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Cited by 218

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Functional diversity of ankyrin repeats in microbial proteins

Open access
Al-Khodor, Souhaila, Price, Christopher T., Kalia, Awdhesh, Abu Kwaik, Yousef·2010·Trends in Microbiology

Abstract

Summary The ankyrin repeat (ANK) is the most common protein-protein interaction motif in nature and predominantly found in eukaryotic proteins. The genome sequencing of various pathogenic or symbiotic bacteria and eukaryotic viruses identified numerous genes encoding ANK-containing proteins that were proposed to have been acquired from eukaryotes by horizontal gene transfer. However, the recent discovery of additional ANK-containing proteins encoded in the genomes of archaea and free-living bacteria suggests either a more ancient origin of the ANK motif or multiple convergent evolution events. Many bacterial pathogens employ various types of secretion systems to deliver ANK-containing proteins into eukaryotic cells where they mimic or manipulate various host functions. Understanding the molecular and biochemical functions of this family of proteins will enhance our understanding of important host-microbe interactions.

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Metadata

Authors
Al-Khodor, S., Price, C. T., Kalia, A., & Abu Kwaik, Y.
Venue
Trends in Microbiology
Publisher
Elsevier BV
Published
2010-03
Volume
18
Issue
3
Pages
132-139
ISSN
0966-842X (ISSN-L)
OpenAlex
W2081730917
Cited by
218
References
3
FWCI
0.87
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Functional diversity of ankyrin repeats in microbial proteins. https://app.cochat.ai/papers/10.1016/j.tim.2009.11.004
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Al-Khodor, S., Price, C. T., Kalia, A., & Abu Kwaik, Y. (2010). Functional diversity of ankyrin repeats in microbial proteins. Trends in Microbiology. https://doi.org/10.1016/j.tim.2009.11.004

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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.