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Crystal structure of the human σ1 receptor

Hayden R. Schmidt, Sanduo Zheng, Esin Gurpinar, Antoine Koehl, Aashish Manglik, Andrew C. Kruse
2016 Nature  
The human σ 1 receptor is an enigmatic ER-resident transmembrane protein implicated in a variety of disorders including depression, drug addiction, and neuropathic pain 1 . Recently, an additional connection to amyotrophic lateral sclerosis (ALS) has emerged from studies of human genetics and mouse models 2 . Unlike many transmembrane receptors that belong to large, extensively studied families such as G protein-coupled receptors or ligand-gated ion channels, the σ 1 receptor is an evolutionary
more » ... isolate with no discernible similarity to any other human protein. Despite its increasingly clear importance in human physiology and disease, the molecular architecture of the σ 1 receptor and its regulation by drug-like compounds remain poorly defined. Here, we report crystal structures of the human σ 1 receptor in complex with two chemically divergent ligands, PD144418 and 4-IBP. The structures reveal a trimeric architecture with a single transmembrane domain in each protomer. The carboxy-terminal domain of the receptor shows an extensive flat, hydrophobic membrane-proximal surface, suggesting an intimate association with the cytosolic surface of the ER membrane in cells. This domain includes a cupin-like β-barrel with the ligandbinding site buried at its center. This large, hydrophobic ligand-binding cavity shows remarkable plasticity in ligand recognition, binding the two ligands in similar positions despite dissimilar chemical structures. Taken together, these results reveal the overall architecture, oligomerization state, and molecular basis for ligand recognition by this important but poorly understood protein. The development of radiolabeled opiates in the 1960s and 1970s led to the discovery that the effects of these drugs are mediated by specific receptor sites with discrete pharmacological properties 3 . These receptors were divided into four classes based their ligand binding
doi:10.1038/nature17391 pmid:27042935 pmcid:PMC5550834 fatcat:jnwwasfn6nfnrft6ni2fxvhymm

Accelerating Protein Design Using Autoregressive Generative Models [article]

Adam J Riesselman, Jung-Eun Shin, Aaron W Kollasch, Conor McMahon, Elana Simon, Chris Sander, Aashish Manglik, Andrew C Kruse, Debora S Marks
2019 biorxiv/medrxiv   pre-print
A major biomedical challenge is the interpretation of genetic variation and the ability to design functional novel sequences. Since the space of all possible genetic variation is enormous, there is a concerted effort to develop reliable methods that can capture genotype to phenotype maps. State-of-art computational methods rely on models that leverage evolutionary information and capture complex interactions between residues. However, current methods are not suitable for a large number of
more » ... ant applications because they depend on robust protein or RNA alignments. Such applications include genetic variants with insertions and deletions, disordered proteins, and functional antibodies. Ideally, we need models that do not rely on assumptions made by multiple sequence alignments. Here we borrow from recent advances in natural language processing and speech synthesis to develop a generative deep neural network-powered autoregressive model for biological sequences that captures functional constraints without relying on an explicit alignment structure. Application to unseen experimental measurements of 43 deep mutational scans predicts the effect of insertions and deletions while matching state-of-art missense mutation prediction accuracies. We then test the model on single domain antibodies, or nanobodies, a complex target for alignment-based models due to the highly variable complementarity determining regions. We fit the model to a naïve llama immune repertoire and generate a diverse, optimized library of 105 nanobody sequences for experimental validation. Our results demonstrate the power of the 'alignment-free' autoregressive model in mutation effect prediction and design of traditionally challenging sequence families.
doi:10.1101/757252 fatcat:4dogko2o3vb75lu4q3hpqaor4i

A genetically encoded biosensor reveals location bias of opioid drug action [article]

