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Infinite re-reading of single proteins at single-amino-acid resolution using nanopore sequencing

As identifying proteins is of paramount importance for cell biology and applications, it is of interest to develop a protein sequencer with the ultimate sensitivity of decoding individual proteins. Here, we demonstrate a nanopore-based single-molecule sequencing approach capable of reliably detecting single amino-acid substitutions within individual peptides. A peptide is linked to a DNA molecule that is pulled through the biological nanopore MspA by a DNA helicase in single amino-acid steps. The peptide sequence yields clear stepping ion current signals which allows to discriminate single-amino-acid substitutions in single reads. Molecular dynamics simulations show these signals to result from size exclusion and pore binding. Notably, we demonstrate the capability to rewind peptide reads, obtaining indefinitely many independent reads of the same individual molecule, yielding virtually 100% read accuracy in variant identification, with an error rate less than 10-6. These proof-of-concept experiments constitute a promising basis for developing a single-molecule protein sequencer. One-sentence summaryThis paper presents proof-of-concept experiments and simulations of a nanopore-based approach to sequencing individual proteins.

biophysics↗

Cross-species incompatibility between a DNA satellite and a chromatin protein poisons germline genome integrity

Satellite DNA spans megabases of eukaryotic sequence and evolves rapidly. Paradoxically, satellite-rich genomic regions mediate strictly conserved, essential processes like chromosome segregation and nuclear structure. A leading resolution to this paradox posits that satellite DNA and satellite-associated chromosomal proteins coevolve to preserve these essential functions. We experimentally test this model of intra-genomic coevolution by conducting the first evolution-guided manipulation of both chromosomal protein and DNA satellite. The 359bp satellite spans an 11Mb array in D. melanogaster that is absent from its sister species, D. simulans. This species-specific DNA satellite colocalizes with the adaptively evolving, ovary-enriched protein, Maternal Haploid (MH)-the Drosophila homolog of Spartan. To determine if MH and 359 coevolve, we swapped the D. simulans version of MH ("MH[sim]") into D. melanogaster. MH[sim] triggers ovarian cell death, reduced ovary size, and loss of mature eggs. Surprisingly, the D. melanogaster mh null mutant has no such ovary phenotypes, suggesting that MH[sim] is toxic in a D. melanogaster background. Using both cell biology and genetics, we discovered that MH[sim] poisons oogenesis through a DNA damage pathway. Remarkably, deleting the D. melanogaster-specific 359 satellite array completely restores mh[sim] germline genome integrity and fertility, consistent with a history of coevolution between these two fast-evolving loci. Germline genome integrity and fertility are also restored by overexpressing Topoisomerase II (Top2), suggesting that MH[sim] interferes with Top2-mediated processing of 359. The observed 359-MH[sim] cross-species incompatibility supports a model under which ostensibly inert repetitive DNA and essential chromosomal proteins must coevolve to preserve germline genome integrity.

evolutionary biology↗

2020 BioImage Analysis Survey: Community experiences and needs for the future

In this paper, we summarize a global survey of 484 participants of the imaging community, conducted in 2020 through the NIH Center for Open BioImage Analysis (COBA). This 23-question survey covered experience with image analysis, scientific background and demographics, and views and requests from different members of the imaging community. Through open-ended questions we asked the community to provide feedback for the open-source tool developers and tool user groups. The communitys requests for tool developers include general improvement of tool documentation and easy-to-follow tutorials. Respondents encourage tool users to follow the best practices guidelines for imaging and ask their image analysis questions on the Scientific Community Image forum (forum.image.sc). We analyzed the communitys preferred method of learning, based on level of computational proficiency and work description. In general, written step-by-step and video tutorials are preferred methods of learning by the community, followed by interactive webinars and office hours with an expert. There is also enthusiasm for a centralized location online for existing educational resources. The survey results will help the community, especially developers, trainers, and organizations like COBA, decide how to structure and prioritize their efforts. Impact statementThe Bioimage analysis community consists of software developers, imaging experts, and users, all with different expertise, scientific background, and computational skill levels. The NIH funded Center for Open Bioimage Analysis (COBA) was launched in 2020 to serve the cell biology communitys growing need for sophisticated open-source software and workflows for light microscopy image analysis. This paper shares the result of a COBA survey to assess the most urgent ongoing needs for software and training in the community and provide a helpful resource for software developers working in this domain. Here, we describe the state of open-source bioimage analysis, developers and users requests from the community, and our resulting view of common goals that would serve and strengthen the community to advance imaging science.

