Biology subjects

Ahlrichs, M.

Publications and source records attributed to Ahlrichs, M..

7 recordsLinked to original sources

bioRxiv2023

Designed Endocytosis-Triggering Proteins mediate Targeted Degradation and amplify signaling

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.

synthetic biology↗

bioRxiv2023

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 and molecular dynamics (MD) simulation, 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 non-Newtonian biomaterials exhibiting fluid-like properties under rest and low shear, but shear-stiffening 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 correlation with matching 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. SignificanceProtein-based hydrogels have many applications in cellular engineering and medicine. Most genetically encodable protein hydrogels are made from naturally harvested proteins or protein-polymer hybrid constructs. Here we describe de novo protein hydrogels and systematically investigate the impact of microscopic properties of the building blocks (e.g., supramolecular interaction, valencies, geometries, flexibility) on the resultant macroscopic gel mechanics, both intra-and extracellularly. These de novo supramolecular protein assemblies, whose properties can be tuned from solid gels to non-Newtonian fluids, provide expanded opportunities for applications in synthetic biology and medicine.

bioengineering↗

bioRxiv2023

Computational design of non-porous, pH-responsive antibody nanoparticles

Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and important for targeted delivery of biologics. We describe the design of octahedral non-porous nanoparticles with the three symmetry axes (four-fold, three-fold, and two-fold) occupied by three distinct protein homooligomers: a de novo designed tetramer, an antibody of interest, and a designed trimer programmed to disassemble below a tunable pH transition point. The nanoparticles assemble cooperatively from independently purified components, and a cryo-EM density map reveals that the structure is very close to the computational design model. The designed nanoparticles can package a variety of molecular payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between to 5.9-6.7. To our knowledge, these are the first designed nanoparticles with more than two structural components and with finely tunable environmental sensitivity, and they provide new routes to antibody-directed targeted delivery.

bioengineering↗

bioRxiv2023

Design of amyloidogenic peptide traps

Segments of proteins with {beta}-strand propensity can self associate to form amyloid fibrils associated with many diseases. These regions often adopt alternative structures in their folded states, or are intrinsically disordered in solution, making it difficult to generate binders or inhibitors with existing strategies. Here we describe a general approach to bind such segments in {beta}-strand and {beta}-hairpin conformations using de novo designed scaffolds that contain deep peptide binding clefts flanked by {beta}-strands that form hydrogen bonds to the peptide upon binding. The designs bind their cognate peptides in vitro with nanomolar affinities and in mammalian cells. The crystal structure of a designed protein-peptide complex is close to the design model, and NMR characterization reveals how the peptide binding cleft is protected in the apo state. We use the approach to design binders to segments of the amyloid forming proteins Transthyretin, Tau, Serum amyloid A1 and A{beta}42. The A{beta} binders block assembly of A{beta} fibrils as effectively as the most potent of the clinically tested antibodies to date.

synthetic biology↗

bioRxiv2022

Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains

Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. Retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the novel nanoparticles we describe may be broadly useful in biotechnological applications.

biochemistry↗

bioRxiv2021

Molecular basis of immune evasion by the delta and kappa SARS-CoV-2 variants

Worldwide SARS-CoV-2 transmission leads to the recurrent emergence of variants, such as the recently described B.1.617.1 (kappa), B.1.617.2 (delta) and B.1.617.2+ (delta+). The B.1.617.2 (delta) variant of concern is causing a new wave of infections in many countries, mostly affecting unvaccinated individuals, and has become globally dominant. We show that these variants dampen the in vitro potency of vaccine-elicited serum neutralizing antibodies and provide a structural framework for describing the impact of individual mutations on immune evasion. Mutations in the B.1.617.1 (kappa) and B.1.617.2 (delta) spike glycoproteins abrogate recognition by several monoclonal antibodies via alteration of key antigenic sites, including an unexpected remodeling of the B.1.617.2 (delta) N-terminal domain. The binding affinity of the B.1.617.1 (kappa) and B.1.617.2 (delta) receptor-binding domain for ACE2 is comparable to the ancestral virus whereas B.1.617.2+ (delta+) exhibits markedly reduced affinity. We describe a previously uncharacterized class of N-terminal domain-directed human neutralizing monoclonal antibodies cross-reacting with several variants of concern, revealing a possible target for vaccine development.

immunology↗

bioRxiv2021

Stabilization of the SARS-CoV-2 Spike receptor-binding domain using deep mutational scanning and structure-based design

The unprecedented global demand for SARS-CoV-2 vaccines has demonstrated the need for highly effective vaccine candidates that are thermostable and amenable to large-scale manufacturing. Nanoparticle immunogens presenting the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein (S) in repetitive arrays are being advanced as second-generation vaccine candidates, as they feature robust manufacturing characteristics and have shown promising immunogenicity in preclinical models. Here, we used previously reported deep mutational scanning (DMS) data to guide the design of stabilized variants of the RBD. The selected mutations fill a cavity in the RBD that has been identified as a linoleic acid binding pocket. Screening of several designs led to the selection of two lead candidates that expressed at higher yields than the wild-type RBD. These stabilized RBDs possess enhanced thermal stability and resistance to aggregation, particularly when incorporated into an icosahedral nanoparticle immunogen that maintained its integrity and antigenicity for 28 days at 35-40{degrees}C, while corresponding immunogens displaying the wild-type RBD experienced aggregation and loss of antigenicity. The stabilized immunogens preserved the potent immunogenicity of the original nanoparticle immunogen, which is currently being evaluated in a Phase I/II clinical trial. Our findings may improve the scalability and stability of RBD-based coronavirus vaccines in any format and more generally highlight the utility of comprehensive DMS data in guiding vaccine design.

microbiology↗