Miriam Stoeber, Damien Jullie, Toon Laeremans, Jan Steyaert, Peter W. Schiller, Aashish Manglik, Mark von Zastrow
2018 bioRxiv   pre-print
feasible the development of a new class of genetically encoded probes, called conformational biosensors, which detect activated receptors based on a defined activation-associated conformational change (Manglik  ...  camelid-derived antibody fragment (nanobody) library that bind in vitro to μ-OR specifically in an active (agonistbound) relative to inactive (antagonist-bound) conformation ( Figure 1A ) (Huang et al., 2015; Manglik  ... 
doi:10.1101/254490 fatcat:ww5fssx5njfznlguyhtptuv6am

β-Arrestin-Biased Angiotensin II Receptor Agonists for COVID-19

Aashish Manglik, Laura M. Wingler, Howard A. Rockman, Robert J. Lefkowitz
2020 Circulation  
doi:10.1161/circulationaha.120.048723 pmid:32412788 pmcid:PMC7382535 fatcat:k5fcyvffvbcfbhxhv2s77ggcpq

Platform for rapid nanobody discovery in vitro [article]

Conor McMahon, Alexander S Baier, Sanduo Zheng, Roberta Pascolutti, Janice X. Ong, Sarah C. Erlandson, Daniel Hilger, Aaron M. Ring, Aashish Manglik, Andrew C. Kruse
2017 bioRxiv   pre-print
Camelid single-domain antibody fragments ('nanobodies') provide the remarkable specificity of antibodies within a single immunoglobulin VHH domain. This unique feature enables applications ranging from their use as biochemical tools to therapeutic agents. Virtually all nanobodies reported to date have been obtained by animal immunization, a bottleneck restricting many applications of this technology. To solve this problem, we developed a fully in vitro platform for nanobody discovery based on
more » ... ast surface display of a synthetic nanobody scaffold. This platform provides a facile and cost-effective method for rapidly isolating nanobodies targeting a diverse range of antigens. We provide a blueprint for identifying nanobodies starting from both purified and non-purified antigens, and in addition, we demonstrate application of the platform to discover rare conformationally-selective nanobodies to a lipid flippase and a G protein-coupled receptor. To facilitate broad deployment of this platform, we have made the library and all associated protocols publicly available.
doi:10.1101/151043 fatcat:vca6xeqr7zekzejpbcbeolaaim

Structure of human ferroportin reveals molecular basis of iron homeostasis [article]

Christian Billesboelle, Caleigh Azumaya, Rachael C Kretsch, Alexander S Powers, Shane Gonen, Simon Schneider, Tara Arvedson, Ron Dror, Yifan Cheng, Aashish Manglik
2020 bioRxiv   pre-print
Iron levels in blood are tightly controlled in humans by the action of the hormone hepcidin on the iron efflux transporter ferroportin. Hepcidin negatively regulates iron absorption and iron recycling by inducing ferroportin internalization and degradation. Aberrant ferroportin activity leads to diseases of iron overload, like hemochromatosis, or iron-restricted anemias. The molecular basis of ferroportin function, including iron transport and hepcidin regulation, remains incompletely
more » ... . Here, we combine cryo-electron microscopy, molecular dynamics simulations, and biochemical experiments to decipher molecular details of iron recognition and hepcidin binding to ferroportin. Iron binds to a conserved cavity in the C-domain of ferroportin, in a unique site within the broader major facilitator superfamily of transporters. We further show that hepcidin binding to ferroportin is allosterically coupled to iron, with a 80-fold increase in hepcidin affinity in the presence of iron. Hepcidin binds to the outward open conformation of ferroportin in a region adjacent to the iron-binding site in the C-domain. These results suggest a new model for hepcidin regulation of ferroportin, where only iron loaded ferroportin molecules are targeted for degradation. More broadly, our structural and functional insights are likely to enable more targeted manipulation of the hepcidin-ferroportin axis in disorders of iron homeostasis.
doi:10.1101/2020.03.16.993006 fatcat:csmyxbcibbfevcr4cuycrxwaui

