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Krishna Kumar K, Wang H, Habrian C, Latorraca NR, Xu J, O'Brien ES, Zhang C, Montabana E, Koehl A, Marqusee S, Isacoff EY, Kobilka BK. Author Correction: Stepwise activation of a metabotropic glutamate receptor. Nature 2024:10.1038/s41586-024-07470-5. [PMID: 38702522 DOI: 10.1038/s41586-024-07470-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/06/2024]
Affiliation(s)
- Kaavya Krishna Kumar
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
| | - Haoqing Wang
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA, USA
| | - Chris Habrian
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Naomi R Latorraca
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Jun Xu
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Evan S O'Brien
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Chensong Zhang
- Division of CryoEM and Bioimaging, Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA, USA
| | - Elizabeth Montabana
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Antoine Koehl
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Susan Marqusee
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- QB3 Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, USA
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, USA
| | - Ehud Y Isacoff
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Brian K Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
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Krishna Kumar K, Wang H, Habrian C, Latorraca NR, Xu J, O'Brien ES, Zhang C, Montabana E, Koehl A, Marqusee S, Isacoff EY, Kobilka BK. Stepwise activation of a metabotropic glutamate receptor. Nature 2024:10.1038/s41586-024-07327-x. [PMID: 38632403 DOI: 10.1038/s41586-024-07327-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 03/15/2024] [Indexed: 04/19/2024]
Abstract
Metabotropic glutamate receptors belong to a family of G protein-coupled receptors that are obligate dimers and possess a large extracellular ligand-binding domain that is linked via a cysteine-rich domain to their 7-transmembrane domain1. Upon activation, these receptors undergo a large conformational change to transmit the ligand binding signal from the extracellular ligand-binding domain to the G protein-coupling 7-transmembrane domain2. In this manuscript, we propose a model for a sequential, multistep activation mechanism of metabotropic glutamate receptor subtype 5. We present a series of structures in lipid nanodiscs, from inactive to fully active, including agonist-bound intermediate states. Further, using bulk and single-molecule fluorescence imaging, we reveal distinct receptor conformations upon allosteric modulator and G protein binding.
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Affiliation(s)
- Kaavya Krishna Kumar
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
| | - Haoqing Wang
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA, USA
| | - Chris Habrian
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Naomi R Latorraca
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Jun Xu
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Evan S O'Brien
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Chensong Zhang
- Division of CryoEM and Bioimaging, Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA, USA
| | - Elizabeth Montabana
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Antoine Koehl
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Susan Marqusee
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- QB3 Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, USA
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, USA
| | - Ehud Y Isacoff
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Brian K Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
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Yu J, Kumar A, Zhang X, Martin C, Raia P, Koehl A, Laeremans T, Steyaert J, Manglik A, Ballet S, Boland A, Stoeber M. Structural Basis of μ-Opioid Receptor-Targeting by a Nanobody Antagonist. bioRxiv 2023:2023.12.06.570395. [PMID: 38106026 PMCID: PMC10723425 DOI: 10.1101/2023.12.06.570395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The μ-opioid receptor (μOR), a prototypical member of the G protein-coupled receptor (GPCR) family, is the molecular target of opioid analgesics such as morphine and fentanyl. Due to the limitations and severe side effects of currently available opioid drugs, there is considerable interest in developing novel modulators of μOR function. Most GPCR ligands today are small molecules, however biologics, including antibodies and nanobodies, are emerging as alternative therapeutics with clear advantages such as affinity and target selectivity. Here, we describe the nanobody NbE, which selectively binds to the μOR and acts as an antagonist. We functionally characterize NbE as an extracellular and genetically encoded μOR ligand and uncover the molecular basis for μOR antagonism by solving the cryo-EM structure of the NbE-μOR complex. NbE displays a unique ligand binding mode and achieves μOR selectivity by interactions with the orthosteric pocket and extracellular receptor loops. Based on a β-hairpin loop formed by NbE that deeply inserts into the μOR and centers most binding contacts, we design short peptide analogues that retain μOR antagonism. The work illustrates the potential of nanobodies to uniquely engage with GPCRs and describes novel μOR ligands that can serve as a basis for therapeutic developments.
