Biology subjects

Hald, A.

Publications and source records attributed to Hald, A..

6 recordsLinked to original sources

bioRxiv2026

A rapid, automation-friendly, cell-free and purification-free pipeline for binding and kinetic characterisation of de novo designed binders with high quality standardised per-design data

De novo protein binders can now be generated far faster than they can be tested. Current validation routes - display selection, cell-free two-hybrid assays, or surface-based biophysics - require cell culture, colony picking, protein purification, target labeling or sensor immobilisation, take 2 to 8 weeks, and require additional methods for affinity and kinetics characterisation. Here we report an end-to-end, cell- and purification-free pipeline that goes from gene to binding affinity and kinetics in three days without genetically modified organisms, cell culture, purification, labelling or immobilisation. An automated, metric-driven loop of RFdiffusion, ProteinMPNN and AlphaFold2 initial-guess generates and filters designs, which are ranked by Boltz-2 ipSAE, assembled by Golden Gate cloning from linear DNA, expressed in a cell-free protein synthesis lysate as fluorescent protein fusions, and screened directly in the unpurified product by flow-induced dispersion analysis (FIDA). Against human growth hormone, 11 of 30 designs (37%) bound, and the four strongest had equilibrium dissociation constants of 0.93-9.98 nM with on- and off-rates resolved from the same cell-free material. Each sample run measures expression level, hydrodynamic radius, oligomeric and aggregation state alongside the binding readout, producing the standardised, per-design datasets that model training requires.

molecular biology↗

bioRxiv2026

pH-sensitive binder design with Proton-PottsMPNN

Physiological compartments span a wide pH range, from blood plasma near pH 7.4 through the mildly acidic tumor microenvironment to the acidified endosome and lysosome, and binders whose affinity responds to these differences underpin recycling antibodies, catalytic extracellular degraders and tumor-conditional therapeutics. Such binders are still obtained mainly by combinatorial histidine scanning and display selection, which is laborious and yields few transferable design rules. Recent computational approaches have enabled the design of pH-sensitive binders that engage at physiological pH and release under acidic conditions, by introducing histidines at key positions so that protonation generates electrostatic repulsion, evaluated through physics-based calculations. However, because the design model has no explicit representation of protonation state, it cannot shape the residues around a titratable site to favor one state over the other, leaving pH sensitivity to be screened for rather than specified. Here we present Proton-PottsMPNN, a sequence-design model that explicitly represents the protonated and deprotonated states of histidine, aspartate and glutamate as distinct sequence tokens. Because protonation state is specified rather than inferred, the model redesigns the microenvironment around a titratable residue so that the chosen protonation state is energetically favored over its alternative. Using Proton-PottsMPNN we designed a library of 8,407 de novo PD-L1 candidate binders in which sequence-structure compatibility and protonation state preference were designed jointly under a single energy function, with no structure-prediction filtering applied. The full library was synthesized and displayed on yeast, then screened against PD-L1 across a series of pH values by fluorescence- and magnetic-activated cell sorting, recovering 237 and 288 unique pH-dependent designs respectively. Transition pH values spanned 4.0 to 5.8, and switches were centered on protonated aspartate and glutamate as well as histidine. Recovered designs showed a stronger model preference for their designed protonation state than designs from the same backbone that were not recovered, and this preference was strongest in the designs that required the most acidic conditions to bind. Proton-PottsMPNN therefore designs binders that engage PD-L1 under acidic conditions fully de novo, directly from a specified protonation state.

biophysics↗

bioRxiv2025

De novo designed protein enables precise epitope-level control of Gremlin-1 antagonism