Measuring ligand efficacy at the mu-opioid receptor using a conformational biosensor

Kathryn E Livingston, Jacob P Mahoney, Aashish Manglik, Roger K Sunahara, John R Traynor
2018 eLife  
Receptor was solubilized and purified in a final buffer comprised of 25 mM HEPES pH 7.4, 100 mM NaCl, 0.01% MNG (Anatrace), and 0.001% cholesterol hemisuccinate (CHS), as previously described (Manglik  ...  Key resources table Reagent type (species) or resource Designation Source or reference Identifiers Additional information Peptide, recombinant protein mu-opioid receptor Manglik et al. (2012  ... 
doi:10.7554/elife.32499 pmid:29932421 pmcid:PMC6042960 fatcat:y7cv5q663jg5rda3w5h2e3omn4

Propagation of conformational changes during μ-opioid receptor activation

Rémy Sounier, Camille Mas, Jan Steyaert, Toon Laeremans, Aashish Manglik, Weijiao Huang, Brian K. Kobilka, Héléne Déméné, Sébastien Granier
2015 Nature  
μ-Opioid receptors (μOR) are G protein coupled receptors (GPCRs) that are activated by a structurally diverse spectrum of natural and synthetic agonists including endogenous endorphin peptides, morphine and methadone. The recent structures of the μOR in inactive 1 and agonistinduced active states (companion article) provide snapshots of the receptor at the beginning and end of a signaling event, but little is known about the dynamic sequence of events that span these two states. Here we report
more » ... he use of solution-state NMR to examine the process of μOR activation. We obtained spectra of the μOR in the absence of ligand, and in the presence of the high-affinity agonist BU72 alone, or with BU72 and a G protein mimetic nanobody. Our results show that conformational changes in transmembrane segments (TM) 5 and 6, which are required for the full engagement of a G protein, are almost completely dependent on the presence of both the agonist and the G protein mimetic nanobody revealing a weak allosteric coupling between the agonist binding pocket and the G protein coupling interface (TM5 and TM6) similar to what has been observed for the β2-adrenergic receptor 2 . Unexpectedly, in the presence of agonist alone, we observe larger spectral changes involving intracellular loop 1 (ICL1) and helix 8 (H8), when compared to changes in TM5 and TM6. These results suggest that one or both of these domains may play a role in the initial interaction with the G protein, and that TM5 and TM6 are only engaged later in the process of complex formation. The initial interactions between the G protein Reprints and permissions information are available at www.nature.com/reprints.
doi:10.1038/nature14680 pmid:26245377 pmcid:PMC4820006 fatcat:x7qw2uotojbalczjgrrjl3bn2a

Nanobodies to Study G Protein–Coupled Receptor Structure and Function

Aashish Manglik, Brian K. Kobilka, Jan Steyaert
2017 Annual Review of Pharmacology and Toxicology  
Manglik · Kobilka · Steyaert Annu. Rev. Pharmacol. Toxicol. 2017.57:19-37. Downloaded from www.annualreviews.org Access provided by 94.224.135.220 on 01/21/17. For personal use only. v Annu.  ... 
doi:10.1146/annurev-pharmtox-010716-104710 pmid:27959623 pmcid:PMC5500200 fatcat:mxdrqaxwszgypadtvi7wfg5fqa

