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The transport of solutes across the cell membrane is essential for metabolic processes, like maintaining cell size and volume, generating the action potential, exchanging nutrients and gases, etc. Membrane transport can be either passive or active. It can be simple diffusion, facilitated, or mediated transport aided by transport proteins such as transporters and channels.
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Related Experiment Video

Updated: Dec 14, 2025

Author Spotlight: Expression and Purification of Human Solute Carrier Transporters Using Codon-Optimized Genes
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A substrate-based ontology for human solute carriers.

Eva Meixner1, Ulrich Goldmann1, Vitaly Sedlyarov1

  • 1CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.

Molecular Systems Biology
|July 23, 2020
PubMed
Summary

This study manually annotates solute carrier (SLC) proteins, revealing ~30% remain functionally orphan. This resource aids in identifying substrates for uncharacterized SLC transporters.

Keywords:
SLCsannotationde-orphanizationontologysolute carriers

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Area of Science:

  • Molecular Biology
  • Genomics
  • Biochemistry

Background:

  • Solute carriers (SLCs) are a vast family of transmembrane transporters crucial for biological functions.
  • Many SLCs are poorly characterized, lacking identified substrates, hindering research and drug development.
  • A lack of structured chemical annotation limits large-scale de-orphanization efforts.

Purpose of the Study:

  • To create a comprehensive manual literature-based annotation of human SLCs.
  • To characterize substrates, transport mechanisms, ion coupling, and subcellular localization for SLCs.
  • To facilitate the identification of substrates for orphan SLC transporters.

Main Methods:

  • Manual literature review and annotation of 446 human SLCs.
  • Development of a substrate-based ontology for SLCs.
  • Application of machine learning to predict potential SLC substrates.

Main Results:

  • Annotation confirmed ~30% of human SLCs are functionally orphan with no known substrates.
  • Analysis identified SLC-specific responses to external perturbations using transcriptomic data.
  • A machine-learning model successfully predicted potential substrates for several orphan SLCs.

Conclusions:

  • The developed SLC annotation and ontology provide a critical resource for understanding transporter function.
  • This work advances the de-orphanization of SLCs and offers insights into their biological roles.
  • The findings will support future research utilizing large biological datasets and transporter studies.