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Affiliation(s)
- Jun Yu
- Department of Molecular and Cellular Biology, University of Geneva, Geneva, Switzerland
| | - Amit Kumar
- Department of Cell Physiology and Metabolism, University of Geneva, Geneva, Switzerland
| | - Xuefeng Zhang
- Department of Molecular and Cellular Biology, University of Geneva, Geneva, Switzerland
| | - Charlotte Martin
- Departments of Chemistry and Bioengineering Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Pierre Raia
- Department of Plant Sciences, University of Geneva, Geneva, Switzerland
| | - Antoine Koehl
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | | | - Jan Steyaert
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
- VIB-VUB Center for Structural Biology, VIB, Brussels, Belgium
| | - Aashish Manglik
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
| | - Steven Ballet
- Departments of Chemistry and Bioengineering Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Andreas Boland
- Department of Molecular and Cellular Biology, University of Geneva, Geneva, Switzerland
| | - Miriam Stoeber
- Department of Cell Physiology and Metabolism, University of Geneva, Geneva, Switzerland
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Kumar KK, Wang H, Habrian C, Latorraca NR, Xu J, O’Brien ES, Zhang C, Montabana E, Koehl A, Marqusee S, Isacoff EY, Kobilka BK. Step-wise activation of a Family C GPCR. bioRxiv 2023:2023.08.29.555158. [PMID: 37693614 PMCID: PMC10491200 DOI: 10.1101/2023.08.29.555158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Metabotropic glutamate receptors belong to a family of G protein-coupled receptors that are obligate dimers and possess a large extracellular ligand-binding domain (ECD) that is linked via a cysteine-rich domain (CRDs) to their 7-transmembrane (TM) domain. Upon activation, these receptors undergo a large conformational change to transmit the ligand binding signal from the ECD to the G protein-coupling TM. In this manuscript, we propose a model for a sequential, multistep activation mechanism of metabotropic glutamate receptor subtype 5. We present a series of structures in lipid nanodiscs, from inactive to fully active, including agonist-bound intermediate states. Further, using bulk and single-molecule fluorescence imaging we reveal distinct receptor conformations upon allosteric modulator and G protein binding.
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Affiliation(s)
- Kaavya Krishna Kumar
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, USA
| | - Haoqing Wang
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, USA
- Sarafin ChEM-H, 290 Jane Stanford Way, Stanford, California 94305, USA
| | - Chris Habrian
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, USA
| | - Naomi R. Latorraca
- Department of Molecular and Cell Biology, University of California Berkeley, CA 94720, USA
| | - Jun Xu
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, USA
| | - Evan S. O’Brien
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, USA
| | - Chensong Zhang
- Division of CryoEM and Bioimaging, Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA, USA
| | - Elizabeth Montabana
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, USA
| | - Antoine Koehl
- Department of Statistics, University of California, Berkeley, CA 94720, USA
| | - Susan Marqusee
- Department of Molecular and Cell Biology, University of California Berkeley, CA 94720, USA; QB3 Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley CA 94720, USA; Department of Chemistry, University of California, Berkeley, Berkeley CA 94720, USA
| | - Ehud Y. Isacoff
- Department of Molecular and Cell Biology, University of California Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley CA 94720, USA
| | - Brian K. Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, USA
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Jagota M, Ye C, Albors C, Rastogi R, Koehl A, Ioannidis N, Song YS. Cross-protein transfer learning substantially improves disease variant prediction. Genome Biol 2023; 24:182. [PMID: 37550700 PMCID: PMC10408151 DOI: 10.1186/s13059-023-03024-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 07/27/2023] [Indexed: 08/09/2023] Open
Abstract
BACKGROUND Genetic variation in the human genome is a major determinant of individual disease risk, but the vast majority of missense variants have unknown etiological effects. Here, we present a robust learning framework for leveraging saturation mutagenesis experiments to construct accurate computational predictors of proteome-wide missense variant pathogenicity. RESULTS We train cross-protein transfer (CPT) models using deep mutational scanning (DMS) data from only five proteins and achieve state-of-the-art performance on clinical variant interpretation for unseen proteins across the human proteome. We also improve predictive accuracy on DMS data from held-out proteins. High sensitivity is crucial for clinical applications and our model CPT-1 particularly excels in this regime. For instance, at 95% sensitivity of detecting human disease variants annotated in ClinVar, CPT-1 improves specificity to 68%, from 27% for ESM-1v and 55% for EVE. Furthermore, for genes not used to train REVEL, a supervised method widely used by clinicians, we show that CPT-1 compares favorably with REVEL. Our framework combines predictive features derived from general protein sequence models, vertebrate sequence alignments, and AlphaFold structures, and it is adaptable to the future inclusion of other sources of information. We find that vertebrate alignments, albeit rather shallow with only 100 genomes, provide a strong signal for variant pathogenicity prediction that is complementary to recent deep learning-based models trained on massive amounts of protein sequence data. We release predictions for all possible missense variants in 90% of human genes. CONCLUSIONS Our results demonstrate the utility of mutational scanning data for learning properties of variants that transfer to unseen proteins.
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Affiliation(s)
- Milind Jagota
- Computer Science Division, University of California, Berkeley, 94720, CA, USA
| | - Chengzhong Ye
- Department of Statistics, University of California, Berkeley, 94720, CA, USA
| | - Carlos Albors
- Computer Science Division, University of California, Berkeley, 94720, CA, USA
| | - Ruchir Rastogi
- Computer Science Division, University of California, Berkeley, 94720, CA, USA
| | - Antoine Koehl
- Department of Statistics, University of California, Berkeley, 94720, CA, USA
| | - Nilah Ioannidis
- Computer Science Division, University of California, Berkeley, 94720, CA, USA
- Chan Zuckerberg Biohub, San Francisco, 94158, CA, USA
- Center for Computational Biology, University of California, Berkeley, 94720, CA, USA
| | - Yun S Song
- Computer Science Division, University of California, Berkeley, 94720, CA, USA.
- Department of Statistics, University of California, Berkeley, 94720, CA, USA.
- Center for Computational Biology, University of California, Berkeley, 94720, CA, USA.