bioinformatics↗

Development of a universal nanobody-binding Fab module for fiducial-assisted cryo- EM studies of membrane proteins

With conformation-specific nanobodies being used for a wide range of structural, biochemical, and cell biological applications, there is a demand for antigen-binding fragments (Fabs) that specifically and tightly bind these nanobodies without disturbing the nanobody-target protein interaction. Here we describe the development of a synthetic Fab (termed NabFab) that binds the scaffold of an alpaca-derived nanobody with picomolar affinity. We demonstrate that upon CDR grafting onto this parent nanobody scaffold, nanobodies recognizing diverse target proteins and derived from llama or camel can cross-react with NabFab without loss of affinity. Using NabFab as a fiducial and size enhancer (50 kDa), we determined the high-resolution cryo-EM structures of nanobody-bound VcNorM and ScaDMT, both small membrane proteins of ~50 kDa. Using an additional anti-Fab nanobody further facillitated reliable initial 3D structure determination from small cryo-EM test datasets. Given that NabFab is of synthetic origin, humanized, and can be conveniently expressed in E. coli in large amounts, it may not only be useful for structural biology, but also for biomedical applications.

molecular biology↗

Characterization of USH1C/harmonin in the human retina provides insights into pathophysiology and therapy options for Usher syndrome

Usher syndrome (USH) is the most common form of hereditary deafness-blindness in humans. USH is a complex genetic disorder, assigned to three clinical subtypes differing in onset, course, and severity, with USH1 being the most severe. Rodent USH1 models do not reflect the ocular phenotype observed in human patients to date; hence, little is known about the pathophysiology of USH1 in the human eye. One of the USH1 genes, USH1C, exhibits extensive alternative splicing and encodes numerous harmonin protein isoforms that function as scaffolds for organizing the USH interactome. RNA-seq analysis of human retinas uncovered harmonin_a1 as the most abundant transcript of USH1C. Bulk RNA-seq analysis and immunoblotting showed abundant expression of harmonin in Muller glia cells (MGCs) and retinal neurons. Furthermore, harmonin was localized in the terminal endfeet and apical microvilli of MGCs, presynaptic region (pedicle) of cones, and outer segments of rods as well as at adhesive junctions of MGCs and photoreceptors in the outer limiting membrane (OLM). Our data provide evidence for the interactions of harmonin with OLM molecules in photoreceptors (PRCs) and MGCs and rhodopsin in PRCs. Subcellular expression and colocalization of harmonin correlate with the clinical phenotype observed in USH1C patients. In addition, primary cilia defects in USH1C patient-derived fibroblasts could be reverted by the delivery of harmonin_a1 transcript isoform. Our data provide novel insights into PRC cell biology, USH1C pathophysiology, and for developing gene therapy treatment.

molecular biology↗

LectinOracle - A Generalizable Deep Learning Model for Lectin-Glycan Binding Prediction

Ranging from bacterial cell adhesion over viral cell entry to human innate immunity, glycan-binding proteins or lectins abound in nature. Widely used as staining and characterization reagents in cell biology, and crucial for understanding the interactions in biological systems, lectins are a focal point of study in glycobiology. Yet the sheer breadth and depth of specificity for diverse oligosaccharide motifs has made studying lectins a largely piecemeal approach, with few options to generalize. Here, we present LectinOracle, a model combining transformer-based representations for proteins and graph convolutional neural networks for glycans to predict their interaction. Using a curated dataset of 564,647 unique protein-glycan interactions, we show that LectinOracle predictions agree with literature-annotated specificities for a wide range of lectins. We further identify clusters of lectins with related binding specificity that are not clustered based on sequence similarity. Using a range of specialized glycan arrays, we show that LectinOracle predictions generalize to new glycans and lectins, with qualitative and quantitative agreement with experimental data. We further demonstrate that LectinOracle can analyze whole lectomes and their role in host-microbe interactions. We envision that the herein presented platform will advance both the study of lectins and their role in (glyco)biology.

bioinformatics↗

Pathogenic, but not non-pathogenic, Rickettsia manipulate inflammasome-dependent IL-1 responses to facilitate their replication and host dissemination.

