Biology subjects

Isbel, L.

Publications and source records attributed to Isbel, L..

5 recordsLinked to original sources

bioRxiv2026

DesignMaster: A Multi-Conditional Diffusion Framework for Rational PROTAC Design

MotivationProteolysis-targeting chimeras (PROTACs) enable targeted protein degradation through ternary complex formation with E3 ubiquitin ligase. However, the rational design of PROTACs remains highly challenging due to limited structure-activity relationship data and the vast conformational diversity of linkers. Existing computational approaches can be broadly divided into structure-based ternary modelling methods and fragment-based linker generation models. Although these approaches have advanced PROTAC design, they typically neglect key physicochemical constraints and linker-length control during the generation process, causing the generated PROTACs to lack balanced structural properties required for effective ternary complex formation with drug-like characteristics. ResultsTo address these limitations, we propose DesignMaster, a diffusion-based generative framework that explicitly incorporates linker length and physicochemical properties as controllable conditioning signals. DesignMaster employs an E(3)-equivariant graph Transformer with a gated multi-condition fusion module to inject linker length and physicochemical constraints throughout the diffusion process, enabling fine-grained and constraint-aware molecular generation. Experiments on PROTAC-DB 2.0 and 3.0 demonstrate that DesignMaster outperforms state-of-the-art baselines, with a 3.2% improvement in validity and a 34.4% improvement in recovery. The Case study shows DesignMaster achieves a 51.78% reduction in RMSD when predicting the linker of PROTAC BCPyr targeting 6W7O, highlighting its potential for practical structure-guided PROTAC design. AvailabilityThe source code and datasets are available at https://github.com/ABILiLab/DesignMaster.

bioinformatics↗

bioRxiv2025

Accurate PROTAC targeted degradation prediction with DegradeMaster

MotivationProteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules that can degrade undruggable protein of interest (POI) by recruiting E3 ligases and hijacking the ubiquitin-proteasome system. Some efforts have been made to develop deep learning-based approaches to predict the degradation ability of a given PROTAC. However, existing deep learning methods either simplify proteins and PROTACs as 2D graphs by disregarding crucial 3D spatial information or exclusively rely on limited labels for supervised learning without considering the abundant information from unlabeled data. Nevertheless, considering the potential to accelerate drug discovery, it is critical to develop more accurate computational methods for PROTAC-targeted protein degradation prediction. ResultsThis study proposes DegradeMaster, a semi-supervised E(3)-equivariant graph neural network-based predictor for targeted degradation prediction of PROTACs. DegradeMaster leverages an E(3)-equivariant graph encoder to incorporate 3D geometric constraints into the molecular representations and utilises a memory-based pseudo-labeling strategy to enrich annotated data during training. A mutual attention pooling module is also designed for interpretable graph representation. Experiments on both supervised and semi-supervised PROTAC datasets demonstrate that DegradeMaster outperforms state-of-the-art baselines, with substantial improvement of AUROC by 10.5%. Case studies show DegradeMaster achieves 88.33% and 77.78% accuracy in predicting the degradability of VZ185 candidates on BRD9 and ACBI3 on KRAS mutants. Visualization of attention weights on 3D molecule graph demonstrates that DegradeMaster recognises linking and binding regions of warhead and E3 ligands and emphasizes the importance of structural information in these areas for degradation prediction. Together, this shows the potential for cutting-edge tools to highlight functional PROTAC components, thereby accelerating novel compound generation. AvailabilityThe source code and datasets are available at https://github.com/Jackson117/DegradeMaster and https://zenodo.org/records/14715718.

bioinformatics↗

bioRxiv2024

Chromatin-dependent motif syntax defines differentiation trajectories

Transcription factors recognizing short DNA sequences within gene regulatory regions are crucial drivers of cell identity. Despite recent advances, their specificity remains incompletely understood. Here, we address this by contrasting two TFs, NGN2 and MyoD1, which recognize ubiquitous E-box motifs yet instigate distinct cell fates--neurons and muscles, respectively. Following controlled induction in embryonic stem cells, we monitor binding across differentiation trajectories, employing an interpretable machine-learning approach integrating pre-existing DNA accessibility data. This reveals a chromatin-dependent motif syntax, delineating both common and factor-specific binding and predicting genome engagement with high precision. Shared binding sites reside in open chromatin, locally influenced by nucleosomes. In contrast, factor-specific binding in closed chromatin involves NGN2 and MyoD1 acting as pioneer-factors, influenced by multi-motifs, rotational spacing, flanking sequences, and specific interaction partners, accounting for subsequent lineage divergence. Extending our methodology to other models demonstrates how such combination of opportunistic-binding and context-specific chromatin opening underpin transcription factor specificity driving differentiation trajectories.

genomics↗

bioRxiv2022

Readout of histone methylation by Trim24 locally restricts chromatin opening by p53

The genomic binding sites of the transcription factor (TF) and tumour suppressor p53 are unusually diverse in regards to their chromatin features, including histone modifications, opening the possibility that chromatin provides context-dependence for p53 regulation. Here, we show that the ability of p53 to open chromatin and activate its target genes is indeed locally restricted by its cofactor Trim24. Trim24 binds to both p53 and unmethylated lysine 4 of histone H3, thereby preferentially locating to those p53 sites that reside in closed chromatin, while it is deterred from accessible chromatin by lysine 4 methylation. The presence of Trim24 increases cell viability upon stress and enables p53 to impact gene expression as a function of the local chromatin state. These findings link histone methylation to p53 function and illustrate how specificity in chromatin can be achieved, not by TF-intrinsic sensitivity to histone modifications, but by employing chromatin-sensitive cofactors which locally modulate TF function.

genomics↗

bioRxiv2021

ZFP462 targets heterochromatin to transposon-derived enhancers restricting transcription factor binding and expression of lineage-specifying genes

ZNF462 haploinsufficiency is linked to Weiss-Kruszka Syndrome, a genetic disorder characterized by a range of neurodevelopmental defects including Autism. Though it is highly conserved in vertebrates and essential for embryonic development the molecular functions of ZNF462 are unclear. We identified its murine homolog ZFP462 in a screen for epigenetic gene silencing in mouse embryonic stem cells (mESCs). Here, we show ZFP462 safeguards neural lineage specification by targeting the H3K9-specific histone methyltransferase complex G9A/GLP to mediate epigenetic silencing of endodermal genes. ZFP462 binds to thousands of transposable elements (TEs) that harbor ESC- and endoderm-specific transcription factor (TF) binding sites and act as enhancers. Through physical interaction with G9A/GLP, ZFP462 seeds heterochromatin at TE-derived enhancers restricting the binding of core pluripotency TFs OCT4 and SOX2. Loss of ZFP462 in ESCs results in increased chromatin accessibility at target sites and ectopic expression of endodermal genes. Taken together, ZFP462 restricts TF binding and subsequent endodermspecific gene activation by conferring lineage and locus-specificity to the broadly expressed epigenetic regulator G9A/GLP. Our results suggest that aberrant activation of endodermal genes in the neuronal lineage underlies ZNF462-associated neurodevelopmental pathology.

genetics↗