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6
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Koleske ML, McInnes G, Brown JEH, Thomas N, Hutchinson K, Chin MY, Koehl A, Arkin MR, Schlessinger A, Gallagher RC, Song YS, Altman RB, Giacomini KM. Functional genomics of OCTN2 variants informs protein-specific variant effect predictor for Carnitine Transporter Deficiency. Proc Natl Acad Sci U S A 2022; 119:e2210247119. [PMID: 36343260 PMCID: PMC9674959 DOI: 10.1073/pnas.2210247119] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 09/16/2022] [Indexed: 11/09/2022] Open
Abstract
Genetic variants in SLC22A5, encoding the membrane carnitine transporter OCTN2, cause the rare metabolic disorder Carnitine Transporter Deficiency (CTD). CTD is potentially lethal but actionable if detected early, with confirmatory diagnosis involving sequencing of SLC22A5. Interpretation of missense variants of uncertain significance (VUSs) is a major challenge. In this study, we sought to characterize the largest set to date (n = 150) of OCTN2 variants identified in diverse ancestral populations, with the goals of furthering our understanding of the mechanisms leading to OCTN2 loss-of-function (LOF) and creating a protein-specific variant effect prediction model for OCTN2 function. Uptake assays with 14C-carnitine revealed that 105 variants (70%) significantly reduced transport of carnitine compared to wild-type OCTN2, and 37 variants (25%) severely reduced function to less than 20%. All ancestral populations harbored LOF variants; 62% of green fluorescent protein (GFP)-tagged variants impaired OCTN2 localization to the plasma membrane of human embryonic kidney (HEK293T) cells, and subcellular localization significantly associated with function, revealing a major LOF mechanism of interest for CTD. With these data, we trained a model to classify variants as functional (>20% function) or LOF (<20% function). Our model outperformed existing state-of-the-art methods as evaluated by multiple performance metrics, with mean area under the receiver operating characteristic curve (AUROC) of 0.895 ± 0.025. In summary, in this study we generated a rich dataset of OCTN2 variant function and localization, revealed important disease-causing mechanisms, and improved upon machine learning-based prediction of OCTN2 variant function to aid in variant interpretation in the diagnosis and treatment of CTD.
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Affiliation(s)
- Megan L. Koleske
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94143
| | - Gregory McInnes
- Biomedical Informatics Training Program, Stanford University, Stanford, CA 94305
- Empirico Inc., San Diego, CA 92122
| | - Julia E. H. Brown
- Program in Bioethics, University of California, San Francisco, CA 94143
- Institute for Health & Aging, University of California, San Francisco, CA 94143
| | - Neil Thomas
- Computer Science Division, University of California, Berkeley, CA 94720
| | - Keino Hutchinson
- Department of Pharmacological Sciences, Icahn School of Medicine at Mt. Sinai, New York, NY 10029
| | - Marcus Y. Chin
- Small Molecule Discovery Center, Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94143
| | - Antoine Koehl
- Department of Statistics, University of California, Berkeley, CA 94720
| | - Michelle R. Arkin
- Small Molecule Discovery Center, Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94143
| | - Avner Schlessinger
- Department of Pharmacological Sciences, Icahn School of Medicine at Mt. Sinai, New York, NY 10029
| | - Renata C. Gallagher
- Institute for Human Genetics, University of California, San Francisco, CA 94143
- Department of Pediatrics, University of California, San Francisco, CA 94143
| | - Yun S. Song
- Computer Science Division, University of California, Berkeley, CA 94720
- Department of Statistics, University of California, Berkeley, CA 94720
| | - Russ B. Altman
- Department of Bioengineering, Stanford University, Stanford, CA 94305
- Department of Genetics, Stanford University, Stanford, CA 94305
| | - Kathleen M. Giacomini
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94143
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7
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Koehl A, Jagota M, Erdmann-Pham DD, Fung A, Song YS. Transferability of Geometric Patterns from Protein Self-Interactions to Protein-Ligand Interactions. Pac Symp Biocomput 2022; 27:22-33. [PMID: 34890133 PMCID: PMC8669734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
There is significant interest in developing machine learning methods to model protein-ligand interactions but a scarcity of experimentally resolved protein-ligand structures to learn from. Protein self-contacts are a much larger source of structural data that could be leveraged, but currently it is not well understood how this data source differs from the target domain. Here, we characterize the 3D geometric patterns of protein self-contacts as probability distributions. We then present a flexible statistical framework to assess the transferability of these patterns to protein-ligand contacts. We observe that the level of transferability from protein self-contacts to protein-ligand contacts depends on contact type, with many contact types exhibiting high transferability. We then demonstrate the potential of leveraging information from these geometric patterns to aid in ligand pose-selection problems in protein-ligand docking. We publicly release our extracted data on geometric interaction patterns to enable further exploration of this problem.