Structure of the δ-opioid receptor bound to naltrindole

Sébastien Granier, Aashish Manglik, Andrew C. Kruse, Tong Sun Kobilka, Foon Sun Thian, William I. Weis, Brian K. Kobilka
2012 Nature  
The opioid receptor family comprises three members, the m-, dand k-opioid receptors, which respond to classical opioid alkaloids such as morphine and heroin as well as to endogenous peptide ligands like endorphins. They belong to the G-proteincoupled receptor (GPCR) superfamily, and are excellent therapeutic targets for pain control. The d-opioid receptor (d-OR) has a role in analgesia, as well as in other neurological functions that remain poorly understood 1 . The structures of the m-OR and
more » ... OR have recently been solved 2,3 . Here we report the crystal structure of the mouse d-OR, bound to the subtype-selective antagonist naltrindole. Together with the structures of the m-OR and k-OR, the d-OR structure provides insights into conserved elements of opioid ligand recognition while also revealing structural features associated with ligand-subtype selectivity. The binding pocket of opioid receptors can be divided into two distinct regions. Whereas the lower part of this pocket is highly conserved among opioid receptors, the upper part contains divergent residues that confer subtype selectivity. This provides a structural explanation and validation for the 'message-address' model of opioid receptor pharmacology 4,5 , in which distinct 'message' (efficacy) and 'address' (selectivity) determinants are contained within a single ligand. Comparison of the address region of the d-OR with other GPCRs reveals that this structural organization may be a more general phenomenon, extending to other GPCR families as well. Opioid receptors have an important role in the central nervous system, regulating pain perception, hedonic homeostasis, mood and wellbeing 1 . Thus, they have long been the focus of physiological and pharmacological studies, as well as being important therapeutic targets. The opioid receptors are GPCRs, and were classified based on their pharmacology and their tissue distribution into three subclasses: the m (for morphine), the d (for vas deferens) and the k (for ketocyclazocine) receptors 6 . The sequence identity within the transmembrane domains (TMs) between the m-OR and d-OR, the m-OR and k-OR, and the d-OR and k-OR is 76%, 73% and 74%, respectively 7 . Another receptor identified by cloning, the nociceptin/orphanin FQ receptor, was classified in this family owing to a high sequence identity (67% in the TM) 7 . However, morphinans and most other classical opioid ligands have little affinity for the nociceptin receptor 8 . The m-, dand k-ORs are activated by endogenous peptides: the endorphins, enkephalins and dynorphins 8 . They are also the targets of chemically diverse small molecules with a variety of efficacy and selectivity profiles 8 . In an effort to understand better the structural basis for opioid receptor pharmacology and function, we used the in meso crystallization method to solve a 3.4 Å structure of a Mus musculus d-OR T4 lysozyme (T4L) fusion protein ( Supplementary Fig. 1 ) bound to naltrindole, a non-covalent d-OR-selective morphinan antagonist 9 . The d-OR structure presents the typical GPCR seven-pass transmembrane helix fold (Fig. 1a) , and shows marked conservation of backbone structure with other opioid receptors (Fig. 1b, c) , even in regions with low sequence conservation (Fig. 1d, e) . The ligand naltrindole sits in an exposed binding pocket, similar in shape to that observed for the m-OR and k-OR 2,3 . The CXCR4 receptor also has a solvent-exposed binding pocket, suggesting that this may be a feature common to some GPCRs activated by peptides. The b-hairpin in extracellular loop (ECL)2 (Fig. 1d) is observed in all three opioid receptors, despite the low sequence identity in this domain. ECL3, which is also poorly conserved among the three opioid receptors, was unresolved in the k-OR structure and has high temperature factors in both m-OR and d-OR (Fig. 1e) , suggesting a relatively flexible link between TM6 and TM7. Of note, the k-OR structure shows a clear difference in the position of the extracellular half of TM1, with an outward displacement of approximately 10 Å (Fig. 1b) compared to the m-OR and d-OR. In this respect, the m-OR and d-OR resemble each other and the CXCR4 chemokine receptor more closely than the k-OR. However, this structural difference may simply reflect differences in crystallization conditions or crystal packing influences, as is seen in the turkey b 1 -adrenergic receptor structure (PDB accession 2VT4), where two different TM1 conformations are observed in the same crystal 10 . dand m-ORs have been observed to form homo-oligomers in transfected cells, and functional studies suggest that they form pharmacologically distinct hetero-oligomers when they are co-expressed 11 . It is therefore interesting that in the m-OR crystal lattice two parallel dimeric interfaces were observed 2 ( Supplementary Fig. 2) . The most extensive interface involves TM5 and TM6 of adjacent protomers. The other interface, which is also observed in the k-OR, involves TM1, TM2 and helix 8. In addition to this common interface, an anti-parallel interaction is also observed in the k-OR crystal lattice. In contrast, the d-OR crystallizes with only an anti-parallel arrangement of receptor molecules ( Supplementary Fig. 2) . However, inferences regarding the physiological relevance of oligomeric interfaces observed in GPCR crystal structures should be made with caution. Purified, detergentsolubilized d-OR and m-OR are monomeric before crystallization and the association into either parallel or antiparallel dimers occurs during crystallogenesis. The differences between the m-OR and d-OR dimeric interfaces probably reflect differences in the most energetically favourable interactions under the crystallography conditions and may be the consequence of one or more of the following: different crystallization conditions, a different T4L arrangement, sequence differences in the protein, and subtle differences in the structures stabilized by the different ligands. Opioid receptors bind exceptionally well to highly diverse ligands, including morphinans, a wide variety of other small molecules, and peptides of varying length. Details of naltrindole binding to the d-OR are presented in Fig. 2 and Supplementary Fig. 3 . Despite their chemical diversity, many opioid ligands display conserved features, most notably a phenolic hydroxyl separated by six carbons from a positive charge, which mimics the amino-terminal tyrosine of all endogenous opioid peptides (Fig. 3) . The morphinan ligand naltrindole used in
doi:10.1038/nature11111 pmid:22596164 pmcid:PMC3523198 fatcat:iqus7o66k5fgniuspqwf4w6woa

