Biology subjects

Borst, A. J.

Publications and source records attributed to Borst, A. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Discovering and designing multistate protein assemblies

Evolved protein assemblies exploit multiple weak interfaces to package cargo, facilitate metabolism, and direct cell movement, often through architectures that depart from strict geometric symmetry. Designed protein assemblies can also break symmetry through conformational flexibility or strain-based defects, but have generally lacked the capacity for large-scale structural rearrangements characteristic of evolved systems. Here, we characterize the structures and biophysical properties of emergent protein assemblies and establish a strategy for designing quasisymmetric materials that switch between assembly states. Rather than relying on intrinsic flexibility, our approach programs multiple self-assembling interfaces onto rigid oligomers. Using multistate design and ensemble predictions, we generate assemblies in which protomers can adopt alternative designed interface modes, enabling identical amino acid sequences to form distinct configurations depending on assembly pathway and environmental conditions. As a proof of principle, we construct quasisymmetric capsids that transition into micron-scale 2D arrays in response to temperature. This work establishes a strategy for encoding alternative assembly geometries within a single protein sequence and provides a foundation for engineering materials with environmentally tunable properties.

biochemistry↗

bioRxiv2026

Distinct mechanisms of neutralization by antibodies targeting a conserved pneumovirus F epitope

Pneumoviruses cause seasonal outbreaks leading to hospitalizations of vulnerable populations such as infants and the elderly. Cross-neutralizing antibodies targeting viral fusion have been isolated from infected individuals, but their elicitation and mechanisms of action remain understudied. Here, we describe two vaccine-elicited antibody classes, LOR24 and LOR69, that bind an overlapping epitope, and identify the somatic mutations that endow their breadth and potency, respectively. Cryo-electron microscopy structures of both antibodies bound to the HRSV fusion (F) protein show binding modes distinct from each other and from the previously described cross-neutralizing antibody MPE8, yet they all use similar motifs for binding. Complementary in vitro and electron microscopy experiments show that these antibodies either lock prefusion F as a trimer, arrest F in a monomeric or intermediate state, or promote the transition to the postfusion conformation. This work sheds light on mechanisms of pneumovirus neutralization and the elicitation of cross-neutralizing antibody responses.

immunology↗

bioRxiv2026

Programmable De Novo Design of Mesoporous Protein Crystal Frameworks

Three-dimensional protein crystals are ordered, porous macroscopic materials with potential applications in catalysis, biosensing, and biomedicine. However, most protein crystals are obtained by empirical screening, providing limited control over the lattice architecture, pore geometry or component composition that determine material function. Here, we present a modular strategy for the programmable design of highly porous, framework-like protein crystals using predefined protein-protein interactions. This strategy yielded over 30 distinct protein crystals, including single-component and multicomponent P213 and I213 lattices that grow to over 100 micrometers in size. Small-angle X-ray scattering and electron microscopy showed close agreement between experimental lattices and computational models. RFdiffusion-guided design generated isomorphous variants with matched lattice parameters, enabling coherent protein crystal alloys, epitaxial core-shell growth and reversible shell assembly. The designed crystals exhibit tunable mesoporous architectures, with limiting apertures of 2-18 nm, and support genetically encoded incorporation of fluorescent protein guests. These results establish a general route to programmable lattice engineering of protein crystals and position them as genetically encoded, compositionally tunable mesoporous materials.

synthetic biology↗

bioRxiv2026

Controlling metal-carbonate phase, form, and function through de novo protein design

Biomineralization enables living systems to construct hybrid materials by controlling the location, orientation, and polymorph of inorganic crystals with proteins and other biomolecules. Despite decades of study, the molecular principles underlying these processes remain difficult to harness in engineered materials, in part because native biomineralization proteins are often intrinsically disordered, heterogeneous, or insoluble. Here we show that de novo designed protein interfaces can be assembled into reconfigurable two-dimensional arrays which template calcite nanocrystals. By fine-tuning RFdiffusion2 on repeat protein scaffolds, we further enable the design of protein architectures which selectively form aragonite, a metastable polymorph of calcium carbonate, in nucleation conditions that otherwise result in a mixture of phases. Extending beyond inorganics found in biological systems, we show that lattice-matched protein designs template cobalt carbonate formation: a flat helical repeat protein interface promotes unconfined growth, whereas soluble D3 cage assemblies yield more homogenous cobalt carbonate nanocrystals confined to the interior of the cage. These protein-cage cobalt carbonate hybrid materials function as electrocatalysts for alkaline water splitting. Our results demonstrate the potential of deep learning-based methods to unlock the structural and functional activity of protein-mineral composites.