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Affiliation(s)
- Antoine Koehl
- Department of Statistics, University of California, Berkeley, CA 94720, USA
| | - Milind Jagota
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
| | | | - Alexander Fung
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
| | - Yun S. Song
- Department of Statistics, University of California, Berkeley, CA 94720, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158
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8
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Chavan TS, Cheng RC, Jiang T, Mathews II, Stein RA, Koehl A, Mchaourab HS, Tajkhorshid E, Maduke M. A CLC-ec1 mutant reveals global conformational change and suggests a unifying mechanism for the CLC Cl -/H + transport cycle. eLife 2020; 9:53479. [PMID: 32310757 PMCID: PMC7253180 DOI: 10.7554/elife.53479] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 04/18/2020] [Indexed: 12/16/2022] Open
Abstract
Among coupled exchangers, CLCs uniquely catalyze the exchange of oppositely charged ions (Cl– for H+). Transport-cycle models to describe and explain this unusual mechanism have been proposed based on known CLC structures. While the proposed models harmonize with many experimental findings, gaps and inconsistencies in our understanding have remained. One limitation has been that global conformational change – which occurs in all conventional transporter mechanisms – has not been observed in any high-resolution structure. Here, we describe the 2.6 Å structure of a CLC mutant designed to mimic the fully H+-loaded transporter. This structure reveals a global conformational change to improve accessibility for the Cl– substrate from the extracellular side and new conformations for two key glutamate residues. Together with DEER measurements, MD simulations, and functional studies, this new structure provides evidence for a unified model of H+/Cl– transport that reconciles existing data on all CLC-type proteins. Cells are shielded from harmful molecules and other threats by a thin, flexible layer called the membrane. However, this barrier also prevents chloride, sodium, protons and other ions from moving in or out of the cell. Channels and transporters are two types of membrane proteins that form passageways for these charged particles. Channels let ions flow freely from one side of the membrane to the other. To do so, these proteins change their three-dimensional shape to open or close as needed. On the other hand, transporters actively pump ions across the membrane to allow the charged particles to accumulate on one side. The shape changes needed for that type of movement are different: the transporters have to open a passageway on one side of the membrane while closing it on the other side, alternating openings to one side or the other. In general, channels and transporters are not related to each other, but one exception is a group called CLCs proteins. Present in many organisms, this family contains a mixture of channels and transporters. For example, humans have nine CLC proteins: four are channels that allow chloride ions in and out, and five are ‘exchange transporters’ that make protons and chloride ions cross the membrane in opposite directions. These proteins let one type of charged particle move freely across the membrane, which generates energy that the transporter then uses to actively pump the other ion in the direction needed by the cell. Yet, the exact three-dimensional changes required for CLC transporters and channels to perform their roles are still unknown. To investigate this question, Chavan, Cheng et al. harnessed a technique called X-ray crystallography, which allows scientists to look at biological molecules at the level of the atom. This was paired with other methods to examine a CLC mutant that adopts the shape of a normal CLC transporter when it is loaded with a proton. The experiments revealed how various elements in the transporter move relative to each other to adopt a structure that allows protons and chloride ions to enter the protein from opposite sides of the membrane, using separate pathways. While obtained on a bacterial CLC, these results can be applied to other CLC channels and transporters (including those in humans), shedding light on how this family transports charged particles across membranes. From bone diseases to certain types of seizures, many human conditions are associated with poorly functioning CLCs. Understanding the way these structures change their shapes to perform their roles could help to design new therapies for these health problems.
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Affiliation(s)
- Tanmay S Chavan
- Department of Molecular & Cellular Physiology, Stanford University School of Medicine, Stanford, United States
| | - Ricky C Cheng
- Department of Molecular & Cellular Physiology, Stanford University School of Medicine, Stanford, United States
| | - Tao Jiang
- NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Irimpan I Mathews
- Stanford Synchrotron Radiation Lightsource, Stanford University, Menlo Park, United States
| | - Richard A Stein
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, United States
| | - Antoine Koehl
- Department of Molecular & Cellular Physiology, Stanford University School of Medicine, Stanford, United States
| | - Hassane S Mchaourab
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, United States
| | - Emad Tajkhorshid
- NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Merritt Maduke
- Department of Molecular & Cellular Physiology, Stanford University School of Medicine, Stanford, United States
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9
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Koehl A, Hu H, Feng D, Sun B, Zhang Y, Robertson MJ, Chu M, Kobilka TS, Laeremans T, Steyaert J, Tarrasch J, Dutta S, Fonseca R, Weis WI, Mathiesen JM, Skiniotis G, Kobilka BK. Structural insights into the activation of metabotropic glutamate receptors. Nature 2019; 566:79-84. [PMID: 30675062 PMCID: PMC6709600 DOI: 10.1038/s41586-019-0881-4] [Citation(s) in RCA: 181] [Impact Index Per Article: 36.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 12/12/2018] [Indexed: 12/11/2022]
Abstract
Metabotropic glutamate receptors are family C G-protein-coupled receptors. They form obligate dimers and possess extracellular ligand-binding Venus flytrap domains, which are linked by cysteine-rich domains to their 7-transmembrane domains. Spectroscopic studies show that signalling is a dynamic process, in which large-scale conformational changes underlie the transmission of signals from the extracellular Venus flytraps to the G protein-coupling domains-the 7-transmembrane domains-in the membrane. Here, using a combination of X-ray crystallography, cryo-electron microscopy and signalling studies, we present a structural framework for the activation mechanism of metabotropic glutamate receptor subtype 5. Our results show that agonist binding at the Venus flytraps leads to a compaction of the intersubunit dimer interface, thereby bringing the cysteine-rich domains into close proximity. Interactions between the cysteine-rich domains and the second extracellular loops of the receptor enable the rigid-body repositioning of the 7-transmembrane domains, which come into contact with each other to initiate signalling.
