Regulation of intestinal senescence during cholestatic liver disease modulates barrier function and liver disease progression.

Background & Aims: Senescence has been reported to have differential functions in cholangiocytes and hepatic stellate cells (HSCs) during human and murine cholestatic disease, being detrimental in biliary cells and anti-fibrotic in HSCs. Cholestatic liver disease is associated with loss of intestinal barrier function and changes in the microbiome, the mechanistic cause of which is undetermined. Methods: Intestinal samples were analysed from controls and patients with primary sclerosing cholangitis, as well as wild-type (WT) and p16-3MR transgenic mice. Cholestatic liver disease was induced by bile duct ligation (BDL) and DDC diet feeding. Fexaramine was used as an intestinal-restricted FXR agonist and antibiotics were given to eliminate the intestinal microbiome. Senescent cells were eliminated in p16-3MR mice with ganciclovir and in WT mice with the senolytic drug ABT-263. In vitro studies were done in intestinal CaCo-2 cells and organoids were generated from intestinal crypts isolated from mice. Results: Herein, we show increased senescence in intestinal epithelial cells (IECs) in patients with primary sclerosing cholangitis and in mice after BDL and DDC diet feeding. Intestinal senescence was increased in response to reduced exposure to bile acids and increased presence of lipopolysaccharide in vitro and in vivo during cholestatic liver disease. Senescence of IECs was associated with lower proliferation but increased intestinal stem cell activation, as supported by increased organoid growth from intestinal stem cells. Elimination of senescent cells with genetic and pharmacological approaches exacerbated liver injury and fibrosis during cholestatic liver disease, which was associated with increased IEC apoptosis and permeability. Conclusions: Senescence occurs in IECs during cholestatic disease and the elimination of senescent cells has a detrimental impact on the gut-liver axis. Our results point to cell-specific rather than systemic targeting of senescence as a therapeutic approach to treat cholestatic liver disease. Impact and implications: Cholestatic liver disease associates with the dysregulation of intestinal barrier function, while the mechanisms mediating the disruption of the gut-liver axis remain largely undefined. Here, we demonstrate that senescence, a cellular response to stress, is activated in intestinal cells during cholestatic liver disease in humans and mice. Mechanistically, we demonstrate that the reduction of bile acids and the increased presence of bacterial products mediate the activation of intestinal senescence during cholestatic liver disease. Importantly, the elimination of these senescent cells promotes further damage to the intestine that aggravates liver disease, with increased tissue damage and fibrosis. Our results provide evidence that therapeutic strategies to treat cholestatic liver disease by eliminating senescent cells may have unwanted effects in the intestine and support the need to develop cell/organ-specific approaches.

Enumerative Discovery of Noncanonical Polypeptide Secondary Structures.

Energetically favorable local interactions can overcome the entropic cost of chain ordering and cause otherwise flexible polymers to adopt regularly repeating backbone conformations. A prominent example is the α helix present in many protein structures, which is stabilized by i, i + 4 hydrogen bonds between backbone peptide units. With the increased chemical diversity offered by unnatural amino acids and backbones, it has been possible to identify regularly repeating structures not present in proteins, but to date, there has been no systematic approach for identifying new polymers likely to have such structures despite their considerable potential for molecular engineering. Here we describe a systematic approach to search through dipeptide combinations of 130 chemically diverse amino acids to identify those predicted to populate unique low-energy states. We characterize ten newly identified dipeptide repeating structures using circular dichroism spectroscopy and comparison with calculated spectra. NMR and X-ray crystallographic structures of two of these dipeptide-repeat polymers are similar to the computational models. Our approach is readily generalizable to identify low-energy repeating structures for a wide variety of polymers, and our ordered dipeptide repeats provide new building blocks for molecular engineering.

Protein interactions in human pathogens revealed through deep learning.

Identification of bacterial protein-protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lite, a rapid deep learning model that leverages residue-residue coevolution and protein structure prediction to systematically identify and structurally characterize protein-protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1,923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer-membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.

