencing-based Isoform Dynamics (nano-ID), a method that detects newly synthesized RNA isoforms and monitors isoform metabolism. nano-ID combines metabolic RNA labeling, long-read nanopore sequencing of native RNA molecules and machine learning. Application of nano-ID to the heat shock response in human cells reveals that many RNA isoforms change their synthesis rate, stability, and splicing pattern. nano-ID also shows that the metabolism of individual RNA isoforms differs strongly from that estimated for the combined RNA signal at a specific gene locus. And although combined RNA stability correlates with poly(A)-tail length, individual RNA isoforms can deviate significantly. nano-ID enables studies of RNA metabolism on the level of single RNA molecules and isoforms in different cell states and conditions.

molecular biology↗