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Affiliation(s)
- Antoine Koehl
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Hongli Hu
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA.,Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Dan Feng
- ConfometRx, Santa Clara, CA, USA
| | | | - Yan Zhang
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA.,Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael J Robertson
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA.,Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Tong Sun Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.,ConfometRx, Santa Clara, CA, USA
| | - Toon Laeremans
- Structural Biology Brussels, Vrije Universiteit Brussel (VUB), Brussels, Belgium.,VIB-VUB Center for Structural Biology, VIB, Brussels, Belgium
| | - Jan Steyaert
- Structural Biology Brussels, Vrije Universiteit Brussel (VUB), Brussels, Belgium.,VIB-VUB Center for Structural Biology, VIB, Brussels, Belgium
| | - Jeffrey Tarrasch
- Life Sciences Institute and Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Somnath Dutta
- Life Sciences Institute and Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, MI, USA.,Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
| | - Rasmus Fonseca
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA.,Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.,Biosciences Division, SLAC National Accelerator Laboratory, Stanford University, Stanford, CA, USA
| | - William I Weis
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA.,Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Jesper M Mathiesen
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Georgios Skiniotis
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA. .,Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
| | - Brian K Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA. .,ConfometRx, Santa Clara, CA, USA.
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10
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Maeda S, Koehl A, Matile H, Hu H, Hilger D, Schertler GFX, Manglik A, Skiniotis G, Dawson RJP, Kobilka BK. Development of an antibody fragment that stabilizes GPCR/G-protein complexes. Nat Commun 2018; 9:3712. [PMID: 30213947 PMCID: PMC6137068 DOI: 10.1038/s41467-018-06002-w] [Citation(s) in RCA: 116] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Accepted: 07/25/2018] [Indexed: 11/10/2022] Open
Abstract
Single-particle cryo-electron microscopy (cryo-EM) has recently enabled high-resolution structure determination of numerous biological macromolecular complexes. Despite this progress, the application of high-resolution cryo-EM to G protein coupled receptors (GPCRs) in complex with heterotrimeric G proteins remains challenging, owning to both the relative small size and the limited stability of these assemblies. Here we describe the development of antibody fragments that bind and stabilize GPCR-G protein complexes for the application of high-resolution cryo-EM. One antibody in particular, mAb16, stabilizes GPCR/G-protein complexes by recognizing an interface between Gα and Gβγ subunits in the heterotrimer, and confers resistance to GTPγS-triggered dissociation. The unique recognition mode of this antibody makes it possible to transfer its binding and stabilizing effect to other G-protein subtypes through minimal protein engineering. This antibody fragment is thus a broadly applicable tool for structural studies of GPCR/G-protein complexes. The determination of high resolution structures of G protein coupled receptors (GPCRs) in complex with heterotrimeric G proteins is challenging. Here authors develop an antibody fragment, mAB16, which stabilizes GPCR/G-protein complexes and facilitates the application of high resolution cryo-EM.
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Affiliation(s)
- Shoji Maeda
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305, USA
| | - Antoine Koehl
- Department of Structural Biology, Stanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305, USA
| | - Hugues Matile
- Roche Pharma Research and Early Development, Therapeutic Modalities, Roche Innovation Center Basel, F.Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Hongli Hu
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305, USA.,Department of Structural Biology, Stanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305, USA
| | - Daniel Hilger
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305, USA
| | - Gebhard F X Schertler
- Laboratory of Biomolecular Research, Paul Scherrer Institute, 5232, Villigen, Switzerland
| | - Aashish Manglik
- Department of Pharmaceutical Chemistry, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94143, USA.,Department of Anesthesia and Perioperative Care, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94143, USA
| | - Georgios Skiniotis
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305, USA.,Department of Structural Biology, Stanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305, USA
| | - Roger J P Dawson
- Roche Pharma Research and Early Development, Therapeutic Modalities, Roche Innovation Center Basel, F.Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Brian K Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, CA, 94305, USA.
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11
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Koehl A, Hu H, Maeda S, Zhang Y, Qu Q, Paggi JM, Latorraca NR, Hilger D, Dawson R, Matile H, Schertler GFX, Granier S, Weis WI, Dror RO, Manglik A, Skiniotis G, Kobilka BK. Structure of the µ-opioid receptor-G i protein complex. Nature 2018; 558:547-552. [PMID: 29899455 PMCID: PMC6317904 DOI: 10.1038/s41586-018-0219-7] [Citation(s) in RCA: 439] [Impact Index Per Article: 73.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Accepted: 05/04/2018] [Indexed: 12/03/2022]
Abstract
The μ-opioid receptor (μOR) is a G-protein-coupled receptor (GPCR) and the target of most clinically and recreationally used opioids. The induced positive effects of analgesia and euphoria are mediated by μOR signalling through the adenylyl cyclase-inhibiting heterotrimeric G protein Gi. Here we present the 3.5 Å resolution cryo-electron microscopy structure of the μOR bound to the agonist peptide DAMGO and nucleotide-free Gi. DAMGO occupies the morphinan ligand pocket, with its N terminus interacting with conserved receptor residues and its C terminus engaging regions important for opioid-ligand selectivity. Comparison of the μOR-Gi complex to previously determined structures of other GPCRs bound to the stimulatory G protein Gs reveals differences in the position of transmembrane receptor helix 6 and in the interactions between the G protein α-subunit and the receptor core. Together, these results shed light on the structural features that contribute to the Gi protein-coupling specificity of the µOR.