Rickettsia species (spp.) are strict obligate intracellular bacteria, with some being pathogenic in their mammalian host, including humans. One critical feature of these stealthy group of pathogens is their ability to manipulate hostile cytosolic environments to their benefits. Although our understanding of Rickettsia cell biology and pathogenesis are evolving, the mechanisms by which pathogenic Rickettsia spp. evade host innate immune detection remains elusive. Here, we showed that disease severity in wild-type (WT) C57BL/6J mice infected with R. typhi (etiologic agent of murine typhus) and R. rickettsii (etiologic agent of Rocky Mountain Spotted Fever), but not with non-pathogenic R. montanensis, correlated with levels of bacterial burden as detected in the spleens, as well as the serum concentrations of pro-inflammatory cytokine IL-1 and to a lesser extent IL- 1{beta}. Antibody-mediated neutralization of IL-1 confirmed a key role in controlling mortality rates and bacterial burdens of rickettsiae-infected WT mice. As macrophages are a primary source of both IL-1 and IL-1{beta} cytokines, we determined the mechanism of the anti-rickettsial activities using bone-marrow-derived macrophages. We found that pathogenic R. typhi and R. rickettsii, but not non-pathogenic R. montanensis, eluded pro- IL-1 induction and benefited pre-dominantly from the reduced IL-1 secretion, via a Caspase-11-Gsdmd-dependent pathway, to facilitate intracytosolic replication. Adoptative transfer experiments identified that IL-1 secretion by macrophages was critical for controlling rickettsiosis in WT mice. In sum, we identified a previously unappreciated pathway by which pathogenic, unlike non-pathogenic, rickettsiae preferentially target the Caspase-11-Gsdmd-IL-1 signaling axis in macrophages thus supporting their replication within the host. IMPORTANCECurrently, no vaccines are available to prevent rickettsioses, while vector-borne rickettsial infections in humans are on the rise globally. In fact, the insufficient understanding of how pathogenic Rickettsia species circumvent host immune defense mechanisms has significantly hindered the development of more effective therapeutics. Here, we identified a previously unappreciated role for the Caspase-11-Gsdmd-IL-1 signaling axis, to limiting the replication of pathogenic R. rickettsia and R. typhi species in murine macrophages and wild-type (WT) C57BL/6J mice. Adoptative transfer studies further identified IL-1-secreting macrophages as critical mediators in controlling rickettsial infection in WT mice. Collectively, these findings provide insight into the potential mechanism of how pathogenic, but not non-pathogenic Rickettsia spp., benefit from a reduction in the Caspase-11-Gsdmd-mediated release of IL-1 to support host colonization.

microbiology↗

Vascular lung triculture organoid via soluble extracellular matrix suspension

Micropatterned suspension culture creates consistently sized and shaped cell aggregates but has not produced organotypic structures from stable cells, thus restricting its use in accurate disease modeling. Here, we show that organotypic structure is achieved in hybrid suspension culture via supplementation of soluble extracellular matrix (ECM). We created a viable lung organoid from epithelial, endothelial, and fibroblast human stable cell lines in suspension culture. We demonstrate the importance of soluble ECM in organotypic patterning with the emergence of lumen-like structures with airspace showing feasible gas exchange units, formation of branching, perfusable vasculature, and long-term 70-day maintenance of lumen structure. Our results show a dependent relationship between enhanced fibronectin fibril assembly and the incorporation of ECM in the organoid. We successfully applied this technology in modeling lung fibrosis via bleomycin induction and test a potential antifibrotic drug in vitro while maintaining fundamental cell-cell interactions in lung tissue. Our human fluorescent lung organoid (hFLO) model represents features of pulmonary fibrosis which were ameliorated by fasudil treatment. We also demonstrate a 3D culture method with potential of creating organoids from mature cells, thus opening avenues for disease modeling and regenerative medicine, enhancing understanding of lung cell biology in health and lung disease.

bioengineering↗

Identification of electroporation sites in the complex lipid organization of the plasma membrane

