Abstract

The serotonin transporter (SERT/SLC6A4) is arguably the most extensively studied solute carrier (SLC). During its eponymous action - i.e., the retrieval of serotonin from the extracellular space - SERT undergoes a conformational cycle. Typical inhibitors (antidepressant drugs and cocaine), partial and full substrates (amphetamines and their derivatives) and atypical inhibitors (ibogaine analogues) bind preferentially to different states in this cycle. This results in competitive or non-competitive transport inhibition. Here, we explored the action of N-formyl-1,3-bis (3,4-methylenedioxyphenyl)-prop-2-yl-amine (ECSI#6) on SERT: inhibition of serotonin uptake by ECSI#6 was enhanced with increasing serotonin concentration. Conversely, the KM for serotonin was lowered by augmenting ECSI#6. ECSI#6 bound with low affinity to the outward-facing state of SERT but with increased affinity to a potassium-bound state. Electrophysiological recordings showed that ECSI#6 preferentially interacted with the inward-facing state. Kinetic modeling recapitulated the experimental data and verified that uncompetitive inhibition arose from preferential binding of ECSI#6 to the K+-bound, inward-facing conformation of SERT. This binding mode predicted a pharmacochaperoning action of ECSI#6, which was confirmed by examining its effect on the folding-deficient mutant SERT-PG601,602AA: preincubation of HEK293 cells with ECSI#6 restored export of SERT-PG601,602AA from the endoplasmic reticulum and substrate transport. Similarly, in transgenic flies, the administration of ECSI#6 promoted the delivery of SERT-PG601,602AA to the presynaptic specialization of serotonergic neurons. To the best of our knowledge, ECSI#6 is the first example of an uncompetitive SLC inhibitor. Pharmacochaperones endowed with the binding mode of ECSI#6 are attractive, because they can rescue misfolded transporters at concentrations, which cause modest transport inhibition.

Data availability

We uploaded original data onto Dyrad.The generated DOI is: doi.org/10.5061/dryad.fqz612jvz.

The following data sets were generated

Article and author information

Author details

  1. Shreyas Bhat

    Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  2. Ali El-Kasaby

    Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  3. Ameya Kasture

    Department of Neurobiology, University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  4. Danila Boytsov

    Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  5. Julian B Reichelt

    Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  6. Thomas Hummel

    Department of Neurobiology, University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8108-9307
  7. Sonja Sucic

    Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  8. Christian Pifl

    Center for Brain Research, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  9. Michael Freissmuth

    Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  10. Walter Sandtner

    Institute of Pharmacology, Medical University of Vienna, Vienna, Austria
    For correspondence
    walter.sandtner@meduniwien.ac.at
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3637-260X

Funding

Austrian Science Fund (P31813)

  • Walter Sandtner

Austrian Science Fund (P31255-B27)

  • Sonja Sucic

Vienna Science and Technology Fund (LSC17-026)

  • Michael Freissmuth

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

Copyright

© 2023, Bhat 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

  • 1,945
    views
  • 318
    downloads
  • 4
    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. Shreyas Bhat
  2. Ali El-Kasaby
  3. Ameya Kasture
  4. Danila Boytsov
  5. Julian B Reichelt
  6. Thomas Hummel
  7. Sonja Sucic
  8. Christian Pifl
  9. Michael Freissmuth
  10. Walter Sandtner
(2023)
A mechanism of uncompetitive inhibition of the serotonin transporter
eLife 12:e82641.
https://doi.org/10.7554/eLife.82641

Share this article

https://doi.org/10.7554/eLife.82641

Further reading

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Joar Esteban Pinto Torres, Mathieu Claes ... Yann G-J Sterckx
    Research Article

    African trypanosomes are the causative agents of neglected tropical diseases affecting both humans and livestock. Disease control is highly challenging due to an increasing number of drug treatment failures. African trypanosomes are extracellular, blood-borne parasites that mainly rely on glycolysis for their energy metabolism within the mammalian host. Trypanosomal glycolytic enzymes are therefore of interest for the development of trypanocidal drugs. Here, we report the serendipitous discovery of a camelid single-domain antibody (sdAb aka Nanobody) that selectively inhibits the enzymatic activity of trypanosomatid (but not host) pyruvate kinases through an allosteric mechanism. By combining enzyme kinetics, biophysics, structural biology, and transgenic parasite survival assays, we provide a proof-of-principle that the sdAb-mediated enzyme inhibition negatively impacts parasite fitness and growth.

    1. Structural Biology and Molecular Biophysics
    Manming Xu, Sarath Chandra Dantu ... Shozeb Haider
    Research Article

    The relationship between protein dynamics and function is essential for understanding biological processes and developing effective therapeutics. Functional sites within proteins are critical for activities such as substrate binding, catalysis, and structural changes. Existing computational methods for the predictions of functional residues are trained on sequence, structural, and experimental data, but they do not explicitly model the influence of evolution on protein dynamics. This overlooked contribution is essential as it is known that evolution can fine-tune protein dynamics through compensatory mutations either to improve the proteins’ performance or diversify its function while maintaining the same structural scaffold. To model this critical contribution, we introduce DyNoPy, a computational method that combines residue coevolution analysis with molecular dynamics simulations, revealing hidden correlations between functional sites. DyNoPy constructs a graph model of residue–residue interactions, identifies communities of key residue groups, and annotates critical sites based on their roles. By leveraging the concept of coevolved dynamical couplings—residue pairs with critical dynamical interactions that have been preserved during evolution—DyNoPy offers a powerful method for predicting and analysing protein evolution and dynamics. We demonstrate the effectiveness of DyNoPy on SHV-1 and PDC-3, chromosomally encoded β-lactamases linked to antibiotic resistance, highlighting its potential to inform drug design and address pressing healthcare challenges.