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MESH Headings
- Animals
- Binding Sites
- Cryoelectron Microscopy
- Enkephalin, Ala(2)-MePhe(4)-Gly(5)-/pharmacology
- Female
- GTP-Binding Protein alpha Subunits, Gi-Go/chemistry
- GTP-Binding Protein alpha Subunits, Gi-Go/metabolism
- GTP-Binding Protein alpha Subunits, Gi-Go/ultrastructure
- GTP-Binding Protein alpha Subunits, Gs/chemistry
- GTP-Binding Protein alpha Subunits, Gs/metabolism
- Humans
- Ligands
- Mice
- Mice, Inbred BALB C
- Molecular Dynamics Simulation
- Morphinans/chemistry
- Morphinans/metabolism
- Protein Stability/drug effects
- Receptors, Adrenergic, beta-2/chemistry
- Receptors, Adrenergic, beta-2/metabolism
- Receptors, Opioid, mu/agonists
- Receptors, Opioid, mu/chemistry
- Receptors, Opioid, mu/metabolism
- Receptors, Opioid, mu/ultrastructure
- Substrate Specificity
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Affiliation(s)
- Antoine Koehl
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Hongli Hu
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Shoji Maeda
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Yan Zhang
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Qianhui Qu
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Joseph M Paggi
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Naomi R Latorraca
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
- Biophysics Program, Stanford University, Stanford, CA, USA
| | - Daniel Hilger
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Roger Dawson
- Roche Pharma Research and Early Development, Therapeutic Modalities, Roche Innovation Center Basel, F.Hoffmann-La Roche, Basel, Switzerland
| | - Hugues Matile
- Roche Pharma Research and Early Development, Therapeutic Modalities, Roche Innovation Center Basel, F.Hoffmann-La Roche, Basel, Switzerland
| | - Gebhard F X Schertler
- Laboratory of Biomolecular Research, Paul Scherrer Institute, Villigen, Switzerland
- Department of Biology, ETH Zürich, Zürich, Switzerland
| | | | - William I Weis
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Ron O Dror
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
- Biophysics Program, Stanford University, Stanford, CA, USA
| | - Aashish Manglik
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA.
- Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, CA, USA.
| | - Georgios Skiniotis
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
| | - Brian K Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
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12
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Kubacki J, Kajewski D, Goraus J, Szot K, Koehl A, Lenser C, Dittmann R, Szade J. Impact of Fe doping on the electronic structure of SrTiO3 thin films determined by resonant photoemission. J Chem Phys 2018; 148:154702. [DOI: 10.1063/1.5007928] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- J. Kubacki
- A. Chełkowski Institute of Physics, University of Silesia, Katowice 40-007, Poland
- Silesian Center for Education and Interdisciplinary Research, Chorzów, Poland
| | - D. Kajewski
- A. Chełkowski Institute of Physics, University of Silesia, Katowice 40-007, Poland
| | - J. Goraus
- A. Chełkowski Institute of Physics, University of Silesia, Katowice 40-007, Poland
- Silesian Center for Education and Interdisciplinary Research, Chorzów, Poland
| | - K. Szot
- A. Chełkowski Institute of Physics, University of Silesia, Katowice 40-007, Poland
- Peter Grünberg Institut, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - A. Koehl
- Peter Grünberg Institut, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Ch. Lenser
- Peter Grünberg Institut, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - R. Dittmann
- Peter Grünberg Institut, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - J. Szade
- A. Chełkowski Institute of Physics, University of Silesia, Katowice 40-007, Poland
- Silesian Center for Education and Interdisciplinary Research, Chorzów, Poland
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13
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Lindemann J, Hoffmann T, Koehl A, Walz EM, Sommer F. Influence of cooling face masks on nasal air conditioning and nasal geometry. Rhinology 2017; 55:120-125. [PMID: 28029166 DOI: 10.4193/rhin16.212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
INTRODUCTION Nasal geometries and temperature of the nasal mucosa are the primary factors affecting nasal air conditioning. Data on intranasal air conditioning after provoking the trigeminal nerve with a cold stimulus simulating the effects of an arctic condition is still missing. The objective was to investigate the influence of skin cooling face masks on nasal air conditioning, mucosal temperature and nasal geometry. METHODS Standardized in vivo measurements of intranasal air temperature, humidity and mucosal temperature were performed in 55 healthy subjects at defined detection sites before and after wearing a cooling face mask. Measurements of skin temperature, rhinomanometry and acoustic rhinometry were accomplished. RESULTS After wearing the face mask the facial skin temperature was significantly reduced. Intranasal air temperature did not change. Absolute humidity and mucosal temperature increased significantly. The acoustic rhinometric results showed a significant increase of the volumes and the cross-sectional areas. There was no change in nasal airflow. CONCLUSIONS Nasal mucosal temperature, humidity of inhaled air, and volume of the anterior nose increased after application of a cold face mask. The response is mediated by the trigeminal nerve. Increased mucosal temperatures as well as changes in nasal geometries seem to guarantee sufficient steady intranasal nasal air conditioning.
