Biology subjects

Hardy, B.

Publications and source records attributed to Hardy, B..

7 recordsLinked to original sources

bioRxiv2026

Integrated Skin Sensitization Assessment Using Consensus Modelling and Tiered New Approach Methodology: A SaferSkin Case Study

The transition toward animal-free safety assessment of chemicals has accelerated the development of New Approach Methodologies (NAMs) for predicting skin sensitization. However, individual in silico models and experimental NAM assays frequently produce inconsistent or contradictory results, limiting their reliability when used in isolation. To address this challenge, we present a tiered integrated assessment framework implemented through the open source SaferSkin application, which enables systematic comparison and integration of multiple predictive models and experimental data within a transparent weight-of-evidence workflow. In this case study, a diverse set of 21 reference compounds was evaluated using a battery of in silico approaches, including the OECD QSAR Toolbox, VEGA, CASE Ultra and additional machine-learning models implemented within SaferSkin. The platform enables side-by-side comparison of predictions and integration of experimental data through Bayesian network models, allowing probabilistic updating of predictions as new evidence becomes available. Our results demonstrate that reliance on any single predictive model is insufficient for robust hazard identification due to frequent disagreement between models. In contrast, consensus interpretation across multiple modelling approaches combined with targeted experimental evidence substantially improves predictive confidence. The integrated weight-of-evidence framework showed strong concordance with reference classifications and was further supported by independent validation using the Pred-Skin Bayesian model. Importantly, the tiered workflow enables resolution of ambiguous cases. For example, lower-tier predictions for ethyl (2E,4Z)-deca-dienoate were inconsistent across models, whereas targeted third-tier testing using the SENS-IS assay identified the compound as a strong sensitiser (GHS Category 1A). Overall, this study demonstrates how integrated modelling, Bayesian evidence updating and targeted NAM testing can reduce uncertainty in skin sensitization assessment. The SaferSkin framework provides a transparent and reproducible approach for implementing Next Generation Risk Assessment (NGRA) strategies and supports the development of animal-free regulatory toxicology and Safe-and-Sustainable-by-Design chemical innovation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/711911v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@196a52eorg.highwire.dtl.DTLVardef@13690a6org.highwire.dtl.DTLVardef@1528703org.highwire.dtl.DTLVardef@11e05d2_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

pharmacology and toxicology↗

bioRxiv2026

AOPGraphExplorer 2.0: An Interactive Graph-Based Platform for Multi-Domain Mechanistic Annotation and Exploration of Adverse Outcome Pathways

The Adverse Outcome Pathway (AOP) framework is a cornerstone of modern mechanistic toxicology, providing a structured representation of causal biological events linking molecular initiating events to adverse health outcomes. However, the practical exploration and interpretation of AOPs remain challenging due to the fragmentation of mechanistic knowledge across heterogeneous biological databases and the limited availability of integrated, interactive tools. Here, we present AOPGraphExplorer 2.0, an interactive graph-based platform for the visualization, annotation, and analysis of AOP networks derived from AOP-Wiki. This new version introduces a scalable, modular architecture that integrates multi-domain mechanistic annotations, including biological processes, molecular entities, anatomical context, diseases, and stressors, directly into AOP graphs. AOPGraphExplorer 2.0 enables dynamic filtering of AOP networks based on weight-of-evidence and quantitative understanding scores, supports AOP-, Key Event-, and keyword-centric queries, and generates exportable interactive HTML and machine-readable JSON representations for documentation, sharing, and computational reuse. In addition, the platform provides automated network statistics and annotation coverage summaries, supporting transparent and reproducible analysis. By bridging AOP-Wiki with external biomedical knowledge resources in a unified graph framework, AOPGraphExplorer 2.0 transforms AOP exploration into a multi-domain systems-level analysis workflow. The platform supports hypothesis generation, mechanistic interpretation, and evidence-based decision-making in toxicology, pharmacology, and risk assessment.

systems biology↗

bioRxiv2025

Expansion of DNA-Encoded Library Hits Using Generative Chemistry and Ultra-Large Compound Catalogs

DNA-encoded libraries (DELs) are powerful tools for initial hit identification, yet the combinatorial chemistries and building block choices used in their construction can restrict chemical space coverage and hit drug-likeness, limiting efficient hit expansion. Generative artificial intelligence (AI), by contrast, can in principle explore drug-like chemical space around any given compound, but it often struggles with the synthesizability of generated molecules and requires a set of validated hits to initiate exploration. Here, we present a synergistic methodology that overcomes these mutual limitations by leveraging experimentally validated DEL data to initialize and bias an AI-powered virtual screening pipeline, expanding initial DEL hits with both de novo and purchasable compounds from ultra-large chemical libraries. Using this approach, we identified novel and commercially available hits from the Enamine REAL Space for the chromatin reader protein 53BP1 and validated them in a time-resolved fluorescence resonance energy transfer (TR-FRET) displacement assay. Three compounds demonstrated TR-FRET IC50 values <= 50 uM, while 11 exhibited IC50 values <= 100 uM. Critically, the AI-nominated hits exhibited greater chemical diversity, improved drug-likeness, and were readily purchasable off-the-shelf compared to compounds from the initial DEL selection. This work demonstrates a streamlined platform in which empirical DEL data and generative chemistry models are combined to enable rapid hit expansion from initially screened libraries into diverse, commercially available chemical matter.