Computational design of serine hydrolases.

Enzymes that proceed through multistep reaction mechanisms often utilize complex, polar active sites positioned with sub-angstrom precision to mediate distinct chemical steps, which makes their de novo construction extremely challenging. We sought to overcome this challenge using the classic catalytic triad and oxyanion hole of serine hydrolases as a model system. We used RFdiffusion1 to generate proteins housing catalytic sites of increasing complexity and varying geometry, and a newly developed ensemble generation method called ChemNet to assess active site geometry and preorganization at each step of the reaction. Experimental characterization revealed novel serine hydrolases that catalyze ester hydrolysis with catalytic efficiencies (k cat /K m ) up to 3.8 x 103 M-1 s-1, closely match the design models (Cα RMSDs < 1 Å), and have folds distinct from natural serine hydrolases. In silico selection of designs based on active site preorganization across the reaction coordinate considerably increased success rates, enabling identification of new catalysts in screens of as few as 20 designs. Our de novo buildup approach provides insight into the geometric determinants of catalysis that complements what can be obtained from structural and mutational studies of native enzymes (in which catalytic group geometry and active site makeup cannot be so systematically varied), and provides a roadmap for the design of industrially relevant serine hydrolases and, more generally, for designing complex enzymes that catalyze multi-step transformations.

Comparative evaluation of the accuracy of six different apex locators in working length determination of molars using intraoral periapical radiographs: An in vivo study.

Context: One of the crucial steps in endodontic treatment is determining the working length (WL). There are various methods for performing this procedure, one of which is an electronic apex locator (EAL) measurement. Aims: The aim of this study was to determine the accuracy of six EALs, i.e.. Root ZX, Root ZX Mini, Propex PiXi, Innvopex-1, Woodpex III, and Raypex 6 for WL estimation in the mandibular first molars. Material and Method: The study included 180 root canals with symptomatic irreversible pulpitis, divided into six groups using different apex locators. WL determination was compared with intraoral periapical radiographs. Results were categorized as accurate, short, or long. The data were statistically analyzed. Results: ROOT ZX had an accuracy of 96.7%, Root ZX Mini had an accuracy of 93.3%, PiXi had an accuracy of 90.0%, Innvopex-1 had an accuracy of 90.0%, Woodpex III had an accuracy of 86.7%, and Raypex 6 had an accuracy of 83.4%, respectively. There was a statistically nonsignificant difference between groups (P < 0.05). Conclusion: Newly developed apex locators, such as the Innvopex-1, have shown accuracy comparable to well-established EALs like the Root ZX. This highlights the importance of conducting more extensive, large-scale research to confirm and validate their effectiveness.

Prognostic Significance of Hemodynamics in Patients With Transposition of the Great Arteries and Systemic Right Ventricle.

BACKGROUND: Patients with transposition of the great arteries (TGA) and systemic right ventricle often confront significant adverse cardiac events. The prognostic significance of invasive hemodynamic parameters in this context remains uncertain. Our hypothesis is that the aortic pulsatility index and hemodynamic profiling utilizing invasive measures provide prognostic insights for patients with TGA and a systemic right ventricle. METHODS: This retrospective multicenter cohort study encompasses adults with TGA and a systemic right ventricle who underwent cardiac catheterization. Data collection, spanning from 1994 to 2020, encompasses clinical and hemodynamic parameters, including measured and calculated values such as pulmonary capillary wedge pressure, aortic pulsatility index, and cardiac index. Pulmonary capillary wedge pressure and cardiac index values were used to establish 4 distinct hemodynamic profiles. A pulmonary capillary wedge pressure of ≥15 mm Hg indicated congestion, termed wet, while a cardiac index <2.2 L/min per m2 signified inadequate perfusion, labeled cold. The primary outcome comprised a composite of all-cause death, heart transplantation, or the requirement for mechanical circulatory support. RESULTS: Of 1721 patients with TGA, 242 individuals with available invasive hemodynamic data were included. The median follow-up duration after cardiac catheterization was 11.4 (interquartile range, 7.5-15.9) years, with a mean age of 38.5±10.8 years at the time of cardiac catheterization. Among hemodynamic parameters, an aortic pulsatility index <1.5 emerged as a robust predictor of the primary outcome, with adjusted hazard ratios of 5.90 (95% CI, 3.01-11.62; P<0.001). Among the identified 4 hemodynamic profiles, the cold/wet profile was associated with the highest risk for the primary outcome, with an adjusted hazard ratio of 3.83 (95% CI, 1.63-9.02; P<0.001). CONCLUSIONS: A low aortic pulsatility index (<1.5) and the cold/wet hemodynamic profile are linked with an elevated risk of adverse long-term cardiac outcomes in patients with TGA and systemic right ventricle.