biochemistry↗

bioRxiv2026

Templating and confining calcium phosphate mineralization within designed protein assemblies

Bone formation involves the deposition of ordered hydroxyapatite (HAp) on collagen fibrils, but the underlying molecular mechanisms remain largely unresolved, limiting the design of protein-apatite hybrid materials. Here we show that computationally designed de novo proteins can template and confine HAp mineralization. We design C3-symmetric oligomers with inner surfaces chemically complementary to the HAp {010} facet, and assemble these through additional interfaces into D3 oligomers, one-dimensional nanotubes, and two-dimensional arrays. Electron microscopy revealed templated mineralization and confinement at each hierarchical level, with mineral shape guided by the underlying protein architecture. Conversion of an initially formed amorphous phase to HAp is driven by the designed protein-mineral interface. Our results establish a framework for programmable protein-guided mineralization, providing a foundation for next-generation hybrid materials.

biochemistry↗

bioRxiv2025

De novo design of protein nanoparticles with integrated functional motifs

Computational design of self-assembling proteins has long relied on pre-existing structures and sequences, fundamentally limiting control over their structural and functional properties. Recent machine learning-based methods have transformed our ability to design functional small de novo proteins and oligomers, yet methods to design large de novo protein assemblies with structures tailored to specific applications are still underexplored. Here, we develop a generalizable method for designing de novo symmetric protein complexes that incorporate target functional motifs into their structures. We report 34 new protein nanoparticles that form on-target assemblies with cubic point group symmetries. The nanoparticles exhibit a wide variety of backbones that were designed with atom-level accuracy, as evidenced by several cryo-EM and crystal structures that reveal minimal deviations from the design models. We use the method to generate a de novo antigen-tailored nanoparticle vaccine that elicits robust immune responses in mice. These results establish a generalizable approach that can be used to design functional self-assembling protein complexes with structures tailored to specific applications.

biochemistry↗

bioRxiv2025

De novo design of RNA and nucleoprotein complexes

Nucleic acids fold into sequence-dependent tertiary structures and carry out diverse biological functions, much like proteins. However, while considerable advances have been made in the de novo design of protein structure and function, the same has not yet been achieved for RNA tertiary structures of similar intricacy. Here, we describe a generative diffusion framework, RFDpoly, for generalized de novo biopolymer (RNA, DNA and protein) design, and use it to create diverse and designable RNA structures. We design RNA structures with novel folds and experimentally validate them using a combination of chemical footprinting (SHAPE-seq) and electron microscopy. We further use this approach to design protein-nucleic acid assemblies; the crystal structure of one such design is nearly identical to the design model. This work demonstrates that the principles of structure-based de novo protein design can be extended to nucleic acids, opening the door to creating a wide range of new RNA structures and protein-nucleic acid complexes.

biochemistry↗

bioRxiv2025

Solubilization of Membrane Proteins using designed protein WRAPS

The development of therapies and vaccines targeting integral membrane proteins has been complicated by their extensive hydrophobic surfaces, which can make production and structural characterization difficult. Here we describe a general deep learning-based design approach for solubilizing native membrane proteins while preserving their sequence, fold, and function using genetically encoded de novo protein WRAPs (Water-soluble RFdiffused Amphipathic Proteins) that surround the lipid-interacting hydrophobic surfaces, rendering them stable and water-soluble without the need for detergents. We design WRAPs for both beta-barrel outer membrane and helical multi-pass transmembrane proteins, and show that the solubilized proteins retain the binding and enzymatic functions of the native targets with enhanced stability. Syphilis vaccine development has been hindered by difficulties in characterizing and producing the outer membrane protein antigens; we generated soluble versions of four Treponema pallidum outer membrane beta barrels which are potential syphilis vaccine antigens. A 4.0 [A] cryo-EM map of WRAPed TP0698 is closely consistent with the design model. WRAPs should be broadly useful for facilitating biochemical and structural characterization of integral membrane proteins, enabling therapeutic discovery by screening against purified soluble targets, and generating antigenically intact immunogens for vaccine development.

biochemistry↗

bioRxiv2025

A Multivalent Pan-Ebolavirus Nanoparticle Vaccine Provides Protection in Rodents from Lethal Infection by Adapted Zaire and Sudan Viruses

