Engineering of pH-dependent antigen binding properties for toxin-targeting IgG1 antibodies using light-chain shuffling.

Immunoglobulin G (IgG) antibodies that bind their cognate antigen in a pH-dependent manner (acid-switched antibodies) can release their bound antigen for degradation in the acidic environment of endosomes, while the IgGs are rescued by the neonatal Fc receptor (FcRn). Thus, such IgGs can neutralize multiple antigens over time and therefore be used at lower doses than their non-pH-responsive counterparts. Here, we show that light-chain shuffling combined with phage display technology can be used to discover IgG1 antibodies with increased pH-dependent antigen binding properties, using the snake venom toxins, myotoxin II and α-cobratoxin, as examples. We reveal differences in how the selected IgG1s engage their antigens and human FcRn and show how these differences translate into distinct cellular handling properties related to their pH-dependent antigen binding phenotypes and Fc-engineering for improved FcRn binding. Our study showcases the complexity of engineering pH-dependent antigen binding IgG1s and demonstrates the effects on cellular antibody-antigen recycling.

A comparative study of protein structure prediction tools for challenging targets: Snake venom toxins.

Protein structure determination is a critical aspect of biological research, enabling us to understand protein function and potential applications. Recent advances in deep learning and artificial intelligence have led to the development of several protein structure prediction tools, such as AlphaFold2 and ColabFold. However, their performance has primarily been evaluated on well-characterised proteins and their ability to predict sturtctures of proteins lacking experimental structures, such as many snake venom toxins, has been less scrutinised. In this study, we evaluated three modelling tools on their prediction of over 1000 snake venom toxin structures for which no experimental structures exist. Our findings show that AlphaFold2 (AF2) performed the best across all assessed parameters. We also observed that ColabFold (CF) only scored slightly worse than AF2, while being computationally less intensive. All tools struggled with regions of intrinsic disorder, such as loops and propeptide regions, and performed well in predicting the structure of functional domains. Overall, our study highlights the importance of exercising caution when working with proteins with no experimental structures available, particularly those that are large and contain flexible regions. Nonetheless, leveraging computational structure prediction tools can provide valuable insights into the modelling of protein interactions with different targets and reveal potential binding sites, active sites, and conformational changes, as well as into the design of potential molecular binders for reagent, diagnostic, or therapeutic purposes.

Discovery and optimization of a broadly-neutralizing human monoclonal antibody against long-chain α-neurotoxins from snakes.

Snakebite envenoming continues to claim many lives across the globe, necessitating the development of improved therapies. To this end, broadly-neutralizing human monoclonal antibodies may possess advantages over current plasma-derived antivenoms by offering superior safety and high neutralization capacity. Here, we report the establishment of a pipeline based on phage display technology for the discovery and optimization of high affinity broadly-neutralizing human monoclonal antibodies. This approach yielded a recombinant human antibody with superior broadly-neutralizing capacities in vitro and in vivo against different long-chain α-neurotoxins from elapid snakes. This antibody prevents lethality induced by Naja kaouthia whole venom at an unprecedented low molar ratio of one antibody per toxin and prolongs the survival of mice injected with Dendroaspis polylepis or Ophiophagus hannah whole venoms.

Generation of Multivalent Nanobody-Based Proteins with Improved Neutralization of Long α-Neurotoxins from Elapid Snakes.

Recombinantly produced biotherapeutics hold promise for improving the current standard of care for snakebite envenoming over conventional serotherapy. Nanobodies have performed well in the clinic, and in the context of antivenom, they have shown the ability to neutralize long α-neurotoxins in vivo. Here, we showcase a protein engineering approach to increase the valence and hydrodynamic size of neutralizing nanobodies raised against a long α-neurotoxin (α-cobratoxin) from the venom of the monocled cobraNaja kaouthia. Based on the p53 tetramerization domain, a panel of anti-α-cobratoxin nanobody-p53 fusion proteins, termed Quads, were produced with different valences, inclusion or exclusion of Fc regions for endosomal recycling purposes, hydrodynamic sizes, and spatial arrangements, comprising up to 16 binding sites. Measurements of binding affinity and stoichiometry showed that the nanobody binding affinity was retained when incorporated into the Quad scaffold, and all nanobody domains were accessible for toxin binding, subsequently displaying increased blocking potency in vitro compared to the monomeric format. Moreover, functional assessment using automated patch-clamp assays demonstrated that the nanobody and Quads displayed neutralizing effects against long α-neurotoxins from both N. kaouthia and the forest cobra N. melanoleuca. This engineering approach offers a means of altering the valence, endosomal recyclability, and hydrodynamic size of existing nanobody-based therapeutics in a simple plug-and-play fashion and can thus serve as a technology for researchers tailoring therapeutic properties for improved neutralization of soluble targets such as snake toxins.

In vitro discovery of a human monoclonal antibody that neutralizes lethality of cobra snake venom.

The monocled cobra (Naja kaouthia) is among the most feared snakes in Southeast Asia due to its toxicity, which is predominantly derived from long-chain α-neurotoxins. The only specific treatment for snakebite envenoming is antivenom based on animal-derived polyclonal antibodies. Despite the lifesaving importance of these medicines, major limitations in safety, supply consistency, and efficacy create a need for improved treatments. Here, we describe the discovery and subsequent optimization of a recombinant human monoclonal immunoglobulin G antibody against α-cobratoxin using phage display technology. Affinity maturation by light chain-shuffling resulted in a significant increase in in vitro neutralization potency and in vivo efficacy. The optimized antibody prevented lethality when incubated with N. kaouthia whole venom prior to intravenous injection. This study is the first to demonstrate neutralization of whole snake venom by a single recombinant monoclonal antibody, thus providing a tantalizing prospect of bringing recombinant antivenoms based on human monoclonal or oligoclonal antibodies to the clinic.

Advances in antibody phage display technology.

Phage display technology can be used for the discovery of antibodies for research, diagnostic, and therapeutic purposes. In this review, we present and discuss key parameters that can be optimized when performing phage display selection campaigns, including the use of different antibody formats and advanced strategies for antigen presentation, such as immobilization, liposomes, nanodiscs, virus-like particles, and whole cells. Furthermore, we provide insights into selection strategies that can be used for the discovery of antibodies with complex binding requirements, such as targeting a specific epitope, cross-reactivity, or pH-dependent binding. Lastly, we provide a description of specialized phage display libraries for the discovery of bispecific antibodies and pH-sensitive antibodies. Together, these methods can be used to improve antibody discovery campaigns against all types of antigens.

The minimization of mechanical work in vibrated granular matter.

Experiments and computer simulations are carried out to investigate phase separation in a granular gas under vibration. The densities of the dilute and the dense phase are found to follow a lever rule and obey an equation of state. Here we show that the Maxwell equal-areas construction predicts the coexisting pressure and binodal densities remarkably well, even though the system is far from thermal equilibrium. This construction can be linked to the minimization of mechanical work associated with density fluctuations without invoking any concept related to equilibrium-like free energies.