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Affiliation(s)
- J Lindemann
- Department of Otorhinolaryngology, University of Ulm, Ulm, Germany
| | - T Hoffmann
- Department of Otorhinolaryngology, University of Ulm, Ulm, Germany
| | - A Koehl
- Department of Otorhinolaryngology, Hospital of Magdeburg, Magdeburg, Germany
| | - E M Walz
- Department of Otorhinolaryngology, University of Ulm, Ulm, Germany
| | - F Sommer
- Department of Otorhinolaryngology, University of Ulm, Ulm, Germany
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14
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Abstract
The human σ1 receptor is an enigmatic endoplasmic-reticulum-resident transmembrane protein implicated in a variety of disorders including depression, drug addiction, and neuropathic pain. Recently, an additional connection to amyotrophic lateral sclerosis has emerged from studies of human genetics and mouse models. Unlike many transmembrane receptors that belong to large, extensively studied families such as G-protein-coupled receptors or ligand-gated ion channels, the σ1 receptor is an evolutionary 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 σ1 receptor and its regulation by drug-like compounds remain poorly defined. Here we report crystal structures of the human σ1 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 endoplasmic reticulum membrane in cells. This domain includes a cupin-like β-barrel with the ligand-binding site buried at its centre. 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.
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Affiliation(s)
- Hayden R Schmidt
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Sanduo Zheng
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Esin Gurpinar
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Antoine Koehl
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Aashish Manglik
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Andrew C Kruse
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA
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15
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AhYoung AP, Koehl A, Vizcarra CL, Cascio D, Egea PF. Structure of a putative ClpS N-end rule adaptor protein from the malaria pathogen Plasmodium falciparum. Protein Sci 2016; 25:689-701. [PMID: 26701219 DOI: 10.1002/pro.2868] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2015] [Revised: 12/20/2015] [Accepted: 12/21/2015] [Indexed: 01/05/2023]
Abstract
The N-end rule pathway uses an evolutionarily conserved mechanism in bacteria and eukaryotes that marks proteins for degradation by ATP-dependent chaperones and proteases such as the Clp chaperones and proteases. Specific N-terminal amino acids (N-degrons) are sufficient to target substrates for degradation. In bacteria, the ClpS adaptor binds and delivers N-end rule substrates for their degradation upon association with the ClpA/P chaperone/protease. Here, we report the first crystal structure, solved at 2.7 Å resolution, of a eukaryotic homolog of bacterial ClpS from the malaria apicomplexan parasite Plasmodium falciparum (Pfal). Despite limited sequence identity, Plasmodium ClpS is very similar to bacterial ClpS. Akin to its bacterial orthologs, plasmodial ClpS harbors a preformed hydrophobic pocket whose geometry and chemical properties are compatible with the binding of N-degrons. However, while the N-degron binding pocket in bacterial ClpS structures is open and accessible, the corresponding pocket in Plasmodium ClpS is occluded by a conserved surface loop that acts as a latch. Despite the closed conformation observed in the crystal, we show that, in solution, Pfal-ClpS binds and discriminates peptides mimicking bona fide N-end rule substrates. The presence of an apicoplast targeting peptide suggests that Pfal-ClpS localizes to this plastid-like organelle characteristic of all Apicomplexa and hosting most of its Clp machinery. By analogy with the related ClpS1 from plant chloroplasts and cyanobacteria, Plasmodium ClpS likely functions in association with ClpC in the apicoplast. Our findings open new venues for the design of novel anti-malarial drugs aimed at disrupting parasite-specific protein quality control pathways.
