Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies.

Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.

De novo protein design-From new structures to programmable functions.

Methods from artificial intelligence (AI) trained on large datasets of sequences and structures can now "write" proteins with new shapes and molecular functions de novo, without starting from proteins found in nature. In this Perspective, I will discuss the state of the field of de novo protein design at the juncture of physics-based modeling approaches and AI. New protein folds and higher-order assemblies can be designed with considerable experimental success rates, and difficult problems requiring tunable control over protein conformations and precise shape complementarity for molecular recognition are coming into reach. Emerging approaches incorporate engineering principles-tunability, controllability, and modularity-into the design process from the beginning. Exciting frontiers lie in deconstructing cellular functions with de novo proteins and, conversely, constructing synthetic cellular signaling from the ground up. As methods improve, many more challenges are unsolved.

Structure-based design of non-hypertrophic apelin receptor modulator.

Apelin is a key hormone in cardiovascular homeostasis that activates the apelin receptor (APLNR), which is regarded as a promising therapeutic target for cardiovascular disease. However, adverse effects through the ß-arrestin pathway limit its pharmacological use. Here, we report cryoelectron microscopy (cryo-EM) structures of APLNR-Gi1 complexes bound to three agonists with divergent signaling profiles. Combined with functional assays, we have identified "twin hotspots" in APLNR as key determinants for signaling bias, guiding the rational design of two exclusive G-protein-biased agonists WN353 and WN561. Cryo-EM structures of WN353- and WN561-stimulated APLNR-G protein complexes further confirm that the designed ligands adopt the desired poses. Pathophysiological experiments have provided evidence that WN561 demonstrates superior therapeutic effects against cardiac hypertrophy and reduced adverse effects compared with the established APLNR agonists. In summary, our designed APLNR modulator may facilitate the development of next-generation cardiovascular medications.

Natural malaria infection elicits rare but potent neutralizing antibodies to the blood-stage antigen RH5.

Plasmodium falciparum reticulocyte-binding protein homolog 5 (RH5) is the most advanced blood-stage malaria vaccine candidate and is being evaluated for efficacy in endemic regions, emphasizing the need to study the underlying antibody response to RH5 during natural infection, which could augment or counteract responses to vaccination. Here, we found that RH5-reactive B cells were rare, and circulating immunoglobulin G (IgG) responses to RH5 were short-lived in malaria-exposed Malian individuals, despite repeated infections over multiple years. RH5-specific monoclonal antibodies isolated from eight malaria-exposed individuals mostly targeted non-neutralizing epitopes, in contrast to antibodies isolated from five RH5-vaccinated, malaria-naive UK individuals. However, MAD8-151 and MAD8-502, isolated from two malaria-exposed Malian individuals, were among the most potent neutralizers out of 186 antibodies from both cohorts and targeted the same epitopes as the most potent vaccine-induced antibodies. These results suggest that natural malaria infection may boost RH5-vaccine-induced responses and provide a clear strategy for the development of next-generation RH5 vaccines.

Preclinical proof of principle for orally delivered Th17 antagonist miniproteins.

Interleukin (IL)-23 and IL-17 are well-validated therapeutic targets in autoinflammatory diseases. Antibodies targeting IL-23 and IL-17 have shown clinical efficacy but are limited by high costs, safety risks, lack of sustained efficacy, and poor patient convenience as they require parenteral administration. Here, we present designed miniproteins inhibiting IL-23R and IL-17 with antibody-like, low picomolar affinities at a fraction of the molecular size. The minibinders potently block cell signaling in vitro and are extremely stable, enabling oral administration and low-cost manufacturing. The orally administered IL-23R minibinder shows efficacy better than a clinical anti-IL-23 antibody in mouse colitis and has a favorable pharmacokinetics (PK) and biodistribution profile in rats. This work demonstrates that orally administered de novo-designed minibinders can reach a therapeutic target past the gut epithelial barrier. With high potency, gut stability, and straightforward manufacturability, de novo-designed minibinders are a promising modality for oral biologics.

Structural mechanisms of α7 nicotinic receptor allosteric modulation and activation.

The α7 nicotinic acetylcholine receptor is a pentameric ligand-gated ion channel that plays an important role in cholinergic signaling throughout the nervous system. Its unique physiological characteristics and implications in neurological disorders and inflammation make it a promising but challenging therapeutic target. Positive allosteric modulators overcome limitations of traditional α7 agonists, but their potentiation mechanisms remain unclear. Here, we present high-resolution structures of α7-modulator complexes, revealing partially overlapping binding sites but varying conformational states. Structure-guided functional and computational tests suggest that differences in modulator activity arise from the stable rotation of a channel gating residue out of the pore. We extend the study using a time-resolved cryoelectron microscopy (cryo-EM) approach to reveal asymmetric state transitions for this homomeric channel and also find that a modulator with allosteric agonist activity exploits a distinct channel-gating mechanism. These results define mechanisms of α7 allosteric modulation and activation with implications across the pentameric receptor superfamily.