Hedgehog pathway activation through conformational blockade of the Patched sterol conduit [article]

Yunxiao Zhang, Wan-Jin Lu, David Bulkley, Jiahao Liang, Arthur Ralko, Kelsey J Roberts, Anping Li, Wonhwa Cho, Yifan Cheng, Aashish Manglik, Philip Beachy
2019 bioRxiv   pre-print
Activation of the Hedgehog pathway may have therapeutic value for improved bone healing, taste receptor cell regeneration, and alleviation of colitis or other conditions. Systemic pathway activation, however, may be detrimental and therapeutic application has been difficult for lack of agents amenable to tissue targeting. We have developed a novel agonist, a conformation-specific nanobody against the Hedgehog receptor Patched1. This nanobody potently activates the Hedgehog pathway in vitro and
more » ... n vivo by stabilizing an alternative conformation of a Patched1 "switch helix", as revealed by cryo-EM structure determination. Although this conformation likely constitutes part of the transport cycle, nanobody-trapping disrupts the cycle and prevents substrate movement through the Patched1 sterol conduit. Our conformation-selective nanobody approach provides a new route to the development of transporter-related pharmacologic agents and may be generally applicable to the study of other transporters.
doi:10.1101/783290 fatcat:kkuw53irlnhi7fo472wgy6inae

Applications of molecular replacement to G protein-coupled receptors

Andrew C. Kruse, Aashish Manglik, Brian K. Kobilka, William I. Weis
2013 Acta Crystallographica Section D: Biological Crystallography  
The first, that of the -opioid receptor (OR) in space group C2 at 2.8 Å resolution (Manglik et al., 2012) , was solved in this manner following an identical procedure to that described above.  ... 
doi:10.1107/s090744491301322x pmid:24189241 pmcid:PMC3817703 fatcat:ik5lnqgozzacvfyl73wzlfkl3m

