De novo designed proteins neutralize lethal snake venom toxins.

Snakebite envenoming remains a devastating and neglected tropical disease, claiming over 100,000 lives annually and causing severe complications and long-lasting disabilities for many more1,2. Three-finger toxins (3FTx) are highly toxic components of elapid snake venoms that can cause diverse pathologies, including severe tissue damage3 and inhibition of nicotinic acetylcholine receptors (nAChRs) resulting in life-threatening neurotoxicity4. Currently, the only available treatments for snakebite consist of polyclonal antibodies derived from the plasma of immunized animals, which have high cost and limited efficacy against 3FTxs5,6,7. Here, we use deep learning methods to de novo design proteins to bind short- and long-chain α-neurotoxins and cytotoxins from the 3FTx family. With limited experimental screening, we obtain protein designs with remarkable thermal stability, high binding affinity, and near-atomic level agreement with the computational models. The designed proteins effectively neutralize all three 3FTx sub-families in vitro and protect mice from a lethal neurotoxin challenge. Such potent, stable, and readily manufacturable toxin-neutralizing proteins could provide the basis for safer, cost-effective, and widely accessible next-generation antivenom therapeutics. Beyond snakebite, our computational design methodology should help democratize therapeutic discovery, particularly in resource-limited settings, by substantially reducing costs and resource requirements for development of therapies to neglected tropical diseases.

Macromolecular Cargo Encapsulation via In Vitro Assembly of Two-Component Protein Nanoparticles.

Self-assembling protein nanoparticles are a promising class of materials for targeted drug delivery. Here, the use of a computationally designed, two-component, icosahedral protein nanoparticle is reported to encapsulate multiple macromolecular cargoes via simple and controlled self-assembly in vitro. Single-stranded RNA molecules between 200 and 2500 nucleotides in length are encapsulated and protected from enzymatic degradation for up to a month with length-dependent decay rates. Immunogenicity studies of nanoparticles packaging synthetic polymers carrying a small-molecule TLR7/8 agonist show that co-delivery of antigen and adjuvant results in a more than 20-fold increase in humoral immune responses while minimizing systemic cytokine secretion associated with free adjuvant. Coupled with the precise control over nanoparticle structure offered by computational design, robust and versatile encapsulation via in vitro assembly opens the door to a new generation of cargo-loaded protein nanoparticles that can combine the therapeutic effects of multiple drug classes.

Designed Endocytosis-Triggering Proteins mediate Targeted Degradation.

Endocytosis and lysosomal trafficking of cell surface receptors can be triggered by interaction with endogenous ligands. Therapeutic approaches such as LYTAC1,2 and KineTAC3, have taken advantage of this to target specific proteins for degradation by fusing modified native ligands to target binding proteins. While powerful, these approaches can be limited by possible competition with the endogenous ligand(s), the requirement in some cases for chemical modification that limits genetic encodability and can complicate manufacturing, and more generally, there may not be natural ligands which stimulate endocytosis through a given receptor. Here we describe general protein design approaches for designing endocytosis triggering binding proteins (EndoTags) that overcome these challenges. We present EndoTags for the IGF-2R, ASGPR, Sortillin, and Transferrin receptors, and show that fusing these tags to proteins which bind to soluble or transmembrane protein leads to lysosomal trafficking and target degradation; as these receptors have different tissue distributions, the different EndoTags could enable targeting of degradation to different tissues. The modularity and genetic encodability of EndoTags enables AND gate control for higher specificity targeted degradation, and the localized secretion of degraders from engineered cells. The tunability and modularity of our genetically encodable EndoTags should contribute to deciphering the relationship between receptor engagement and cellular trafficking, and they have considerable therapeutic potential as targeted degradation inducers, signaling activators for endocytosis-dependent pathways, and cellular uptake inducers for targeted antibody drug and RNA conjugates.

De novo design of protein structure and function with RFdiffusion.

There has been considerable recent progress in designing new proteins using deep-learning methods1-9. Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence-structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.

Mannose-binding lectin and complement mediate follicular localization and enhanced immunogenicity of diverse protein nanoparticle immunogens.

Nanoparticle (NP) vaccine formulations promote immune responses through multiple mechanisms. We recently reported that mannose-binding lectin (MBL) triggers trafficking of glycosylated HIV Env-immunogen NPs to lymph node follicles. Here, we investigate effects of MBL and complement on NP forms of HIV and other viral antigens. MBL recognition of oligomannose on gp120 nanoparticles significantly increases antigen accumulation in lymph nodes and antigen-specific germinal center (GC) responses. MBL and complement also mediate follicular trafficking and enhance GC responses to influenza, HBV, and HPV particulate antigens. Using model protein nanoparticles bearing titrated levels of glycosylation, we determine that mannose patches at a minimal density of 2.1 × 10-3 mannose patches/nm2 are required to trigger follicular targeting, which increases with increasing glycan density up to at least ∼8.2 × 10-3 patches/nm2. Thus, innate immune recognition of glycans has a significant impact on humoral immunity, and these findings provide a framework for engineering glycan recognition to optimize vaccine efficacy.