The plasma membrane of a biological cell is a complex assembly of lipids and membrane proteins, which tightly regulate transmembrane transport. When a cell is exposed to a strong electric field, the membrane integrity becomes transiently disrupted by formation of transmembrane pores. This phenomenon, termed electroporation, is already utilized in many rapidly developing applications in medicine including gene therapy, cancer treatment, and treatment of cardiac arrythmias. However, the molecular mechanisms of electroporation are not yet sufficiently well understood; in particular, it is unclear where exactly pores form in the complex organization of the plasma membrane. In this study we combine coarse-grained molecular dynamics simulations, machine learning methods, and Bayesian survival analysis to identify how formation of pores depends on the local lipid organization. We show that pores do not form homogeneously across the membrane, but colocalize with domains that have specific features, the most important being high density of polyunsaturated lipids. We further show that knowing the lipid organization is sufficient to reliably predict poration sites with machine learning. However, by analysing poration kinetics with Bayesian survival analysis we then show that poration does not depend solely on local lipid arrangement, but also on membrane mechanical properties and the polarity of the electric field. Finally, we discuss how the combination of atomistic and coarse-grained molecular dynamics simulations, machine learning methods, and Bayesian survival analysis can guide the design of future experiments and help us to develop an accurate description of plasma membrane electroporation on the whole-cell level. Achieving this will allow us to shift the optimization of electroporation applications from blind trial-and-error approaches to mechanistic-driven design.

biophysics↗

Single-cell Atlas Unveils Cellular Heterogeneity and Novel Markers in Human Neonatal and Adult Intervertebral Discs

The origin, composition, distribution, and function of cells in the human intervertebral disc (IVD) has not been fully understood. Here, cell atlases of both human neonatal and adult IVDs have been generated and further assessed by gene ontology pathway enrichment, pseudo-time trajectory, histology, and immunofluorescence. Comparison of cell atlases revealed the presence of two sub-populations of notochordal cells (NCs) and their associated markers in both the neonatal and adult IVDs. Developmental trajectories predicted 7 different cell states that describe the developmental process from neonatal to adult cells in IVD and analyzed the NCs role in the IVD development. A high heterogeneity and gradual transition of annulus fibrosus cells (AFCs) in the neonatal IVD was detected and their potential relevance in IVD development assessed. Collectively, comparing single-cell atlases between neonatal and adult IVDs delineates the landscape of IVD cell biology and may help discovering novel therapeutic targets for IVD degeneration.

developmental biology↗

Activity-dependent endoplasmic reticulum Ca2+ uptake depends on Kv2.1-mediated endoplasmic reticulum/plasma membrane junctions to promote synaptic transmission

The endoplasmic reticulum (ER) forms a continuous and dynamic network throughout a neuron, extending from dendrites to axon terminals, and axonal ER dysfunction is implicated in several neurological disorders. In addition, tight junctions between the ER and plasma membrane (PM) are formed by several molecules including Kv2 channels, but the cellular functions of many ER-PM junctions remain unknown. Dynamic Ca2+ uptake into the ER during electrical activity plays an essential role in synaptic transmission as failure to allow rapid ER Ca2+ filling during stimulation activates stromal interaction molecule 1 (STIM1) and decreases both presynaptic Ca2+ influx and synaptic vesicle exocytosis. Our experiments demonstrate that Kv2.1 channels are necessary for enabling ER Ca2+ uptake during electrical activity as genetic depletion of Kv2.1 rendered both the somatic and axonal ER unable to accumulate Ca2+ during electrical stimulation. Moreover, our experiments show that the loss of Kv2.1 in the axon impairs synaptic vesicle fusion during stimulation via a mechanism unrelated to modulation of membrane voltage. Thus, our data demonstrate that the non-conducting role of Kv2.1 in forming stable junctions between the ER and PM via ER VAMP-associated protein (VAP) binding couples ER Ca2+ uptake with electrical activity. Our results further suggest that Kv2.1 has a critical function in neuronal cell biology for Ca2+-handling independent of voltage and reveals a novel and critical pathway for maintaining ER lumen Ca2+ levels and efficient neurotransmitter release. Taken together these findings reveal an essential non-classical role for both Kv2.1 and the ER-PM junctions in synaptic transmission. SignificanceThe endoplasmic reticulum (ER) extends throughout the neuron as a continuous organelle, and its dysfunction is associated with several neurological disorders. During electrical activity, the ER takes up Ca2+ from the cytosol which has been shown to support synaptic transmission. This close choreography of ER Ca2+ uptake with electrical activity suggests functional coupling of the ER to sources of voltage-gated Ca2+ entry through an unknown mechanism. Here we report a non-conducting role for Kv2.1 through its ER binding domain that is necessary for ER Ca2+ uptake during neuronal activity. Loss of Kv2.1 profoundly disables neurotransmitter release without altering presynaptic voltage suggesting that Kv2.1-mediated signaling hubs play an important neurobiological role in Ca2+ handling and synaptic transmission independent of ion conduction.