Conformational landscape of the type V-K CRISPR-associated transposon integration assembly.

CRISPR-associated transposons (CASTs) are mobile genetic elements that co-opt CRISPR-Cas systems for RNA-guided DNA transposition. CASTs integrate large DNA cargos into the attachment (att) site independently of homology-directed repair and thus hold promise for eukaryotic genome engineering. However, the functional diversity and complexity of CASTs hinder an understanding of their mechanisms. Here, we present the high-resolution cryoelectron microscopy (cryo-EM) structure of the reconstituted ∼1 MDa post-transposition complex of the type V-K CAST, together with different assembly intermediates and diverse TnsC filament lengths, thus enabling the recapitulation of the integration complex formation. The results of mutagenesis experiments probing the roles of specific residues and TnsB-binding sites show that transposition activity can be enhanced and suggest that the distance between the PAM and att sites is determined by the lengths of the TnsB C terminus and the TnsC filament. This singular model of RNA-guided transposition provides a foundation for repurposing the system for genome-editing applications.

Guidelines for organizing accessible and inclusive research retreats.

Research retreats are elements of scientific graduate training programs. Although expected to provide strong educational value, some students are reluctant to attend. Here, we identify participation barriers and provide guidelines for retreat design that minimize obstacles and establish an inclusive environment to improve attendance and enrichment for all attendees.

Unlocking translational machinery for antitubercular drug development.

Targeting translational factor proteins (TFPs) presents significant promise for the development of innovative antitubercular drugs. Previous insights from antibiotic binding mechanisms and recently solved 3D crystal structures of Mycobacterium tuberculosis (Mtb) elongation factor thermo unstable-GDP (EF-Tu-GDP), elongation factor thermo stable-EF-Tu (EF-Ts-EF-Tu), and elongation factor G-GDP (EF-G-GDP) have opened up new avenues for the design and development of potent antituberculosis (anti-TB) therapies.

KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies.

Both trio and population designs are popular study designs for identifying risk genetic variants in genome-wide association studies (GWASs). The trio design, as a family-based design, is robust to confounding due to population structure, whereas the population design is often more powerful due to larger sample sizes. Here, we propose KnockoffHybrid, a knockoff-based statistical method for hybrid analysis of both the trio and population designs. KnockoffHybrid provides a unified framework that brings together the advantages of both designs and produces powerful hybrid analysis while controlling the false discovery rate (FDR) in the presence of linkage disequilibrium and population structure. Furthermore, KnockoffHybrid has the flexibility to leverage different types of summary statistics for hybrid analyses, including expression quantitative trait loci (eQTL) and GWAS summary statistics. We demonstrate in simulations that KnockoffHybrid offers power gains over non-hybrid methods for the trio and population designs with the same number of cases while controlling the FDR with complex correlation among variants and population structure among subjects. In hybrid analyses of three trio cohorts for autism spectrum disorders (ASDs) from the Autism Speaks MSSNG, Autism Sequencing Consortium, and Autism Genome Project with GWAS summary statistics from the iPSYCH project and eQTL summary statistics from the MetaBrain project, KnockoffHybrid outperforms conventional methods by replicating several known risk genes for ASDs and identifying additional associations with variants in other genes, including the PRAME family genes involved in axon guidance and which may act as common targets for human speech/language evolution and related disorders.

Targeting neuraminidase: the next frontier for broadly protective influenza vaccines.

Current seasonal influenza vaccines, which mainly target hemagglutinin (HA), require annual updates due to the continuous antigenic drift of the influenza virus. Developing an influenza vaccine with increased breadth of protection will have significant public health benefits. The recent discovery of broadly protective antibodies to neuraminidase (NA) has provided important insights into developing a universal influenza vaccine, either by improving seasonal influenza vaccines or designing novel immunogens. However, further in-depth molecular characterizations of NA antibody responses are warranted to fully leverage broadly protective NA antibodies for influenza vaccine designs. Overall, we posit that focusing on NA for influenza vaccine development is synergistic with existing efforts targeting HA, and may represent a cost-effective approach to generating a broadly protective influenza vaccine.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN.

The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Context-dependent design of induced-fit enzymes using deep learning generates well-expressed, thermally stable and active enzymes.

