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The GxxxG motif: A framework for transmembrane helix-helix association

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Russ, William P, Engelman, Donald M·2000·Journal of Molecular Biology

Abstract

In order to identify strong transmembrane helix packing motifs, we have selected transmembrane domains exhibiting high-affinity homo-oligomerization from a randomized sequence library based on the right-handed dimerization motif of glycophorin A. Sequences were isolated using the TOXCAT system, which measures transmembrane helix-helix association in the Escherichia coli inner membrane. Strong selection was applied to a large range of sequences ( approximately 10(7) possibilities) and resulted in the identification of sequence patterns that mediate high-affinity helix-helix association. The most frequent motif isolated, GxxxG, occurs in over 80% of the isolates. Additional correlations suggest that flanking residues act in concert with the GxxxG motif, and that size complementarity is maintained at the interface, consistent with the idea that the identified sequence patterns represent packing motifs. The convergent identification of similar sequence patterns from an analysis of the transmembrane domains in the SwissProt sequence database suggests that these packing motifs are frequently utilized in naturally occurring helical membrane proteins.

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Metadata

Authors
Russ, W. P., & Engelman, D. M.
Venue
Journal of Molecular Biology
Publisher
Elsevier BV
Published
2000-02
Volume
296
Issue
3
Pages
911-919
ISSN
0022-2836 (ISSN-L)
OpenAlex
W1994373739
Cited by
936
References
0
FWCI
10.25
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: The GxxxG motif: A framework for transmembrane helix-helix association. https://app.cochat.ai/papers/10.1006/jmbi.1999.3489
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Russ, W. P., & Engelman, D. M. (2000). The GxxxG motif: A framework for transmembrane helix-helix association. Journal of Molecular Biology. https://doi.org/10.1006/jmbi.1999.3489

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.