Both Zaire ebolavirus (EBOV) and Sudan ebolavirus (SUDV) are members of the family Filoviridae, first discovered in 1976 during outbreaks of hemorrhagic fever in northern Zaire and southern Sudan. Ebola virus disease outbreaks are major public health events because of their potential for human-to-human transmission with high case fatality rates. Filoviral surface glycoproteins (GPs) are known to be the primary targets of neutralizing antibodies for protection from disease, and are the relevant immunogens in the two approved EBOV vaccines. Here we describe the design, electron microscopy-based structural characterization, and efficacy testing of a series of icosahedral I53-50 nanoparticles displaying prefusion trimeric EBOV and SUDV GP antigens. Mice and guinea pigs vaccinated with either a cocktail of EBOV-GP-I53-50 plus SUDV-GP-I53-50 or mosaic EBOV / SUDV-GP-I53-50 nanoparticles were protected from death or severe clinical signs of disease and weight loss, respectively, when challenged with either mouse-adapted EBOV or guinea pig-adapted SUDV.

immunology↗

bioRxiv2024

Bottom-up design of calcium channels from defined selectivity filter geometry

Native ion channels play key roles in biological systems, and engineered versions are widely used as chemogenetic tools and in sensing devices1,2. Protein design has been harnessed to generate pore-containing transmembrane proteins, but the capability to design ion selectivity based on the interactions between ions and selectivity filter residues, a crucial feature of native ion channels3, has been constrained by the lack of methods to place the metal-coordinating residues with atomic-level precision. Here we describe a bottom-up RFdiffusion-based approach to construct Ca2+ channels from defined selectivity filter residue geometries, and use this approach to design symmetric oligomeric channels with Ca2+ selectivity filters having different coordination numbers and different geometries at the entrance of a wide pore buttressed by multiple transmembrane helices. The designed channel proteins assemble into homogenous pore-containing particles, and for both tetrameric and hexameric ion-coordinating configurations, patch-clamp experiments show that the designed channels have higher conductances for Ca2+ than for Na+ and other divalent ions (Sr2+ and Mg2+). Cryo-electron microscopy indicates that the design method has high accuracy: the structure of the hexameric Ca2+ channel is nearly identical to the design model. Our bottom-up design approach now enables the testing of hypotheses relating filter geometry to ion selectivity by direct construction, and provides a roadmap for creating selective ion channels for a wide range of applications.

biochemistry↗

bioRxiv2024

Structural Convergence and Water-Mediated Substrate Mimicry Enable Broad Neuraminidase Inhibition by Human Antibodies

Influenza has been responsible for multiple global pandemics and seasonal epidemics and claimed millions of lives. The imminent threat of a panzootic outbreak of avian influenza H5N1 virus underscores the urgent need for pandemic preparedness and effective countermeasures, including monoclonal antibodies (mAbs). Here, we characterize human mAbs that target the highly conserved catalytic site of viral neuraminidase (NA), termed NCS mAbs, and the molecular basis of their broad specificity. Cross-reactive NA-specific B cells were isolated by using stabilized NA probes of non-circulating subtypes. We found that NCS mAbs recognized multiple NAs of influenza A as well as influenza B NAs and conferred prophylactic protections in mice against H1N1, H5N1, and influenza B viruses. Cryo-electron microscopy structures of two NCS mAbs revealed that they rely on structural mimicry of sialic acid, the substrate of NA, by coordinating not only amino acid side chains but also water molecules, enabling inhibition of NA activity across multiple influenza A and B viruses, including avian influenza H5N1 clade 2.3.4.4b viruses. Our results provide a molecular basis for the broad reactivity and inhibitory activity of NCS mAbs targeting the catalytic site of NA through substrate mimicry.

immunology↗

bioRxiv2024

Computational design of bifaceted protein nanomaterials with tailorable properties

Recent advances in computational methods have led to considerable progress in the design of self-assembling protein nanoparticles. However, nearly all nanoparticles designed to date exhibit strict point group symmetry, with each subunit occupying an identical, symmetrically related environment. This limits the structural diversity that can be achieved and precludes anisotropic functionalization. Here, we describe a general computational strategy for designing multi-component bifaceted protein nanomaterials with two distinctly addressable sides. The method centers on docking pseudosymmetric heterooligomeric building blocks in architectures with dihedral symmetry and designing an asymmetric protein-protein interface between them. We used this approach to obtain an initial 30-subunit assembly with pseudo-D5 symmetry, and then generated an additional 15 variants in which we controllably altered the size and morphology of the bifaceted nanoparticles by designing de novo extensions to one of the subunits. Functionalization of the two distinct faces of the nanoparticles with de novo protein minibinders enabled specific colocalization of two populations of polystyrene microparticles coated with target protein receptors. The ability to accurately design anisotropic protein nanomaterials with precisely tunable structures and functions could be broadly useful in applications that require colocalizing two or more distinct target moieties.