De novo design of miniprotein antagonists of cytokine storm inducers.

Cytokine release syndrome (CRS), commonly known as cytokine storm, is an acute systemic inflammatory response that is a significant global health threat. Interleukin-6 (IL-6) and interleukin-1 (IL-1) are key pro-inflammatory cytokines involved in CRS and are hence critical therapeutic targets. Current antagonists, such as tocilizumab and anakinra, target IL-6R/IL-1R but have limitations due to their long half-life and systemic anti-inflammatory effects, making them less suitable for acute or localized treatments. Here we present the de novo design of small protein antagonists that prevent IL-1 and IL-6 from interacting with their receptors to activate signaling. The designed proteins bind to the IL-6R, GP130 (an IL-6 co-receptor), and IL-1R1 receptor subunits with binding affinities in the picomolar to low-nanomolar range. X-ray crystallography studies reveal that the structures of these antagonists closely match their computational design models. In a human cardiac organoid disease model, the IL-1R antagonists demonstrated protective effects against inflammation and cardiac damage induced by IL-1ß. These minibinders show promise for administration via subcutaneous injection or intranasal/inhaled routes to mitigate acute cytokine storm effects.

A pan-variant miniprotein inhibitor protects against SARS-CoV-2 variants.

The continued evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has compromised neutralizing antibody responses elicited by prior infection or vaccination and abolished the utility of most monoclonal antibody therapeutics. We previously described a computationally-designed, homotrimeric miniprotein inhibitor, designated TRI2-2, that protects mice against pre-Omicron SARS-CoV-2 variants. Here, we show that TRI2-2 exhibits pan neutralization of variants that evolved during the 4.5 years since the emergence of SARS-CoV-2 and protects mice against BQ.1.1, XBB.1.5 and BA.2.86 challenge when administered post-exposure by an intranasal route. The resistance of TRI2-2 to viral escape and its direct delivery to the upper airways rationalize a path toward clinical advancement.

Single-cell sensor analyses reveal signaling programs enabling Ras-G12C drug resistance.

Clinical resistance to rat sarcoma virus (Ras)-G12C inhibitors is a challenge. A subpopulation of cancer cells has been shown to undergo genomic and transcriptional alterations to facilitate drug resistance but the immediate adaptive effects on Ras signaling in response to these drugs at the single-cell level is not well understood. Here, we used Ras biosensors to profile the activity and signaling environment of endogenous Ras at the single-cell level. We found that a subpopulation of KRas-G12C cells treated with Ras-G12C-guanosine-diphosphate inhibitors underwent adaptive signaling and metabolic changes driven by wild-type Ras at the Golgi and mutant KRas at the mitochondria, respectively. Our Ras biosensors identified major vault protein as a mediator of Ras activation through its scaffolding of Ras signaling pathway components and metabolite channels. Overall, methods including ours that facilitate direct analysis on the single-cell level can report the adaptations that subpopulations of cells adopt in response to cancer therapies, thus providing insight into drug resistance.

Massively parallel measurement of protein-protein interactions by sequencing using MP3-seq.

