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Updated: Feb 18, 2026

Characterization of Membrane Transporters by Heterologous Expression in E. coli and Production of Membrane Vesicles
Published on: December 31, 2019
Structural basis for xenobiotic extrusion by eukaryotic MATE transporter.
Hirotake Miyauchi1, Satomi Moriyama2, Tsukasa Kusakizako1
1Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan.
Researchers determined the crystal structure of a plant Multidrug and Toxic Compound Extrusion (MATE) transporter. This reveals a mechanism involving protonation and hydrogen bonding for xenobiotic transport, aiding drug development.
Area of Science:
- Structural biology
- Molecular biology
- Biochemistry
Background:
- Multidrug and Toxic Compound Extrusion (MATE) transporters are crucial for cellular homeostasis, exporting xenobiotics and drugs.
- While human MATEs handle xenobiotics and clinical drugs, plant MATEs are involved in aluminum tolerance and secondary metabolite transport.
Purpose of the Study:
- To elucidate the structure and transport mechanism of eukaryotic MATE transporters.
- To provide insights for improving the pharmacokinetics of clinical drugs.
Main Methods:
- X-ray crystallography to determine the structure of the Arabidopsis thaliana MATE transporter at 2.6 Å resolution.
- Structure-based mutational analysis to investigate the function of conserved residues.
Main Results:
- The crystal structure reveals a conserved hydrogen-bonding network in the carboxy-terminal lobe (C-lobe) involving acidic residues.
- Protonation of these acidic residues induces a hydrogen-bonding network, leading to structural changes in transmembrane helix 7.
- This mechanism is proposed to be central to the transport function of eukaryotic MATE transporters.
Conclusions:
- The study provides the first crystal structure of a eukaryotic MATE transporter.
- The findings elucidate a novel transport mechanism involving protonation-induced conformational changes.
- This structural and mechanistic understanding is vital for optimizing drug pharmacokinetics.
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