bioengineering↗

bioRxiv2024

Computational redesign of TALE proteins for DNA-templated assembly of protein fibers

Many viral proteins self-assemble into capsid structures, often using their genetic material as a template for assembly. To date, de novo designed capsid-like proteins do not require genetic material as a template for assembly, which can be both an advantage and a disadvantage depending on the use case. Templates are indispensable, for example, in the assembly of linear structures with well-defined lengths. As a first step towards fully de novo designed templated assembly, here we redesign proteins from the Transcription activator-like effector (TALE) family of transcriptional regulators to polymerize on double-stranded DNA (dsDNA) templates. Starting from natural TALE protein sequences, we created idealized repeat proteins with sequence-independent DNA binding properties that cooperatively self-assemble to form linear protein-DNA complexes with template-controlled lengths. We used high-resolution atomic force microscopy (AFM) and cryo electron microscopy (cryo-EM) to characterize the three-dimensional structures of the DNA-protein hybrid complexes. In these structures, a protein filament helically wraps around the dsDNA using a binding mode similar to that of natural TALE proteins. As an example application of these materials, we show the system can be used for repetitive peptide antigen display at precisely controlled repeat distances, and that such immunogens elicit robust antigen-specific antibodies in mice.

biochemistry↗

bioRxiv2024

Bond-centric modular design of protein assemblies

We describe a modular bond-centric approach to protein nanomaterial design inspired by the rich diversity of chemical structures that can be generated from the small number of atomic valencies and bonding interactions. We design protein building blocks with regular coordination geometries and bonding interactions that enable the assembly of a wide variety of closed and opened nanomaterials using simple geometrical principles. Experimental characterization confirms successful formation of more than twenty multi-component polyhedral protein cages, 2D arrays, and 3D protein lattices, with a high (10-50 %) success rate and electron microscopy data closely matching the corresponding design models. Because of the modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable systems.

biochemistry↗

bioRxiv2024

Protein identification using cryo-EM and artificial intelligence guides improved sample purification

Protein purification is essential in protein biochemistry, structural biology, and protein design. It enables the determination of protein structures, the study of biological mechanisms, and the biochemical and biophysical characterization of both natural and de novo designed proteins. Despite the broad application of various protein purification protocols, standard strategies can still encounter challenges, such as the unintended co-purification of unknown contaminants alongside the target protein. In particular, co-purification issues pose significant challenges for designed self-assembling protein nanomaterials, as it is difficult to determine whether unexpected observed geometries represent novel assembly states of the designed system, cross-contamination from other assemblies, or native proteins originating from the expression host. In this study, we assessed the ability of an automated structure-to-sequence pipeline to unambiguously identify an unknown co-purifying protein found across several purified designed protein samples. Using cryo-electron microscopy (Cryo-EM), ModelAngelos sequence-agnostic automated model-building feature, and the Basic Local Alignment Search Tool (BLAST), we identified the unknown protein as dihydrolipoamide succinyltransferase (DLST). This identification was further confirmed by comparing the cryo-EM data with available DLST structures in the Protein Data Bank (PDB) and AlphaFold 3 predictions from the top BLAST hits. The clear identification of DLST informed our subsequent literature search and led to the rational modification of our protein purification protocol, ultimately enabling the exclusion of the contaminant from preparations of our target nanoparticle. This study demonstrates the successful application of a structure-to-sequence workflow, integrating Cryo-EM, ModelAngelo, protein BLAST, PDB structures, and AlphaFold 3 predictions, to identify and remove an unknown protein from a purified sample. It also highlights the broader potential of integrating Cryo-EM with AI-driven tools for accurate protein identification across various samples and contexts within protein science. HighlightsO_LIAn unknown protein was consistently found in multiple de novo designed protein samples. C_LIO_LIThe protein was identified as dihydrolipoamide succinyltransferase (DLST) using Cryo-EM, ModelAngelo and BLAST, and further verified using AlphaFold 3 and the PDB. C_LIO_LIIdentification enabled rational modification of the purification protocol to exclude the contaminant. C_LIO_LIThis method enables accurate protein identification without requiring near-atomic resolution or prior sequence and structural data, making it broadly applicable to various areas of protein science. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/612515v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@592410org.highwire.dtl.DTLVardef@4ea3f3org.highwire.dtl.DTLVardef@edd0bcorg.highwire.dtl.DTLVardef@122fba2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