neuroscience↗

Chromosome-scale assemblies of Acanthamoeba castellanii genomes provide insights into Legionella pneumophila infection-related chromatin re-organization

The unicellular amoeba Acanthamoeba castellanii is ubiquitous in aquatic environments, where it preys on bacteria. The organism also hosts bacterial endosymbionts, some of which are parasitic, including human pathogens such as Chlamydia and Legionella spp. Here we report complete, high quality genome sequences for two extensively studied A. castellanii strains, Neff and C3. Combining long- and short-read data with Hi-C, we generated near chromosome-level assemblies for both strains with 90% of the genome contained in 29 scaffolds for the Neff strain and 31 for the C3 strain. Comparative genomics revealed strain-specific functional enrichment, most notably genes related to signal transduction in the C3 strain, and to viral replication in Neff. Furthermore, we characterized the spatial organization of the A. castellanii genome and showed that it is reorganized during infection by Legionella pneumophila. Infection-dependent chromatin loops were found to be enriched in genes for signal transduction and phosphorylation processes. In genomic regions where chromatin organization changed during Legionella infection, we found functional enrichment for genes associated with metabolism, organelle assembly, and cytoskeleton organization, suggesting that changes in chromosomal folding are associated with host cell biology during infection.

genomics↗

Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction

Experimental studies of cell growth, inheritance, and their associated processes by microscopy require accurate single-cell observations of sufficient duration to reconstruct the genealogy. However, cell tracking--assigning identical cells on consecutive images to a track--is often challenging due to imperfect segmentation, moving cells, or focus drift, resulting in laborious manual verification. Here, we propose fingerprints to identify problematic assignments rapidly. A fingerprint distance measures the similarity between cells in two consecutive images by comparing the structural information contained in the low frequencies of a Fourier transform. We show that it is broadly applicable across cell types and image modalities, provided the image has sufficient structural information. Our tracker (TracX) uses the concept to reject unlikely assignments, thereby substantially increasing tracking performance on published and newly generated long-term data sets from various species. For S. cerevisiae, we propose a comprehensive model for cell size control at the single-cell and population level centered on the Whi5 regulator. It demonstrates how highly precise tracking can help uncover previously undescribed single-cell biology.

systems biology↗

DeepBacs: Bacterial image analysis using open-source deep learning approaches

Deep Learning (DL) is rapidly changing the field of microscopy, allowing for efficient analysis of complex data while often out-performing classical algorithms. This revolution has led to a significant effort to create user-friendly tools allowing biomedical researchers with little background in computer sciences to use this technology effectively. Thus far, these approaches have mainly focused on analysing microscopy images from eukaryotic samples and are still underused in microbiology. In this work, we demonstrate how to use a range of state-of-the-art artificial neural-networks particularly suited for the analysis of bacterial microscopy images, using our recently developed ZeroCostDL4Mic platform. We showcase different DL approaches for segmenting bright field and fluorescence images of different bacterial species, use object detection to classify different growth stages in time-lapse imaging data, and carry out DL-assisted phenotypic profiling of antibiotic-treated cells. To also demonstrate the DL capacity to enhance low-phototoxicity live-cell microscopy, we showcase how image denoising can allow researchers to attain high-fidelity data in faster and longer imaging. Finally, artificial labelling of cell membranes and predictions of super-resolution images allow for accurate mapping of cell shape and intracellular targets. To aid in the training of novice users, we provide a purposefully-built database of training and testing data, enabling bacteriologists to quickly explore how to analyse their data through DL. We hope this lays a fertile ground for the efficient application of DL in microbiology and fosters the creation of novel tools for bacterial cell biology and antibiotic research.

