1. Structural Biology and Molecular Biophysics

A CLC-ec1 mutant reveals global conformational change and suggests a unifying mechanism for the Cl–/H+ transport cycle

  1. Tanmay S Chavan
  2. Ricky C Cheng
  3. Tao Jiang
  4. Irimpan I Mathews
  5. Richard A Stein
  6. Antoine Koehl
  7. Hassane S Mchaourab
  8. Emad Tajkhorshid  Is a corresponding author
  9. Merritt Maduke  Is a corresponding author
  1. Stanford University School of Medicine, United States
  2. University of Illinois at Urbana-Champaign, United States
  3. Stanford University, United States
  4. Vanderbilt University, United States
https://doi.org/10.7554/eLife.53479
Share this article
Cite this article
  1. Tanmay S Chavan
  2. Ricky C Cheng
  3. Tao Jiang
  4. Irimpan I Mathews
  5. Richard A Stein
  6. Antoine Koehl
  7. Hassane S Mchaourab
  8. Emad Tajkhorshid
  9. Merritt Maduke
(2020)
A CLC-ec1 mutant reveals global conformational change and suggests a unifying mechanism for the Cl–/H+ transport cycle
eLife 9:e53479.
https://doi.org/10.7554/eLife.53479
  2. Download BibTeX
  3. Download .RIS

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.

Data availability

Diffraction data have been deposited in PDB under accession code 6V2J

The following data sets were generated

Article and author information

Author details

  1. Tanmay S Chavan

    Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Ricky C Cheng

    Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. 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
    Competing interests
    The authors declare that no competing interests exist.

  4. Irimpan I Mathews

    Stanford Synchrotron Radiation Lightsource, Stanford University, Menlo Park, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. Richard A Stein

    Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Antoine Koehl

    Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Hassane S Mchaourab

    Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Emad Tajkhorshid

    Department of Biochemistry; Center for Biophysics and Quantitative Biology; 5NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
    For correspondence
    tajkhors@illinois.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8434-1010

  9. Merritt Maduke

    Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, United States
    For correspondence
    maduke@stanford.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7787-306X

Funding

National Institutes of Health (GM113195)

  • Hassane S Mchaourab
  • Emad Tajkhorshid
  • Merritt Maduke

American Heart Association (17POST33670553)

  • Tanmay S Chavan

U.S. Department of Energy (DE-AC02-06CH11357)

  • Antoine Koehl

National Institutes of Health (P41GM103393)

  • Irimpan I Mathews

Blue Waters at National Center for Supercomputing Applications

  • Tao Jiang

Extreme Science and Engineering Discovery Environment (MCA06N060)

  • Emad Tajkhorshid

National Institutes of Health (P41-GM104601)

  • Emad Tajkhorshid

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Chavan et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,862
    views
  • 427
    downloads
  • 39
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Tanmay S Chavan
  2. Ricky C Cheng
  3. Tao Jiang
  4. Irimpan I Mathews
  5. Richard A Stein
  6. Antoine Koehl
  7. Hassane S Mchaourab
  8. Emad Tajkhorshid
  9. Merritt Maduke
(2020)
A CLC-ec1 mutant reveals global conformational change and suggests a unifying mechanism for the Cl–/H+ transport cycle
eLife 9:e53479.
https://doi.org/10.7554/eLife.53479

Share this article

https://doi.org/10.7554/eLife.53479

Categories and tags

Research organism

Further reading

    1. Structural Biology and Molecular Biophysics

    Distinct activation mechanisms of CXCR4 and ACKR3 revealed by single-molecule analysis of their conformational landscapes

    Christopher T Schafer, Raymond F Pauszek III ... David P Millar
    Research Article

