Patterning and folding of intestinal villi by active mesenchymal dewetting.

Tissue folds are structural motifs critical to organ function. In the intestine, bending of a flat epithelium into a periodic pattern of folds gives rise to villi, finger-like protrusions that enable nutrient absorption. However, the molecular and mechanical processes driving villus morphogenesis remain unclear. Here, we identify an active mechanical mechanism that simultaneously patterns and folds the intestinal epithelium to initiate villus formation. At the cellular level, we find that PDGFRA+ subepithelial mesenchymal cells generate myosin II-dependent forces sufficient to produce patterned curvature in neighboring tissue interfaces. This symmetry-breaking process requires altered cell and extracellular matrix interactions that are enabled by matrix metalloproteinase-mediated tissue fluidization. Computational models, together with in vitro and in vivo experiments, revealed that these cellular features manifest at the tissue level as differences in interfacial tensions that promote mesenchymal aggregation and interface bending through a process analogous to the active dewetting of a thin liquid film.

Zfp106 binds to G-quadruplex RNAs and inhibits RAN translation and formation of RNA foci caused by G4C2 repeats.

Expansion of intronic GGGGCC repeats in the C9orf72 gene causes amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. Transcription of the expanded repeats results in the formation of RNA-containing nuclear foci and altered RNA metabolism. In addition, repeat-associated non-AUG (RAN) translation of the expanded GGGGCC-repeat sequence results in the production of highly toxic dipeptide-repeat (DPR) proteins. GGGGCC repeat-containing transcripts form G-quadruplexes, which are associated with formation of RNA foci and RAN translation. Zfp106, an RNA-binding protein essential for motor neuron survival in mice, suppresses neurotoxicity in a Drosophila model of C9orf72 ALS. Here, we show that Zfp106 inhibits formation of RNA foci and significantly reduces RAN translation caused by GGGGCC repeats in cultured mammalian cells, and we demonstrate that Zfp106 coexpression reduces the levels of DPRs in C9orf72 patient-derived cells. Further, we show that Zfp106 binds to RNA G-quadruplexes and causes a conformational change in the G-quadruplex structure formed by GGGGCC repeats. Together, these data demonstrate that Zfp106 suppresses the formation of RNA foci and DPRs caused by GGGGCC repeats and suggest that the G-quadruplex RNA-binding function of Zfp106 contributes to its suppression of GGGGCC repeat-mediated cytotoxicity.

De novo-designed transmembrane proteins bind and regulate a cytokine receptor.

Transmembrane (TM) domains as simple as a single span can perform complex biological functions using entirely lipid-embedded chemical features. Computational design has the potential to generate custom tool molecules directly targeting membrane proteins at their functional TM regions. Thus far, designed TM domain-targeting agents have been limited to mimicking the binding modes and motifs of natural TM interaction partners. Here, we demonstrate the design of de novo TM proteins targeting the erythropoietin receptor (EpoR) TM domain in a custom binding topology competitive with receptor homodimerization. The TM proteins expressed in mammalian cells complex with EpoR and inhibit erythropoietin-induced cell proliferation. In vitro, the synthetic TM domain complex outcompetes EpoR homodimerization. Structural characterization reveals that the complex involves the intended amino acids and agrees with our designed molecular model of antiparallel TM helices at 1:1 stoichiometry. Thus, membrane protein TM regions can now be targeted in custom-designed topologies.

Docking for Molecules That Bind in a Symmetric Stack with SymDOCK.

Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of great current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures, the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein's symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligand's docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural-network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study, SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.

An enhanced broad-spectrum peptide inhibits Omicron variants in vivo.

The continual emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) poses a major challenge to vaccines and antiviral therapeutics due to their extensive evasion of immunity. Aiming to develop potent and broad-spectrum anticoronavirus inhibitors, we generated A1-(GGGGS)7-HR2m (A1L35HR2m) by introducing an angiotensin-converting enzyme 2 (ACE2)-derived peptide A1 to the N terminus of the viral HR2-derived peptide HR2m through a long flexible linker, which showed significantly improved antiviral activity. Further cholesterol (Chol) modification at the C terminus of A1L35HR2m greatly enhanced the inhibitory activities against SARS-CoV-2, SARS-CoV-2 VOCs, SARS-CoV, and Middle East respiratory syndrome coronavirus (MERS-CoV) pseudoviruses, with IC50 values ranging from 0.16 to 5.53 nM. A1L35HR2m-Chol also potently inhibits spike-protein-mediated cell-cell fusion and the replication of authentic Omicron BA.2.12.1, BA.5, and EG.5.1. Importantly, A1L35HR2m-Chol distributed widely in respiratory tract tissue and had a long half-life (>10 h) in vivo. Intranasal administration of A1L35HR2m-Chol to K18-hACE2 transgenic mice potently inhibited Omicron BA.5 and EG.5.1 infection both prophylactically and therapeutically.

De novo design of peptides that bind specific conformers of α-synuclein.

Insoluble amyloids rich in cross-ß fibrils are observed in a number of neurodegenerative diseases. Depending on the clinicopathology, the amyloids can adopt distinct supramolecular assemblies, termed conformational strains. However, rapid methods to study amyloids in a conformationally specific manner are lacking. We introduce a novel computational method for de novo design of peptides that tile the surface of α-synuclein fibrils in a conformationally specific manner. Our method begins by identifying surfaces that are unique to the conformational strain of interest, which becomes a "target backbone" for the design of a peptide binder. Next, we interrogate structures in the PDB with high geometric complementarity to the target. Then, we identify secondary structural motifs that interact with this target backbone in a favorable, highly occurring geometry. This method produces monomeric helical motifs with a favorable geometry for interaction with the strands of the underlying amyloid. Each motif is then symmetrically replicated to form a monolayer that tiles the amyloid surface. Finally, amino acid sequences of the peptide binders are computed to provide a sequence with high geometric and physicochemical complementarity to the target amyloid. This method was applied to a conformational strain of α-synuclein fibrils, resulting in a peptide with high specificity for the target relative to other amyloids formed by α-synuclein, tau, or Aß40. This designed peptide also markedly slowed the formation of α-synuclein amyloids. Overall, this method offers a new tool for examining conformational strains of amyloid proteins.

De novo design of drug-binding proteins with predictable binding energy and specificity.

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule-binding proteins with tuned interaction energies is feasible entirely from computation.

De novo design of drug-binding proteins with predictable binding energy and specificity.

The de novo design of small-molecule-binding proteins has seen exciting recent progress; however, the ability to achieve exquisite affinity for binding small molecules while tuning specificity has not yet been demonstrated directly from computation. Here, we develop a computational procedure that results in the highest affinity binders to date with predetermined relative affinities, targeting a series of PARP1 inhibitors. Two of four designed proteins bound with affinities ranging from < 5 nM to low µM, in a predictable manner. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free-energy calculations performed directly on the designed models are in excellent agreement with the experimentally measured affinities, suggesting that the de novo design of small-molecule-binding proteins with tuned interaction energies is now feasible entirely from computation. We expect these methods to open many opportunities in biomedicine, including rapid sensor development, antidote design, and drug delivery vehicles.