The potential of engineered enzymes in industrial applications is often limited by their expression levels, thermal stability, and catalytic diversity. De novo enzyme design faces challenges due to the complexity of enzymatic catalysis. An alternative approach involves expanding natural enzyme capabilities for new substrates and parameters. Here, we introduce CoSaNN (Conformation Sampling using Neural Network), an enzyme design strategy using deep learning for structure prediction and sequence optimization. CoSaNN controls enzyme conformations to expand chemical space beyond simple mutagenesis. It employs a context-dependent approach for generating enzyme designs, considering non-linear relationships in sequence and structure space. We also developed SolvIT, a graph NN predicting protein solubility in Escherichia coli, optimizing enzyme expression selection from larger design sets. Using this method, we engineered enzymes with superior expression levels, with 54% expressed in E. coli, and increased thermal stability, with over 30% having higher Tm than the template, with no high-throughput screening. Our research underscores AI's transformative role in protein design, capturing high-order interactions and preserving allosteric mechanisms in extensively modified enzymes, and notably enhancing expression success rates. This method's ease of use and efficiency streamlines enzyme design, opening broad avenues for biotechnological applications and broadening field accessibility.

Understanding the ant's unique biting system can improve surgical needle holders.

Mechanical grasping and holding devices depend upon a firm and controlled grip. The possibility to improve this gripping performance is severely limited by the need for miniaturization in many applications, such as robotics, microassembly, or surgery. In this paper, we show how this gripping can be improved in one application (the endoscopic needle holder) by understanding and imitating the design principles that evolution has selected to make the mandibles of an ant a powerful natural gripping device. State-of-the-art kinematic, morphological, and engineering approaches show that the ant, in contrast to other insects, has considerable movement within the articulation and the jaw´s rotational axis. We derived three major evolutionary design principles from the ant's biting apparatus: 1) a mobile joint axis, 2) a tilted orientation of the mandibular axis, and 3) force transmission of the adductor muscle to the tip of the mandible. Application of these three principles to a commercially available endoscopic needle holder resulted in calculated force amplification up to 296% and an experimentally measured one up to 433%. This reduced the amount of translations and rotations of the needle, compared to the needle's original design, while retaining its size or outer shape. This study serves as just one example showing how bioengineers might find elegant solutions to their design problems by closely observing the natural world.

The potential importance of the built-environment microbiome and its impact on human health.

There is increasing evidence that interactions between microbes and their hosts not only play a role in determining health and disease but also in emotions, thought, and behavior. Built environments greatly influence microbiome exposures because of their built-in highly specific microbiomes coproduced with myriad metaorganisms including humans, pets, plants, rodents, and insects. Seemingly static built structures host complex ecologies of microorganisms that are only starting to be mapped. These microbial ecologies of built environments are directly and interdependently affected by social, spatial, and technological norms. Advances in technology have made these organisms visible and forced the scientific community and architects to rethink gene-environment and microbe interactions respectively. Thus, built environment design must consider the microbiome, and research involving host-microbiome interaction must consider the built-environment. This paradigm shift becomes increasingly important as evidence grows that contemporary built environments are steadily reducing the microbial diversity essential for human health, well-being, and resilience while accelerating the symptoms of human chronic diseases including environmental allergies, and other more life-altering diseases. New models of design are required to balance maximizing exposure to microbial diversity while minimizing exposure to human-associated diseases. Sustained trans-disciplinary research across time (evolutionary, historical, and generational) and space (cultural and geographical) is needed to develop experimental design protocols that address multigenerational multispecies health and health equity in built environments.

Structure and design of Langya virus glycoprotein antigens.

Langya virus (LayV) is a recently discovered henipavirus (HNV), isolated from febrile patients in China. HNV entry into host cells is mediated by the attachment (G) and fusion (F) glycoproteins which are the main targets of neutralizing antibodies. We show here that the LayV F and G glycoproteins promote membrane fusion with human, mouse, and hamster target cells using a different, yet unknown, receptor than Nipah virus (NiV) and Hendra virus (HeV) and that NiV- and HeV-elicited monoclonal and polyclonal antibodies do not cross-react with LayV F and G. We determined cryoelectron microscopy structures of LayV F, in the prefusion and postfusion states, and of LayV G, revealing their conformational landscape and distinct antigenicity relative to NiV and HeV. We computationally designed stabilized LayV G constructs and demonstrate the generalizability of an HNV F prefusion-stabilization strategy. Our data will support the development of vaccines and therapeutics against LayV and closely related HNVs.

Antibiotic class with potent in vivo activity targeting lipopolysaccharide synthesis in Gram-negative bacteria.