Protein-protein interactions (PPIs) regulate many cellular processes and engineered PPIs have cell and gene therapy applications. Here, we introduce massively parallel PPI measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Lastly, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics-based energy terms to predict MP3-seq values. We find that AF-M-based models could be valuable for prescreening interactions but experimentally measuring interactions remains necessary to rank their strengths quantitatively.

Accurate de novo design of heterochiral protein-protein interactions.

Abiotic D-proteins that selectively bind to natural L-proteins have gained significant biotechnological interest. However, the underlying structural principles governing such heterochiral protein-protein interactions remain largely unknown. In this study, we present the de novo design of D-proteins consisting of 50-65 residues, aiming to target specific surface regions of L-proteins or L-peptides. Our designer D-protein binders exhibit nanomolar affinity toward an artificial L-peptide, as well as two naturally occurring proteins of therapeutic significance: the D5 domain of human tropomyosin receptor kinase A (TrkA) and human interleukin-6 (IL-6). Notably, these D-protein binders demonstrate high enantiomeric specificity and target specificity. In cell-based experiments, designer D-protein binders effectively inhibited the downstream signaling of TrkA and IL-6 with high potency. Moreover, these binders exhibited remarkable thermal stability and resistance to protease degradation. Crystal structure of the designed heterochiral D-protein-L-peptide complex, obtained at a resolution of 2.0 Å, closely resembled the design model, indicating that the computational method employed is highly accurate. Furthermore, the crystal structure provides valuable information regarding the interactions between helical L-peptides and D-proteins, particularly elucidating a novel mode of heterochiral helix-helix interactions. Leveraging the design of D-proteins specifically targeting L-peptides or L-proteins opens up avenues for systematic exploration of the mirror-image protein universe, paving the way for a diverse range of applications.

Parametrically guided design of beta barrels and transmembrane nanopores using deep learning.

Francis Crick's global parameterization of coiled coil geometry has been widely useful for guiding design of new protein structures and functions. However, design guided by similar global parameterization of beta barrel structures has been less successful, likely due to the deviations required from ideal beta barrel geometry to maintain extensive inter-strand hydrogen bonding without introducing considerable backbone strain. Instead, beta barrels and other protein folds have been designed guided by 2D structural blueprints; while this approach has successfully generated new fluorescent proteins, transmembrane nanopores, and other structures, it requires considerable expert knowledge and provides only indirect control over the global barrel shape. Here we show that the simplicity and control over shape and structure provided by global parametric representations can be generalized beyond coiled coils by taking advantage of the rich sequence-structure relationships implicit in RoseTTAFold based inpainting and diffusion design methods. Starting from parametrically generated idealized barrel backbones, both RFjoint inpainting and RFdiffusion readily incorporate the backbone irregularities necessary for proper folding with minimal deviation from the idealized barrel geometries. We show that for beta barrels across a broad range of global beta sheet parameterizations, these methods achieve high in silico and experimental success rates, with atomic accuracy confirmed by an X-ray crystal structure of a novel beta barrel topology, and de novo designed 12, 14, and 16 stranded transmembrane nanopores with conductances ranging from 200 to 500 pS. By combining the simplicity and control of parametric generation with the high success rates of deep learning based protein design methods, our approach makes the design of proteins where global shape confers function, such as beta barrel nanopores, more precisely specifiable and accessible.

Capturing clinically relevant Campylobacter attributes through direct whole genome sequencing of stool.

