Biology subjects

Wolff, D. S.

Publications and source records attributed to Wolff, D. S..

5 recordsLinked to original sources

bioRxiv2026

Accelerating multi-objective VHH discovery via integrated high-throughput selection and AlphaFold3-guided structure prediction

Discovering therapeutic antibodies that bind multiple related targets with high affinity and favourable biophysical properties remains challenging and resource intensive. For snakebite antivenoms, this challenge is critical as treatments must neutralise toxins across multiple snake species. We developed a pipeline combining high-throughput yeast screening, deep sequencing, and AlphaFold3 structure prediction to rapidly identify poly-specific variable domains of heavy-chain-only antibodies (VHHs) against long-chain -neurotoxins. Multiplexed yeast display screening generated a dataset of diverse candidates with varying binding specificities. AlphaFold3-generated VHH-toxin complex predictions enabled structure-based prioritisation that accurately predicted poly-specific binders targeting conserved epitopes across multiple toxins. These structural insights enabled computational optimisation of both affinity and solubility without disrupting target recognition. Experimental validation confirmed improved variants maintained broad specificity across toxins. This integrated approach accelerates multi-objective antibody discovery by predicting which candidates will bind multiple targets before extensive laboratory testing, providing a generalisable strategy applicable beyond antivenoms to any therapeutic requiring broad target coverage.

bioengineering↗

bioRxiv2025

Clearing the whey: Efficient inhibition and removal of chymosin from whey by de novo designed protein-based inhibitors

Chymosins are indispensable as coagulants in cheese production. However, the residual activity of these enzymes in the whey by-product limits downstream processing for further food applications, e.g. infant milk formulations or protein powder for athletic purposes. To date, inactivation of coagulants and other enzymes is primarily achieved through heat inactivation (pasteurisation), which remains a challenging and energy-intensive task at an industrial scale and may have adverse effects on the quality. Here, we report the de novo design of small protein minibinders (miBds) that inhibit coagulant activity which marks one of the first industrial applications of generative binder design. Using RFdiffusion1, ProteinMPNN2, and AlphaFold23, we generated and filtered over 2,000 backbone designs to a final panel of 63 candidates targeting bovine and camel chymosins. The first round of selected binders exhibited low-nanomolar Kiapp 4,5 values against chymosins originating from bovine, camel, and hedgehog, with reversible, pH-dependent dissociation profiles. Notably, we identified miBds specific to bovine and camel chymosin variants, as well as broadly cross-reactive including coagulants of fungal origin. Moreover, when immobilised, the miBds efficiently removed residual chymosin from whey. It was possible to recycle the miBd-coated resin repeatedly through treatment of the resin with high pH (> 11) or low pH (< 3) which emulates industry standard clean-in-place procedures. This dual functionality, of inhibition and reversible capture of chymosin, enables a versatile application for sustainable food production and precise control of proteases and can be extended to other enzyme classes in dairy.

bioengineering↗

bioRxiv2025

Generalizable direct protein sequencing with InstaNexus

Protein-based therapeutics, such as antibodies and nanobodies, are not encoded in reference genomes, challenging their accurate characterization via standard proteomics. Current methods rely on indirect inference, fragmented outputs, and labor-intensive workflows, which hinder functional insights and routine application. Here, we present a generalizable, end-to-end workflow for direct protein sequencing, combining streamlined sample preparation, AI-driven de novo peptide sequencing, and tailored assembly to reconstruct contiguous protein sequences. A novel composite scoring framework prioritises longer assemblies and coverage, enhancing accuracy and reducing ambiguity. Validation across diverse protein modalities demonstrates its utility and ability to robustly sequence functionally critical regions of selected proteins. This workflow represents an advance in precision proteomics with promising applications in therapeutic discovery, immune profiling, and protein science.

bioinformatics↗

bioRxiv2023

Simplified post-assembly plasmid library amplification for increased transformation yields in E. coli and S. cerevisiae

Many biological disciplines rely upon the transformation of host cells with heterologous DNA, the limited efficiency of which can significantly hinder a researchers work. Directed evolution in particular typically requires the screening of large (thousand-billion member) libraries to identify sequences of interest, and the creation of these libraries at large enough scales to overcome transformation inefficiencies is a cost-and time-intensive process. We simplify this process by using Rolling Circle Amplification (RCA) to amplify in vitro plasmid DNA assembly reactions, followed by facile resolution of the concatomeric products to monomers through treatment with specific endonucleases and subsequent efficient transformation of the linear DNA products into host cells for in vivo circularisation. We demonstrate that use of a nicking endonuclease to generate homologous single-stranded ends increases the efficiency of E. coli chemical transformation versus both linear DNA with double-stranded homologous ends, and circular golden-gate assembly products, whilst use of a restriction endonuclease to generate linear DNA with double-stranded homologous ends increases the efficiency of chemical and electrotransformation of S. cerevisiae. Importantly, we also optimise the process such that both RCA and endonuclease treatment occur efficiently in the same buffer, streamlining the workflow and reducing product loss through purification steps. We expect our approach to have utility beyond directed evolution in E. coli and S. cerevisiae, to areas such as genome engineering and the manipulation of alternative organisms with even poorer transformation efficiencies.

synthetic biology↗

bioRxiv2023

Machine-learning guided Venom Induced Dermonecrosis Analysis tooL: VIDAL

Snakebite envenoming is a global public health issue that causes significant morbidity and mortality, particularly in low-income regions of the world. The clinical manifestations of envenomings vary depending on the snakes venom, with paralysis, haemorrhage, and necrosis being the most common and medically relevant effects. To assess the efficacy of antivenoms against dermonecrosis, a preclinical testing approach involves in vivo mouse models that mimic local tissue effects of cytotoxic snakebites in humans. However, current methods for assessing necrosis severity are time-consuming and susceptible to human error. To address this, we present the Venom Induced Dermonecrosis Analysis tool (VIDAL), a machine-learning-guided image-based solution that can automatically identify dermonecrotic lesions in mice, adjust for lighting biases, scale the image, extract lesion area and discolouration, and calculate the severity of dermonecrosis. We also introduce a new unit, the dermonecrotic unit (DnU), to better capture the complexity of dermonecrosis severity. Our tool is comparable to the performance of state-of-the-art histopathological analysis, making it an accessible, accurate, and reproducible method for assessing dermonecrosis. Given the urgent need to address the neglected tropical disease that is snakebite, high-throughput technologies such as VIDAL are crucial in developing and validating new and existing therapeutics for this debilitating disease.

pharmacology and toxicology↗