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Affiliation(s)
- Andrew P AhYoung
- Department of Biological Chemistry, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
| | - Antoine Koehl
- Department of Biological Chemistry, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
| | - Christina L Vizcarra
- Department of Chemistry and Biochemistry, University of California at Los Angeles, Los Angeles, California
| | - Duilio Cascio
- Department of Energy Institute for Genomics and Proteomics, University of California at Los Angeles, Los Angeles, California
| | - Pascal F Egea
- Department of Biological Chemistry, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California.,Molecular Biology Institute, University of California at Los Angeles, Los Angeles, California
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16
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AhYoung AP, Koehl A, Cascio D, Egea PF. Structural mapping of the ClpB ATPases of Plasmodium falciparum: Targeting protein folding and secretion for antimalarial drug design. Protein Sci 2015; 24:1508-20. [PMID: 26130467 DOI: 10.1002/pro.2739] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 06/24/2015] [Accepted: 06/26/2015] [Indexed: 11/08/2022]
Abstract
Caseinolytic chaperones and proteases (Clp) belong to the AAA+ protein superfamily and are part of the protein quality control machinery in cells. The eukaryotic parasite Plasmodium falciparum, the causative agent of malaria, has evolved an elaborate network of Clp proteins including two distinct ClpB ATPases. ClpB1 and ClpB2 are involved in different aspects of parasitic proteostasis. ClpB1 is present in the apicoplast, a parasite-specific and plastid-like organelle hosting various metabolic pathways necessary for parasite growth. ClpB2 localizes to the parasitophorous vacuole membrane where it drives protein export as core subunit of a parasite-derived protein secretion complex, the Plasmodium Translocon of Exported proteins (PTEX); this process is central to parasite virulence and survival in the human host. The functional associations of these two chaperones with parasite-specific metabolism and protein secretion make them prime drug targets. ClpB proteins function as unfoldases and disaggregases and share a common architecture consisting of four domains-a variable N-terminal domain that binds different protein substrates, followed by two highly conserved catalytic ATPase domains, and a C-terminal domain. Here, we report and compare the first crystal structures of the N terminal domains of ClpB1 and ClpB2 from Plasmodium and analyze their molecular surfaces. Solution scattering analysis of the N domain of ClpB2 shows that the average solution conformation is similar to the crystalline structure. These structures represent the first step towards the characterization of these two malarial chaperones and the reconstitution of the entire PTEX to aid structure-based design of novel anti-malarial drugs.
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Affiliation(s)
- Andrew P AhYoung
- Department of Biological Chemistry, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Antoine Koehl
- Department of Biological Chemistry, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Duilio Cascio
- Department of Energy Institute for Genomics and Proteomics, UCLA, Los Angeles, California
| | - Pascal F Egea
- Department of Biological Chemistry, David Geffen School of Medicine, UCLA, Los Angeles, California.,Molecular Biology Institute, UCLA, Los Angeles, California
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17
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Lyubimov AY, Murray TD, Koehl A, Araci IE, Uervirojnangkoorn M, Zeldin OB, Cohen AE, Soltis SM, Baxter EL, Brewster AS, Sauter NK, Brunger AT, Berger JM. Capture and X-ray diffraction studies of protein microcrystals in a microfluidic trap array. Acta Crystallogr D Biol Crystallogr 2015; 71:928-40. [PMID: 25849403 PMCID: PMC4388268 DOI: 10.1107/s1399004715002308] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Accepted: 02/03/2015] [Indexed: 11/10/2022]
Abstract
X-ray free-electron lasers (XFELs) promise to enable the collection of interpretable diffraction data from samples that are refractory to data collection at synchrotron sources. At present, however, more efficient sample-delivery methods that minimize the consumption of microcrystalline material are needed to allow the application of XFEL sources to a wide range of challenging structural targets of biological importance. Here, a microfluidic chip is presented in which microcrystals can be captured at fixed, addressable points in a trap array from a small volume (<10 µl) of a pre-existing slurry grown off-chip. The device can be mounted on a standard goniostat for conducting diffraction experiments at room temperature without the need for flash-cooling. Proof-of-principle tests with a model system (hen egg-white lysozyme) demonstrated the high efficiency of the microfluidic approach for crystal harvesting, permitting the collection of sufficient data from only 265 single-crystal still images to permit determination and refinement of the structure of the protein. This work shows that microfluidic capture devices can be readily used to facilitate data collection from protein microcrystals grown in traditional laboratory formats, enabling analysis when cryopreservation is problematic or when only small numbers of crystals are available. Such microfluidic capture devices may also be useful for data collection at synchrotron sources.
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Affiliation(s)
- Artem Y. Lyubimov
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305, USA
- Department of Neurology and Neurological Science, Stanford University, Stanford, CA 94305, USA
- Department of Structural Biology, Stanford University, Stanford, CA 94305, USA
- Department of Photon Science, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Thomas D. Murray
- Biophysics Graduate Group, University of California, Berkeley, CA 94720, USA
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Antoine Koehl
- Department of Structural Biology, Stanford University, Stanford, CA 94305, USA
| | - Ismail Emre Araci
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Monarin Uervirojnangkoorn
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305, USA
- Department of Neurology and Neurological Science, Stanford University, Stanford, CA 94305, USA
- Department of Structural Biology, Stanford University, Stanford, CA 94305, USA
- Department of Photon Science, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Oliver B. Zeldin
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305, USA
- Department of Neurology and Neurological Science, Stanford University, Stanford, CA 94305, USA
- Department of Structural Biology, Stanford University, Stanford, CA 94305, USA
- Department of Photon Science, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Aina E. Cohen
- SLAC National Accelerator Laboratory, Stanford, CA 94305, USA
| | | | | | - Aaron S. Brewster
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Nicholas K. Sauter
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Axel T. Brunger
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305, USA
- Department of Neurology and Neurological Science, Stanford University, Stanford, CA 94305, USA
- Department of Structural Biology, Stanford University, Stanford, CA 94305, USA
- Department of Photon Science, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - James M. Berger
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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18
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Froboese N, Koehl A. [Tumor of the tongue of a male teenager]. Laryngorhinootologie 2014; 93:535-6. [PMID: 24691767 DOI: 10.1055/s-0034-1370935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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