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E3 ubiquitin ligases (E3s) confer specificity of protein degradation through ubiquitination of substrate proteins. Yet, the vast majority of the >600 human E3s have no known substrates. To identify proteolytic E3-substrate pairs at scale, we developed combinatorial mapping of E3 targets (COMET), a framework for testing the role of many E3s in degrading many candidate substrates within a single experiment. We applied COMET to SCF ubiquitin ligase subunits that mediate degradation of target substrates (6,716 F-box-ORF [open reading frame] combinations) and E3s that degrade short-lived transcription factors (TFs) (26,028 E3-TF combinations). Our data suggest that many E3-substrate relationships are complex rather than 1:1 associations. Finally, we leverage deep learning to predict the structural basis of E3-substrate interactions and probe the strengths and limits of such models. Looking forward, we consider the practicality of transposing this framework, i.e., computational structural prediction of all possible E3-substrate interactions, followed by multiplex experimental validation.
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http://dx.doi.org/10.1016/j.molcel.2025.01.016 | DOI Listing |
Cereb Cortex
August 2025
Department of Psychology, University of Milano-Bicocca, Milan, Italy.
Semantic composition allows us to construct complex meanings (e.g., "dog house", "house dog") from simpler constituents ("dog", "house").
View Article and Find Full Text PDFFerroptosis, an iron-dependent cell death pathway driven by lipid peroxidation, has emerged as a critical pathophysiological mechanism linking cancer and inflammatory diseases. The seemingly distinct pathologies exhibit shared microenvironmental hallmarks-oxidative stress, immune dysregulation, and metabolic reprogramming-that converge on ferroptosis regulation. This review synthesizes how ferroptosis operates at the intersection of these diseases, acting as both a tumor-suppressive mechanism and a driver of inflammatory tissue damage.
View Article and Find Full Text PDFNature
September 2025
Microsoft Research, Cambridge, UK.
Artificial intelligence (AI) and combinatorial optimization drive applications across science and industry, but their increasing energy demands challenge the sustainability of digital computing. Most unconventional computing systems target either AI or optimization workloads and rely on frequent, energy-intensive digital conversions, limiting efficiency. These systems also face application-hardware mismatches, whether handling memory-bottlenecked neural models, mapping real-world optimization problems or contending with inherent analog noise.
View Article and Find Full Text PDFCommun Biol
August 2025
CerCo, CNRS UMR5549, Toulouse, France.
Electrophysiological and neuroimaging studies have revealed how the brain encodes various visual categories and concepts. An open question is how combinations of multiple visual concepts are represented in terms of the component brain patterns: are brain responses to individual concepts composed according to algebraic rules? To explore this, we generated "conceptual perturbations" in neural space by averaging fMRI responses to images with a shared concept (e.g.
View Article and Find Full Text PDFMethods
August 2025
Science Center for Future Foods, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China; School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China. Electronic address:
We optimized permeabilization for CUT&Tag in S. pombe, enabling robust H3K9me3 profiling using lightly fixed permeabilized sepheroplasts, overcoming limitations of ChIP-seq including crosslinking artifacts and high cell input. We established an optimized Cleavage Under Targets and Tagmentation (CUT&Tag) protocol for high-resolution epigenome profiling inSchizosaccharomyces pombeusing Critical permeabilization refinements identified Lywallzyme as the optimal enzyme for spheroplast generation (>95 % efficiency in 60 min at 10 mg/mL), outperforming Zymolyase-20 T and combinatorial treatments.
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