biophysics↗

bioRxiv2024

A host-directed adjuvant resuscitates and sensitizes intracellular bacterial persisters to antibiotics

There are two major problems in the field of antimicrobial chemotherapy-antibiotic resistance and antibiotic tolerance. In the case of antibiotic tolerance, antibiotics fail to kill the bacteria as their phenotypic state affords them protection from the bactericidal activity of the antibiotic. Antibiotic tolerance can affect an entire bacterial population, or a subset of cells known as persister cells. Interaction with the host induces the formation of persister cells in numerous pathogens, with reactive oxygen and nitrogen species production being heavily implicated in the collapse of bacterial energy levels and entrance into an antibiotic tolerant state. Here, we developed a high-throughput screen to identify energy modulators for intracellular Staphylococcus aureus. The identified compound, KL1, increases intracellular bacterial energy and sensitizes the persister population to antibiotics, without causing cytotoxicity or bacterial outgrowth. We demonstrate that KL1 exhibits adjuvant activity in a murine model of S. aureus bacteremia and intracellular infection of Salmonella Typhimurium. Transcriptomic analysis and further studies on its mechanism of action reveal that KL1 modulates host immune response genes and suppresses the production of reactive species in host macrophages, alleviating one of the major stressors that induce antibiotic tolerance. Our findings highlight the potential to target intracellular persister cells by stimulating their metabolism and encourage larger efforts to address antibiotic tolerance at the host-pathogen interface, particularly within the intracellular milieu.

microbiology↗

bioRxiv2024

Skin Sensitisation Case Study: Comparison of Defined Approaches including OECD 497 Guidance

Characterising known and new chemical compounds for skin sensitisation provides a basis for the development of safer products where ingredients are exposed to skin. By including new approaches, such as tiered testing strategies and integrated data analysis, it is possible to develop next generation products adhering to emerging regulations, scientific evidence and animal welfare principles. To ensure data integrity during such assessment the OECD provides characterisation guidelines and Defined Approaches (DAs) to uniform work-flows. In this study we developed and applied the integrated characterisation tool called < > to compare the results of different DAs for eight compounds and included results obtained from current OECD guidance and emerging methods. We tested two compounds with unclear or indeterminate results with the SENS-IS assay to explore the value of the experiment in strengthening the weight of evidence and arriving at a clearer conclusion.

pharmacology and toxicology↗

bioRxiv2021

REPROGRAMMING CBX8-PRC1 FUNCTION WITH A POSITIVE ALLOSTERIC MODULATOR

ABSTRACTCanonical targeting of Polycomb Repressive Complex 1 (PRC1) to repress developmental genes is mediated by cell type-specific, paralogous chromobox (CBX) proteins (CBX2, 4, 6, 7 and 8). Based on their central role in silencing and their misregulation associated with human disease including cancer, CBX proteins are attractive targets for small molecule chemical probe development. Here, we have used a quantitative and target-specific cellular assay to discover a potent positive allosteric modulator (PAM) of CBX8. The PAM activity of UNC7040 antagonizes H3K27me3 binding by CBX8 while increasing interactions with nucleic acids and participation in variant PRC1. We show that treatment with UNC7040 leads to efficient PRC1 chromatin eviction, loss of silencing and reduced proliferation across different cancer cell lines. Our discovery and characterization of UNC7040 not only revealed the most cellularly potent CBX8-specific chemical probe to date, but also corroborates a mechanism of polycomb regulation by non-histone lysine methylated interaction partners.

synthetic biology↗

bioRxiv2020

Precision design of single and multi-heme de novo proteins

The de novo design of simplified porphyrin-binding helical bundles is a versatile approach for the construction of valuable biomolecular tools to both understand and enhance protein functions such as electron transfer, oxygen binding and catalysis. However, the methods utilised to design such proteins by packing hydrophobic side chains into a buried binding pocket for ligands such as heme have typically created highly flexible, molten globule-like structures, which are not amenable to structural determination, hindering precise engineering of subsequent designs. Here we report the crystal structure of a de novo two-heme binding "maquette" protein, 4D2, derived from the previously designed D2 peptide, offering new opportunities for computational design and re-engineering. The 4D2 structure was used as a basis to create a range of heme binding proteins which retain the architecture and stability of the initial crystal structure. A well-structured single-heme binding variant was constructed by computational sequence redesign of the hydrophobic protein core, assessed by NMR, and utilised for experimental validation of computational redox prediction and design. The structure was also extended into a four-heme binding helical bundle resembling a molecular wire. Despite a molecular weight of only 24kDa, imaging by CryoEM illustrated a remarkable level of detail in this structure, indicating the positioning of both the secondary structure and the heme cofactors. The design and determination of atomic-level resolution in such de novo proteins is an invaluable resource for the continued development of novel and functional protein tools.

synthetic biology↗