De novo design of potent inhibitors of Clostridioides difficile toxin B

Clostridioides difficile is a major cause of secondary disease in hospitals. During infection, C. difficile toxin B drives disease pathology. Here we use deep learning and Rosetta-based approaches to de novo design small proteins that block the entry of TcdB into cells. These molecules have binding affinities and neutralization IC50s in the pM range and are compelling candidates for further clinical development. By directly targeting the toxin rather than the pathogen, these molecules have the advantage of immediate cessation of disease and lower selective pressure for escape compared to conventional antibiotics. As C. difficile infects the colon, the protease and pH resistance of the designed proteins opens the door to oral delivery of engineered biologics. Significance statementC. difficile infection (CDI) is a major public health concern with over half a million cases in the United States annually resulting in 30,000 deaths. Current therapies are inadequate and frequently result in cycles of recurrent infection (rCDI). Progress has been made in the development of anti-toxin mAb therapies that can reduce the rate of rCDI, but these remain unaffordable and out of reach for many patients. Using de novo protein design, we developed small protein inhibitors targeting two independent receptor binding sites on the toxin that drives pathology during CDI. These molecules are high affinity, potently neutralizing and stable in simulated intestinal fluid, making them strong candidates for the clinical development of new CDI therapies.

microbiology↗

bioRxiv2024

Atomically accurate de novo design of single-domain antibodies

Despite the central role that antibodies play in modern medicine, there is currently no method to design novel antibodies that bind a specific epitope entirely in silico. Instead, antibody discovery currently relies on animal immunization or random library screening approaches. Here, we demonstrate that combining computational protein design using a fine-tuned RFdiffusion network alongside yeast display screening enables the generation of antibody variable heavy chains (VHHs) and single chain variable fragments (scFvs) that bind user-specified epitopes with atomic-level precision. To verify this, we experimentally characterized VHH binders to four disease-relevant epitopes using multiple orthogonal biophysical methods, including cryo-EM, which confirmed the proper Ig fold and binding pose of designed VHHs targeting influenza hemagglutinin and Clostridium difficile toxin B (TcdB). For the influenza-targeting VHH, high-resolution structural data further confirmed the accuracy of CDR loop conformations. While initial computational designs exhibit modest affinity, affinity maturation using OrthoRep enables production of single-digit nanomolar binders that maintain the intended epitope selectivity. We further demonstrate the de novo design of single-chain variable fragments (scFvs), creating binders to TcdB and a Phox2b peptide-MHC complex by combining designed heavy and light chain CDRs. Cryo-EM structural data confirmed the proper Ig fold and binding pose for two distinct TcdB scFvs, with high-resolution data for one design additionally verifying the atomically accurate conformations of all six CDR loops. Our approach establishes a framework for the rational computational design, screening, isolation, and characterization of fully de novo antibodies with atomic-level precision in both structure and epitope targeting.

bioengineering↗

bioRxiv2023

De novo design of allosterically switchable protein assemblies

Allosteric modulation of protein function, wherein the binding of an effector to a protein triggers conformational changes at distant functional sites, plays a central role in the control of metabolism and cell signaling1-3. There has been considerable interest in designing allosteric systems, both to gain insight into the mechanisms underlying such "action at a distance" modulation and to create synthetic proteins whose functions can be regulated by effectors4-7. However, emulating the subtle conformational changes distributed across many residues, characteristic of natural allosteric proteins, is a significant challenge8,9. Here, inspired by the classic Monod-Changeux-Wyman model of cooperativity10, we investigate the de novo design of allostery through rigid-body coupling of designed effector-switchable hinge modules11 to protein interfaces12 that direct the formation of alternative oligomeric states. We find that this approach can be used to generate a wide variety of allosterically switchable systems, including cyclic rings that incorporate or eject subunits in response to effector binding and dihedral cages that undergo effector-induced disassembly. Size-exclusion chromatography, mass photometry13, and electron microscopy reveal that these designed allosteric protein assemblies closely resemble the design models in both the presence and absence of effectors and can have ligand-binding cooperativity comparable to classic natural systems such as hemoglobin14. Our results indicate that allostery can arise from global coupling of the energetics of protein substructures without optimized sidechain-sidechain allosteric communication pathways and provide a roadmap for generating allosterically triggerable delivery systems, protein nanomachines, and cellular feedback control circuitry.

biochemistry↗