Campylobacter is the leading bacterial cause of infectious intestinal disease, but the pathogen typically accounts for a very small proportion of the overall stool microbiome in each patient. Diagnosis is even more difficult due to the fastidious nature of Campylobacter in the laboratory setting. This has, in part, driven a change in recent years, from culture-based to rapid PCR-based diagnostic assays which have improved diagnostic detection, whilst creating a knowledge gap in our clinical and epidemiological understanding of Campylobacter genotypes - no isolates to sequence. In this study, direct metagenomic sequencing approaches were used to assess the possibility of replacing genome sequences with metagenome sequences; metagenomic sequencing outputs were used to describe clinically relevant attributes of Campylobacter genotypes. A total of 37 diarrhoeal stool samples with Campylobacter and five samples with an unknown pathogen result were collected and processed with and without filtration, DNA was extracted, and metagenomes were sequenced by short-read sequencing. Culture-based methods were used to validate Campylobacter metagenome-derived genome (MDG) results. Sequence output metrics were assessed for Campylobacter genome quality and accuracy of characterization. Of the 42 samples passing quality checks for analysis, identification of Campylobacter to the genus and species level was dependent on Campylobacter genome read count, coverage and genome completeness. A total of 65% (24/37) of samples were reliably identified to the genus level through Campylobacter MDG, 73% (27/37) by culture and 97% (36/37) by qPCR. The Campylobacter genomes with a genome completeness of over 60% (n=21) were all accurately identified at the species level (100%). Of those, 72% (15/21) were identified to sequence types (STs), and 95% (20/21) accurately identified antimicrobial resistance (AMR) gene determinants. Filtration of stool samples enhanced Campylobacter MDG recovery and genome quality metrics compared to the corresponding unfiltered samples, which improved the identification of STs and AMR profiles. The phylogenetic analysis in this study demonstrated the clustering of the metagenome-derived with culture-derived genomes and revealed the reliability of genomes from direct stool sequencing. Furthermore, Campylobacter genome spiking percentages ranging from 0 to 2% total metagenome abundance in the ONT MinION sequencer, configured to adaptive sequencing, exhibited better assembly quality and accurate identification of STs, particularly in the analysis of metagenomes containing 2 and 1% of Campylobacter jejuni genomes. Direct sequencing of Campylobacter from stool samples provides clinically relevant and epidemiologically important genomic information without the reliance on cultured genomes.

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 part in the control of metabolism and cell signalling1-3. 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-Wyman-Changeux model of cooperativity10, we investigate the de novo design of allostery through rigid-body coupling of peptide-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 peptide 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 peptide effectors and can have ligand-binding cooperativity comparable to classic natural systems such as haemoglobin14. Our results indicate that allostery can arise from global coupling of the energetics of protein substructures without optimized side-chain-side-chain allosteric communication pathways and provide a roadmap for generating allosterically triggerable delivery systems, protein nanomachines and cellular feedback control circuitry.

Computational stabilization of a non-heme iron enzyme enables efficient evolution of new function.

Directed evolution has emerged as a powerful tool for engineering new biocatalysts. However, introducing new catalytic residues can be destabilizing, and it is generally beneficial to start with a stable enzyme parent. Here we show that the deep learning-based tool ProteinMPNN can be used to redesign Fe(II)/αKG superfamily enzymes for greater stability, solubility, and expression while retaining both native activity and industrially-relevant non-native functions. For the Fe(II)/αKG enzyme tP4H, we performed site-saturation mutagenesis with both the wild-type and stabilized design variant and screened for activity increases in a non-native C-H hydroxylation reaction. We observed substantially larger increases in non-native activity for variants obtained from the stabilized scaffold compared to those from the wild-type enzyme. ProteinMPNN is user-friendly and widely-accessible, and straightforward structural criteria were sufficient to obtain stabilized, catalytically-functional variants of the Fe(II)/αKG enzymes tP4H and GriE. Our work suggests that stabilization by computational sequence redesign could be routinely implemented as a first step in directed evolution campaigns for novel biocatalysts.

Sequence-specific targeting of intrinsically disordered protein regions.

A general approach to design proteins that bind tightly and specifically to intrinsically disordered regions (IDRs) of proteins and flexible peptides would have wide application in biological research, therapeutics, and diagnosis. However, the lack of defined structures and the high variability in sequence and conformational preferences has complicated such efforts. We sought to develop a method combining biophysical principles with deep learning to readily generate binders for any disordered sequence. Instead of assuming a fixed regular structure for the target, general recognition is achieved by threading the query sequence through diverse extended binding modes in hundreds of templates with varying pocket depths and spacings, followed by RFdiffusion refinement to optimize the binder-target fit. We tested the method by designing binders to 39 highly diverse unstructured targets. Experimental testing of ~36 designs per target yielded binders with affinities better than 100 nM in 34 cases, and in the pM range in four cases. The co-crystal structure of a designed binder in complex with dynorphin A is closely consistent with the design model. All by all binding experiments for 20 designs binding diverse targets show they are highly specific for the intended targets, with no crosstalk even for the closely related dynorphin A and dynorphin B. Our approach thus could provide a general solution to the intrinsically disordered protein and peptide recognition problem.

