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Editorial
. 2022 Apr 21:11:e78549.
doi: 10.7554/eLife.78549.

Exploring the conformational diversity of proteins

Avner Schlessinger  1 , Massimiliano Bonomi  2
Affiliations
Editorial

Exploring the conformational diversity of proteins

Avner Schlessinger et al. Elife. .

Abstract

An artificial intelligence-based method can predict distinct conformational states of membrane transporters and receptors.

Keywords: G-protein coupled receptors; artificial intelligence; conformational dynamics; machine learning; molecular biophysics; none; protein structure prediction; structural biology; transmembrane protein; transporters.

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Conflict of interest statement

AS, MB No competing interests declared

Figures

Figure 1.
Figure 1.. Conformational changes of the alanine-serine-cysteine transporter 2 (ASCT2).
An artificial intelligence-based programme, called AF2, can predict the conformational diversity of membrane proteins, such as ASCT2, by modifying the depth of the input multiple sequence alignment. Shown are the cryo-electron microscopy structures of ASCT2 in conformations facing inside (blue) and outside of the cell (yellow). ASCT2 uses an elevator-type alternating access mechanism to transport molecules, which involves a change in the relative orientation of the scaffold (dark tones) and transport domains (light tones) of the protein.
See this image and copyright information in PMC

Comment on

References

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