microbiology↗

Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation

Advances in microscopy hold great promise for allowing quantitative and precise readouts of morphological and molecular phenomena at the single cell level in bacteria. However, the potential of this approach is ultimately limited by the availability of methods to perform unbiased cell segmentation, defined as the ability to faithfully identify cells independent of their morphology or optical characteristics. In this study, we present a new algorithm, Omnipose, which accurately segments samples that present significant challenges to current algorithms, including mixed bacterial cultures, antibiotic-treated cells, and cells of extended or branched morphology. We show that Omnipose achieves generality and performance beyond leading algorithms and its predecessor, Cellpose, by virtue of unique neural network outputs such as the gradient of the distance field. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism and on the segmentation of non-bacterial objects. Our results distinguish Omnipose as a uniquely powerful tool for answering diverse questions in bacterial cell biology.

microbiology↗

Towards a structurally resolved human protein interaction network

All cellular functions are governed by complex molecular machines that assemble through protein-protein interactions. Their atomic details are critical to the study of their molecular mechanisms but fewer than 5% of hundreds of thousands of human interactions have been structurally characterized. Here, we test the potential and limitations of recent progress in deep-learning methods using AlphaFold2 to predict structures for 65,484 human interactions. We show that higher confidence models are enriched in interactions supported by affinity or structure-based methods and can be orthogonally confirmed by spatial constraints defined by cross-link data. We identify 3,137 high confidence models, of which 1,371 have no homology to a known structure, from which we identify interface residues harbouring disease mutations, suggesting potential mechanisms for pathogenic variants. We find groups of interface phosphorylation sites that show patterns of co-regulation across conditions, suggestive of coordinated tuning of multiple interactions as signalling responses. Finally, we provide examples of how the predicted binary complexes can be used to build larger assemblies. Accurate prediction of protein complexes promises to greatly expand our understanding of the atomic details of human cell biology in health and disease.

bioinformatics↗

A nuclear cAMP microdomain suppresses tumor growth by Hippo pathway inactivation

cAMP signaling pathways are critical for both oncogenesis and tumor suppression. cAMP signaling is localized to multiple spatially distinct microdomains, but the role of cAMP microdomains in cancer cell biology is poorly understood. We developed a tunable genetic system that allows us to activate cAMP signaling in specific microdomains. We uncovered a previously unappreciated nuclear cAMP microdomain that functionally activates a tumor suppressive pathway in a broad range of cancers by inhibiting YAP, a key effector protein of the Hippo pathway, inside the nucleus. We show that nuclear cAMP induces a LATS-dependent pathway leading to phosphorylation of nuclear YAP solely at serine 397, export of YAP from the nucleus, without YAP protein degradation. Thus, nuclear cAMP inhibition of nuclear YAP is distinct from other known mechanisms of Hippo regulation. Pharmacologic targeting of specific cAMP microdomains remains an untapped therapeutic approach for cancer, and since Hippo pathway deregulation can lead to oncogenesis and chemotherapeutic resistance, drugs directed at the nuclear cAMP microdomain may provide new avenues for the treatment of cancer.

cancer biology↗

Cryo-EM of the yeast VO complex reveals distinct binding sites for macrolide V-ATPase inhibitors

Vacuolar-type adenosine triphosphatases (V-ATPases) are proton pumps found in almost all eukaryotic cells. These enzymes consist of a soluble catalytic V1 region that hydrolyzes ATP and a membrane-embedded VO region responsible for proton translocation. V-ATPase activity leads to acidification of endosomes, phagosomes, lysosomes, secretory vesicles, and the trans-Golgi network, with extracellular acidification occurring in some specialized cells. Small molecule inhibitors of V-ATPase have played a crucial role in elucidating numerous aspects of cell biology by blocking acidification of intracellular compartments, while therapeutic use of V-ATPase inhibitors has been proposed for treatment of cancer, osteoporosis, and some infections. Here, we determine structures of the isolated VO complex from Saccharomyces cerevisiae bound to two well-known macrolide inhibitors: bafilomycin A1 and archazolid A. The structures reveal different binding sites for the inhibitors on the surface of the proton-carrying c ring, with only a small amount of overlap between the two sites. Binding of both inhibitors is mediated primarily through van der Waals interactions in shallow pockets and suggests that the inhibitors block rotation of the ring. Together, these structures indicate the existence of a large chemical space available for V-ATPase inhibitors that block acidification by binding the c ring.

biochemistry↗