Condom Failure Among HIV-Negative Men in Serodiscordant Relationships in Australia, Brazil, and Thailand.

Condoms continue to be used by many gay, bisexual, and other men who have sex with men (GBM) to reduce the risk of HIV transmission. However this is impacted by condom failure events, defined here as condom breakage and slippage. In a prospective, observational cohort study of 343 HIV serodiscordant male couples recruited through high HIV caseload clinics and hospitals between 2012 and 2016 in Australia, Brazil, and Thailand, condom failure rates and associated factors were analysed, including with the study partner versus other sexual partners. There were 717 reported instances of condom failure from an estimated total of 25,831 sex acts with condoms, from over 588.4 participant years of follow up. Of the HIV-negative partners (n = 343) in the study, more than a third (n = 117, 36.7%) reported at least one instance of condom failure with any partner type during study follow-up. Condom failure with their study partner was reported by 91/343 (26.5%) HIV-negative partners, compared with 43/343 (12.5%) who reported condom failure with other partners. In total, there were 86 events where the HIV-negative partner experienced ano-receptive condom failure with ejaculation, representing 12.0% of all failure events. In multivariable analysis, compared to Australia, HIV-negative men in Brazil reported a higher incidence risk rate of condom failure (IRR = 1.64, 95%CI 1.01-2.68, p = 0.046) and HIV-negative men who reported anal sex with other partners reported an increased risk of condom failure compared with men who only had sex with their study partner (IRR = 1.89, 95%CI 1.08-3.33, p = 0.025). Although at least one event of condom failure was reported by a significant proportion of participants, overall condom failure events represented a small proportion of the total condom protected sex acts.

De Novo Design of Integrin α5ß1 Modulating Proteins for Regenerative Medicine.

Integrin α5ß1 is crucial for cell attachment and migration in development and tissue regeneration, and α5ß1 binding proteins could have considerable utility in regenerative medicine and next-generation therapeutics. We use computational protein design to create de novo α5ß1-specific modulating miniprotein binders, called NeoNectins, that bind to and stabilize the open state of α5ß1. When immobilized onto titanium surfaces and throughout 3D hydrogels, the NeoNectins outperform native fibronectin and RGD peptide in enhancing cell attachment and spreading, and NeoNectin-grafted titanium implants outperformed fibronectin and RGD-grafted implants in animal models in promoting tissue integration and bone growth. NeoNectins should be broadly applicable for tissue engineering and biomedicine.

Binding and sensing diverse small molecules using shape-complementary pseudocycles.

We describe an approach for designing high-affinity small molecule-binding proteins poised for downstream sensing. We use deep learning-generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.

Sculpting conducting nanopore size and shape through de novo protein design.

Transmembrane ß-barrels have considerable potential for a broad range of sensing applications. Current engineering approaches for nanopore sensors are limited to naturally occurring channels, which provide suboptimal starting points. By contrast, de novo protein design can in principle create an unlimited number of new nanopores with any desired properties. Here we describe a general approach to designing transmembrane ß-barrel pores with different diameters and pore geometries. Nuclear magnetic resonance and crystallographic characterization show that the designs are stably folded with structures resembling those of the design models. The designs have distinct conductances that correlate with their pore diameter, ranging from 110 picosiemens (~0.5 nanometer pore diameter) to 430 picosiemens (~1.1 nanometer pore diameter). Our approach opens the door to the custom design of transmembrane nanopores for sensing and sequencing applications.