Growth-factor antagonists regulate key developmental and pathological processes, yet the molecular principles governing their control remain poorly understood. Gremlin-1 (GREM1) is a secreted antagonist of bone morphogenetic proteins (BMPs) whose dysregulation is implicated in fibrosis and cancer. Here, we report a de novo designed protein that binds GREM1 with sub-nanomolar affinity and selectively releases BMPs for downstream signalling. By integrating generative deep-learning-based protein design with molecular-dynamics-derived flexibility descriptors, we identify a predictive relationship between interface rigidity, desolvation energy, and binding success. The resulting binder, RF1-2, reproduces the native BMP-binding epitope on GREM1 at near-atomic precision, as confirmed by cryo-electron microscopy, and competitively blocks BMP-2 and BMP-4 association. These results establish interface rigidity as a key physical determinant of antagonist inhibition and demonstrate how AI-guided protein design can uncover molecular principles underlying extracellular signalling control.

biochemistry↗

bioRxiv2024

Evaluation of Gremlin-1 as a therapeutic target in metabolic dysfunction-associated steatohepatitis

Gremlin-1 has been implicated in liver fibrosis in metabolic dysfunction-associated steatohepatitis (MASH) via inhibition of bone-morphogenetic protein (BMP) signalling and has thereby been identified as a potential therapeutic target. Using rat in vivo and human in vitro and ex vivo model systems of MASH fibrosis, we show that neutralisation of Gremlin-1 activity with monoclonal therapeutic antibodies does not reduce liver inflammation or liver fibrosis. Still, Gremlin-1 was upregulated in human and rat MASH fibrosis, but expression was restricted to a small subpopulation of COL3A1/THY1+ myofibroblasts. Lentiviral overexpression of Gremlin-1 in LX-2 cells and primary hepatic stellate cells led to changes in BMP-related gene expression, which did not translate to increased fibrogenesis. Furthermore, we show that Gremlin-1 binds to heparin with high affinity, which prevents Gremlin-1 from entering systemic circulation, prohibiting Gremlin-1-mediated organ crosstalk. Overall, our findings suggest a redundant role for Gremlin-1 in the pathogenesis of liver fibrosis, which is unamenable to therapeutic targeting.

pathology↗

bioRxiv2023

Cystic fibrosis systemic immune profile is associated with lung microbes and characterized by widespread alterations in the innate and adaptive immune compartments

Polymicrobial airway infections and detrimental inflammation characterize patients with cystic fibrosis (CF), a disease with heterogeneous clinical outcomes. How the overall immune response is affected in CF, its relationships with the lung microbiome, and the source of clinical heterogeneity are unclear. Our work identifies a specific CF immune profile characterized by widespread hyperactivation, enrichment of CD35+/CD49d+ neutrophils, and reduction in dendritic cells. Further, our data indicate signs of immune dysregulation due to alterations in Tregs homeostasis, which, together with an impaired B-cell immune function, are linked with patients lung function and are potentially the source of clinical heterogeneity. Indeed, clinical heterogeneity does not stem from a specific lung microbiome; yet, commensal bacteria correlate with higher concentrations of circulating immune cells and lower expression of leukocyte activation markers, a condition reversed by pathogenic microorganisms. Overall, our findings provide unique markers and immunomodulatory targets for improving the treatment of CF.

immunology↗

bioRxiv2020

A simple, safe and sensitive method for SARS-CoV-2 inactivation and RNA extraction for RT-qPCR

The SARS-CoV-2 pandemic has created an urgent need for large amounts of diagnostic tests to detect viral RNA, which commercial suppliers are increasingly unable to deliver. In addition to the lack of availability, the current methods do not always fully inactivate the virus. Together, this calls for the development of safer methods for extraction and detection of viral RNA from patient samples that utilise readily available reagents and equipment present in most standard laboratories. We present a rapid and straightforward RNA extraction protocol for inactivating the SARS-CoV-2 virus that uses standard lab reagents. This protocol expands analysis capacity as the inactivated samples can be used in RT-qPCR detection tests at laboratories not otherwise classified for viral work. The method circumvents the need for commercial RNA purification kits, takes about 30 minutes from swab to PCR-ready viral RNA, and enables downstream detection of SARS-CoV-2 by RT-qPCR with very high sensitivity (~4 viral RNA copies per RT-qPCR). In summary, we present a rapid, safe and sensitive method for high-throughput detection of SARS-CoV-2, that can be conducted in any laboratory equipped with a qPCR machine.

microbiology↗