    The canonical chemokine receptor CXCR4 and atypical receptor ACKR3 both respond to CXCL12 but induce different effector responses to regulate cell migration. While CXCR4 couples to G proteins and directly promotes cell migration, ACKR3 is G-protein-independent and scavenges CXCL12 to regulate extracellular chemokine levels and maintain CXCR4 responsiveness, thereby indirectly influencing migration. The receptors also have distinct activation requirements. CXCR4 only responds to wild-type CXCL12 and is sensitive to mutation of the chemokine. By contrast, ACKR3 recruits GPCR kinases (GRKs) and β-arrestins and promiscuously responds to CXCL12, CXCL12 variants, other peptides and proteins, and is relatively insensitive to mutation. To investigate the role of conformational dynamics in the distinct pharmacological behaviors of CXCR4 and ACKR3, we employed single-molecule FRET to track discrete conformational states of the receptors in real-time. The data revealed that apo-CXCR4 preferentially populates a high-FRET inactive state, while apo-ACKR3 shows little conformational preference and high transition probabilities among multiple inactive, intermediate and active conformations, consistent with its propensity for activation. Multiple active-like ACKR3 conformations are populated in response to agonists, compared to the single CXCR4 active-state. This and the markedly different conformational landscapes of the receptors suggest that activation of ACKR3 may be achieved by a broader distribution of conformational states than CXCR4. Much of the conformational heterogeneity of ACKR3 is linked to a single residue that differs between ACKR3 and CXCR4. The dynamic properties of ACKR3 may underly its inability to form productive interactions with G proteins that would drive canonical GPCR signaling.

    1. Immunology and Inflammation
    2. Structural Biology and Molecular Biophysics

    Load-based divergence in the dynamic allostery of two TCRs recognizing the same pMHC

    Ana Cristina Chang-Gonzalez, Aoi Akitsu ... Wonmuk Hwang
    Research Advance

    Increasing evidence suggests that mechanical load on the αβ T-cell receptor (TCR) is crucial for recognizing the antigenic peptide-bound major histocompatibility complex (pMHC) molecule. Our recent all-atom molecular dynamics (MD) simulations revealed that the inter-domain motion of the TCR is responsible for the load-induced catch bond behavior of the TCR-pMHC complex and peptide discrimination (Chang-Gonzalez et al., 2024). To further examine the generality of the mechanism, we perform all-atom MD simulations of the B7 TCR under different conditions for comparison with our previous simulations of the A6 TCR. The two TCRs recognize the same pMHC and have similar interfaces with pMHC in crystal structures. We find that the B7 TCR-pMHC interface stabilizes under ∼15 pN load using a conserved dynamic allostery mechanism that involves the asymmetric motion of the TCR chassis. However, despite forming comparable contacts with pMHC as A6 in the crystal structure, B7 has fewer high-occupancy contacts with pMHC and exhibits higher mechanical compliance during the simulation. These results indicate that the dynamic allostery common to the TCRαβ chassis can amplify slight differences in interfacial contacts into distinctive mechanical responses and nuanced biological outcomes.

    1. Immunology and Inflammation
    2. Structural Biology and Molecular Biophysics

    Ab initio prediction of specific phospholipid complexes and membrane association of HIV-1 MPER antibodies by multi-scale simulations

    Colleen A Maillie, Kiana Golden ... Marco Mravic
    Research Article

    A potent class of HIV-1 broadly neutralizing antibodies (bnAbs) targets the envelope glycoprotein’s membrane proximal exposed region (MPER) through a proposed mechanism where hypervariable loops embed into lipid bilayers and engage headgroup moieties alongside the epitope. We address the feasibility and determinant molecular features of this mechanism using multi-scale modeling. All-atom simulations of 4E10, PGZL1, 10E8, and LN01 docked onto HIV-like membranes consistently form phospholipid complexes at key complementarity-determining region loop sites, solidifying that stable and specific lipid interactions anchor bnAbs to membrane surfaces. Ancillary protein-lipid contacts reveal surprising contributions from antibody framework regions. Coarse-grained simulations effectively capture antibodies embedding into membranes. Simulations estimating protein-membrane interaction strength for PGZL1 variants along an inferred maturation pathway show bilayer affinity is evolved and correlates with neutralization potency. The modeling demonstrated here uncovers insights into lipid participation in antibodies’ recognition of membrane proteins and highlights antibody features to prioritize in vaccine design.