Large-scale state-dependent membrane remodeling by a transporter protein

  1. Wenchang Zhou
  2. Giacomo Fiorin
  3. Claudio Anselmi
  4. Hossein Ali Karimi-Varzaneh
  5. Horacio Poblete
  6. Lucy Forrest  Is a corresponding author
  7. José D Faraldo-Gómez  Is a corresponding author
  1. National Heart, Lung and Blood Institute, National Institutes of Health, United States
  2. Children's National Medical Center, United States
  3. National Institute of Neurological Disorders and Stroke, National Institutes of Health, United States

Abstract

That channels and transporters can influence the membrane morphology is increasingly recognized. Less appreciated is that the extent and free-energy cost of these deformations likely varies among different functional states of a protein, and thus, that they might contribute significantly to defining its mechanism. We consider the trimeric Na+-aspartate symporter GltPh, a homolog of an important class of neurotransmitter transporters, whose mechanism entails one of the most drastic structural changes known. Molecular simulations indicate that when the protomers become inward-facing, they cause deep, long-ranged, and yet mutually-independent membrane deformations. Using a novel simulation methodology, we estimate that the free-energy cost of this membrane perturbation is in the order of 6-7 kcal/mol per protomer. Compensating free-energy contributions within the protein or its environment must thus stabilize this inward-facing conformation for the transporter to function. We discuss these striking results in the context of existing experimental observations for this and other transporters.

Data availability

Input and output files for 1 (out of 3) replica of each simulation system/condition in our study have been uploaded to Zenodo, a public repository free of charge, and is available at the DOI 10.5281/zenodo.3558957.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Wenchang Zhou

    Theoretical Molecular Biophysics Section, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0397-1032
  2. Giacomo Fiorin

    Theoretical Molecular Biophysics Section, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  3. Claudio Anselmi

    Research Center for Genetic Medicine, Children's National Medical Center, Bethesda, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3017-5085
  4. Hossein Ali Karimi-Varzaneh

    Computational Structural Biology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  5. Horacio Poblete

    Theoretical Molecular Biophysics Section, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  6. Lucy Forrest

    Computational Structural Biology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States
    For correspondence
    lucy.forrest@nih.gov
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1855-7985
  7. José D Faraldo-Gómez

    Theoretical Molecular Biophysics Laboratory, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    For correspondence
    jose.faraldo@nih.gov
    Competing interests
    José D Faraldo-Gómez, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7224-7676

Funding

National Heart, Lung, and Blood Institute

  • Wenchang Zhou
  • Giacomo Fiorin
  • Claudio Anselmi
  • José D Faraldo-Gómez

National Institute of Neurological Disorders and Stroke

  • Hossein Ali Karimi-Varzaneh
  • Horacio Poblete
  • Lucy Forrest

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

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Metrics

  • 3,380
    views
  • 455
    downloads
  • 44
    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. Wenchang Zhou
  2. Giacomo Fiorin
  3. Claudio Anselmi
  4. Hossein Ali Karimi-Varzaneh
  5. Horacio Poblete
  6. Lucy Forrest
  7. José D Faraldo-Gómez
(2019)
Large-scale state-dependent membrane remodeling by a transporter protein
eLife 8:e50576.
https://doi.org/10.7554/eLife.50576

Share this article

https://doi.org/10.7554/eLife.50576

Further reading

    1. Structural Biology and Molecular Biophysics
    Mart GF Last, Leoni Abendstein ... Thomas H Sharp
    Tools and Resources

    Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible, and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available on GitHub. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature segmentations of cellular architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at aiscryoet.org, we hope that Ais will help accelerate research and dissemination of data involving cryoET.

    1. Structural Biology and Molecular Biophysics
    Sneha Menon, Subinoy Adhikari, Jagannath Mondal
    Research Article

    The mis-folding and aggregation of intrinsically disordered proteins (IDPs) such as α-synuclein (αS) underlie the pathogenesis of various neurodegenerative disorders. However, targeting αS with small molecules faces challenges due to the lack of defined ligand-binding pockets in its disordered structure. Here, we implement a deep artificial neural network-based machine learning approach, which is able to statistically distinguish the fuzzy ensemble of conformational substates of αS in neat water from those in aqueous fasudil (small molecule of interest) solution. In particular, the presence of fasudil in the solvent either modulates pre-existing states of αS or gives rise to new conformational states of αS, akin to an ensemble-expansion mechanism. The ensembles display strong conformation-dependence in residue-wise interaction with the small molecule. A thermodynamic analysis indicates that small-molecule modulates the structural repertoire of αS by tuning protein backbone entropy, however entropy of the water remains unperturbed. Together, this study sheds light on the intricate interplay between small molecules and IDPs, offering insights into entropic modulation and ensemble expansion as key biophysical mechanisms driving potential therapeutics.