Stably Integrated luxCDABE for Assessment of Salmonella Invasion Kinetics

Kelly N. Flentie, Min Qi, Seth T. Gammon, Yasmin Razia, Felix Lui, Luciano Marpegan, Aashish Manglik, David Piwnica-Worms, Jeffrey S. McKinney
2008 Molecular Imaging  
Salmonella Typhimurium is a common cause of gastroenteritis in humans and also localizes to neoplastic tumors in animals. Invasion of specific eukaryotic cells is a key mechanism of Salmonella interactions with host tissues. Early stages of gastrointestinal cell invasion are mediated by a Salmonella type III secretion system, powered by the adenosine triphosphatase invC. The aim of this work was to characterize the invC dependence of invasion kinetics into disparate eukaryotic cells
more » ... y used as models of gut epithelium or neoplasms. Thus, a nondestructive real-time assay was developed to report eukaryotic cell invasion kinetics using lux + Salmonella that contain chromosomally integrated luxCDABE genes. Bioluminescence-based invasion assays using lux+ Salmonella exhibited inoculum dose-response correlation, distinguished invasion-competent from invasion-incompetent Salmonella, and discriminated relative Salmonella invasiveness in accordance with environmental conditions that induce invasion gene expression. In standard gentamicin protection assays, bioluminescence from lux+ Salmonella correlated with recovery of colony-forming units of internalized bacteria and could be visualized by bioluminescence microscopy. Furthermore, this assay distinguished invasion-competent from invasion-incompetent bacteria independent of gentamicin treatment in real time. Bioluminescence reported Salmonella invasion of disparate eukaryotic cell lines, including neoplastic melanoma, colon adenocarcinoma, and glioma cell lines used in animal models of malignancy. In each case, Salmonella invasion of eukaryotic cells was invC dependent.
doi:10.2310/7290.2008.00024 pmid:19123992 pmcid:PMC2743400 fatcat:w6izszmy3bfntdnyz5fpoip23i

The role of protein dynamics in GPCR function: insights from the β2AR and rhodopsin

Aashish Manglik, Brian Kobilka
2014 Current Opinion in Cell Biology  
G protein-coupled receptors (GPCRs) are versatile signaling proteins that mediate complex cellular responses to hormones and neurotransmitters. Recent advances in GPCR crystallography have provided inactive and active state structures for rhodopsin and the β 2 adrenergic receptor (β 2 AR). Although these structures suggest a two-state 'on-off' mechanism of receptor activation, other biophysical studies and observed signaling versatility suggest that GPCRs are highly dynamic and exist in a
more » ... ude of functionally distinct conformations. To fully understand how GPCRs work, we must characterize these conformations and determine how ligands affect their energetics and rates of interconversion. This brief review will compare and contrast the dynamic properties of rhodopsin and β 2 AR that shed light on the role of structural dynamics in their distinct signaling behaviors.
doi:10.1016/j.ceb.2014.01.008 pmid:24534489 pmcid:PMC3986065 fatcat:fnmmhwzu6bhudfkr2b6ij22pni

Protein design and variant prediction using autoregressive generative models

Jung-Eun Shin, Adam J Riesselman, Aaron W Kollasch, Conor McMahon, Elana Simon, Chris Sander, Aashish Manglik, Andrew C Kruse, Debora S Marks
2021 Nature Communications  
The ability to design functional sequences and predict effects of variation is central to protein engineering and biotherapeutics. State-of-art computational methods rely on models that leverage evolutionary information but are inadequate for important applications where multiple sequence alignments are not robust. Such applications include the prediction of variant effects of indels, disordered proteins, and the design of proteins such as antibodies due to the highly variable complementarity
more » ... termining regions. We introduce a deep generative model adapted from natural language processing for prediction and design of diverse functional sequences without the need for alignments. The model performs state-of-art prediction of missense and indel effects and we successfully design and test a diverse 105-nanobody library that shows better expression than a 1000-fold larger synthetic library. Our results demonstrate the power of the alignment-free autoregressive model in generalizing to regions of sequence space traditionally considered beyond the reach of prediction and design.
doi:10.1038/s41467-021-22732-w pmid:33893299 fatcat:2rjnbm3uajaqfmfpqpop3gon2m
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