Here, we describe the identification of an antibiotic class acting via LpxH, a clinically unexploited target in lipopolysaccharide synthesis. The lipopolysaccharide synthesis pathway is essential in most Gram-negative bacteria and there is no analogous pathway in humans. Based on a series of phenotypic screens, we identified a hit targeting this pathway that had activity on efflux-defective strains of Escherichia coli. We recognized common structural elements between this hit and a previously published inhibitor, also with activity against efflux-deficient bacteria. With the help of X-ray structures, this information was used to design inhibitors with activity on efflux-proficient, wild-type strains. Optimization of properties such as solubility, metabolic stability and serum protein binding resulted in compounds having potent in vivo efficacy against bloodstream infections caused by the critical Gram-negative pathogens E. coli and Klebsiella pneumoniae. Other favorable properties of the series include a lack of pre-existing resistance in clinical isolates, and no loss of activity against strains expressing extended-spectrum-ß-lactamase, metallo-ß-lactamase, or carbapenemase-resistance genes. Further development of this class of antibiotics could make an important contribution to the ongoing struggle against antibiotic resistance.

Design of universal Ebola virus vaccine candidates via immunofocusing.

The Ebola virus causes hemorrhagic fever in humans and poses a significant threat to global public health. Although two viral vector vaccines have been approved to prevent Ebola virus disease, they are distributed in the limited ring vaccination setting and only indicated for prevention of infection from orthoebolavirus zairense (EBOV)-one of three orthoebolavirus species that have caused previous outbreaks. Ebola virus glycoprotein GP mediates viral infection and serves as the primary target of neutralizing antibodies. Here, we describe a universal Ebola virus vaccine approach using a structure-guided design of candidates with hyperglycosylation that aims to direct antibody responses away from variable regions and toward conserved epitopes of GP. We first determined the hyperglycosylation landscape on Ebola virus GP and used that to generate hyperglycosylated GP variants with two to four additional glycosylation sites to mask the highly variable glycan cap region. We then created vaccine candidates by displaying wild-type or hyperglycosylated GP variants on ferritin nanoparticles (Fer). Immunization with these antigens elicited potent neutralizing antisera against EBOV in mice. Importantly, we observed consistent cross-neutralizing activity against Bundibugyo virus and Sudan virus from hyperglycosylated GP-Fer with two or three additional glycans. In comparison, elicitation of cross-neutralizing antisera was rare in mice immunized with wild-type GP-Fer. These results demonstrate a potential strategy to develop universal Ebola virus vaccines that confer cross-protective immunity against existing and emerging filovirus species.

Causally estimating the effect of YouTube's recommender system using counterfactual bots.

In recent years, critics of online platforms have raised concerns about the ability of recommendation algorithms to amplify problematic content, with potentially radicalizing consequences. However, attempts to evaluate the effect of recommenders have suffered from a lack of appropriate counterfactuals-what a user would have viewed in the absence of algorithmic recommendations-and hence cannot disentangle the effects of the algorithm from a user's intentions. Here we propose a method that we call "counterfactual bots" to causally estimate the role of algorithmic recommendations on the consumption of highly partisan content on YouTube. By comparing bots that replicate real users' consumption patterns with "counterfactual" bots that follow rule-based trajectories, we show that, on average, relying exclusively on the YouTube recommender results in less partisan consumption, where the effect is most pronounced for heavy partisan consumers. Following a similar method, we also show that if partisan consumers switch to moderate content, YouTube's sidebar recommender "forgets" their partisan preference within roughly 30 videos regardless of their prior history, while homepage recommendations shift more gradually toward moderate content. Overall, our findings indicate that, at least since the algorithm changes that YouTube implemented in 2019, individual consumption patterns mostly reflect individual preferences, where algorithmic recommendations play, if anything, a moderating role.

De novo design of modular protein hydrogels with programmable intra- and extracellular viscoelasticity.

Relating the macroscopic properties of protein-based materials to their underlying component microstructure is an outstanding challenge. Here, we exploit computational design to specify the size, flexibility, and valency of de novo protein building blocks, as well as the interaction dynamics between them, to investigate how molecular parameters govern the macroscopic viscoelasticity of the resultant protein hydrogels. We construct gel systems from pairs of symmetric protein homo-oligomers, each comprising 2, 5, 24, or 120 individual protein components, that are crosslinked either physically or covalently into idealized step-growth biopolymer networks. Through rheological assessment, we find that the covalent linkage of multifunctional precursors yields hydrogels whose viscoelasticity depends on the crosslink length between the constituent building blocks. In contrast, reversibly crosslinking the homo-oligomeric components with a computationally designed heterodimer results in viscoelastic biomaterials exhibiting fluid-like properties under rest and low shear, but solid-like behavior at higher frequencies. Exploiting the unique genetic encodability of these materials, we demonstrate the assembly of protein networks within living mammalian cells and show via fluorescence recovery after photobleaching (FRAP) that mechanical properties can be tuned intracellularly in a manner similar to formulations formed extracellularly. We anticipate that the ability to modularly construct and systematically program the viscoelastic properties of designer protein-based materials could have broad utility in biomedicine, with applications in tissue engineering, therapeutic delivery, and synthetic biology.