Conserved allosteric inhibition mechanism in SLC1 transporters

  1. Yang Dong
  2. Jiali Wang
  3. Rachel-Ann Garibsingh
  4. Keino Hutchinson
  5. Yueyue Shi
  6. Gilad Eisenberg
  7. Xiaozhen Yu
  8. Avner Schlessinger  Is a corresponding author
  9. Christof Grewer  Is a corresponding author
  1. Binghamton University, United States
  2. Icahn School of Medicine at Mount Sinai, United States

Abstract

Excitatory Amino Acid Transporter 1 (EAAT1) is a plasma-membrane glutamate transporter belonging to the SLC1 family of solute carriers . It plays a key role in neurotransmitter transport and contributes to the regulation of the extracellular glutamate concentration in the mammalian brain. The structure of EAAT1 was determined in complex with UCPH-101, a highly potent and non-competitive inhibitor of EAAT1. Alanine Serine Cysteine Transporter 2 (ASCT2) is a neutral amino acid transporter, which regulates pools of amino acids such as glutamine, serine and alanine between intracellular and extracellular compartments in a Na+ dependent manner. ASCT2 also belongs to the SLC1 family and shares 58% sequence similarity with EAAT1. However, allosteric modulation of ASCT2 via non-competitive inhibitors is unknown. Here we explore the UCPH-101 inhibitory mechanisms of EAAT1 and ASCT2 by using rapid kinetic experiments. Our results show that UCPH-101 slows substrate translocation rather than substrate or Na+ binding, confirming a non-competitive inhibitory mechanism, but only partially inhibits wild-type ASCT2 with relatively low affinity. Guided by computational modeling using ligand docking and molecular dynamics (MD) simulations, we selected two residues involved in UCPH-101/EAAT1 interaction, which were mutated in ASCT2 (F136Y, I237M, F136Y/I237M) in the corresponding positions. We show that in the F136Y/I237M double mutant transporter, 100% of the inhibitory effect of UCPH-101 on anion current could be restored, and the apparent affinity was increased (Ki = 9.3 mM), much closer to the EAAT1 value of 0.6 mM. Finally, we identify a novel non-competitive ASCT2 inhibitor, identified through virtual screening and experimental testing against the allosteric site, further supporting its localization. Together, these data indicate that the mechanism of allosteric modulation is conserved between EAAT1 and ASCT2. Due to the difference in binding site residues between ASCT2 and EAAT1, these results raise the possibility that more potent, and potentially selective inhibitors can be designed that target the ASCT2 allosteric binding site.

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting file. The original, source data files were uploaded as spreadsheets for figures 3-10, Table 1, and Figure supplements 3,4,5,6 and 9. The MD parametrization files for UCPH-101 are also included.

Article and author information

Author details

  1. Yang Dong

    Department of Chemistry, Binghamton University, Binghamton, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jiali Wang

    Department of Chemistry, Binghamton University, Binghamton, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9520-8140
  3. Rachel-Ann Garibsingh

    Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, Ney York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Keino Hutchinson

    Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Yueyue Shi

    Department of Chemistry, Binghamton University, Binghamton, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Gilad Eisenberg

    Department of Chemistry, Binghamton University, Binghamton, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Xiaozhen Yu

    Department of Chemistry, Binghamton University, Binghamton, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Avner Schlessinger

    Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
    For correspondence
    avner.schlessinger@mssm.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4007-7814
  9. Christof Grewer

    Department of Chemistry, Binghamton University, Binghamton, United States
    For correspondence
    cgrewer@binghamton.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8342-9878

Funding

National Institutes of Health (R01 GM108911)

  • Avner Schlessinger
  • Christof Grewer

National Institutes of Health (T32 CA078207)

  • Rachel-Ann Garibsingh

National Institutes of Health (R15 GM135843-01)

  • Christof Grewer

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

Copyright

© 2023, Dong 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

  • 1,293
    views
  • 231
    downloads
  • 9
    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. Yang Dong
  2. Jiali Wang
  3. Rachel-Ann Garibsingh
  4. Keino Hutchinson
  5. Yueyue Shi
  6. Gilad Eisenberg
  7. Xiaozhen Yu
  8. Avner Schlessinger
  9. Christof Grewer
(2023)
Conserved allosteric inhibition mechanism in SLC1 transporters
eLife 12:e83464.
https://doi.org/10.7554/eLife.83464

Share this article

https://doi.org/10.7554/eLife.83464

Further reading

    1. Structural Biology and Molecular Biophysics
    Julia Belyaeva, Matthias Elgeti
    Review Article

    Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure–function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.

    1. Structural Biology and Molecular Biophysics
    Yao Chi Chen, Karen Sargsyan ... Carmay Lim
    Research Article

    Experimental detection of residues critical for protein–protein interactions (PPI) is a time-consuming, costly, and labor-intensive process. Hence, high-throughput PPI-hot spot prediction methods have been developed, but they have been validated using relatively small datasets, which may compromise their predictive reliability. Here, we introduce PPI-hotspotID, a novel method for identifying PPI-hot spots using the free protein structure, and validated it on the largest collection of experimentally confirmed PPI-hot spots to date. We explored the possibility of detecting PPI-hot spots using (i) FTMap in the PPI mode, which identifies hot spots on protein–protein interfaces from the free protein structure, and (ii) the interface residues predicted by AlphaFold-Multimer. PPI-hotspotID yielded better performance than FTMap and SPOTONE, a webserver for predicting PPI-hot spots given the protein sequence. When combined with the AlphaFold-Multimer-predicted interface residues, PPI-hotspotID yielded better performance than either method alone. Furthermore, we experimentally verified several PPI-hotspotID-predicted PPI-hot spots of eukaryotic elongation factor 2. Notably, PPI-hotspotID can reveal PPI-hot spots not obvious from complex structures, including those in indirect contact with binding partners. PPI-hotspotID serves as a valuable tool for understanding PPI mechanisms and aiding drug design. It is available as a web server (https://ppihotspotid.limlab.dnsalias.org/) and open-source code (https://github.com/wrigjz/ppihotspotid/).