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Determination of the binding mode for anti-inflammatory natural product xanthohumol with myeloid differentiation protein 2

Overview of attention for article published in Drug Design, Development and Therapy, January 2016
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Title
Determination of the binding mode for anti-inflammatory natural product xanthohumol with myeloid differentiation protein 2
Published in
Drug Design, Development and Therapy, January 2016
DOI 10.2147/dddt.s98466
Pubmed ID
Authors

Weitao Fu, Lingfeng Chen, Zhe Wang, Chengwei Zhao, Gaozhi Chen, Xing Liu, Yuanrong Dai, Yuepiao Cai, Chenglong Li, Jianmin Zhou, Guang Liang

Abstract

It is recognized that myeloid differentiation protein 2 (MD-2), a coreceptor of toll-like receptor 4 (TLR4) for innate immunity, plays an essential role in activation of the lipopolysaccharide signaling pathway. MD-2 is known as a neoteric and suitable therapeutical target. Therefore, there is great interest in the development of a potent MD-2 inhibitor for anti-inflammatory therapeutics. Several studies have reported that xanthohumol (XN), an anti-inflammatory natural product from hops and beer, can block the TLR4 signaling by binding to MD-2 directly. However, the interaction between MD-2 and XN remains unknown. Herein, our work aims at characterizing interactions between MD-2 and XN. Using a combination of experimental and theoretical modeling analysis, we found that XN can embed into the hydrophobic pocket of MD-2 and form two stable hydrogen bonds with residues ARG-90 and TYR-102 of MD-2. Moreover, we confirmed that ARG-90 and TYR-102 were two necessary residues during the recognition process of XN binding to MD-2. Results from this study identified the atomic interactions between the MD-2 and XN, which will contribute to future structural design of novel MD-2-targeting molecules for the treatment of inflammatory diseases.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 19%
Researcher 7 17%
Student > Master 6 14%
Student > Doctoral Student 2 5%
Student > Bachelor 2 5%
Other 7 17%
Unknown 10 24%
Readers by discipline Count As %
Chemistry 9 21%
Pharmacology, Toxicology and Pharmaceutical Science 6 14%
Biochemistry, Genetics and Molecular Biology 4 10%
Agricultural and Biological Sciences 4 10%
Neuroscience 2 5%
Other 5 12%
Unknown 12 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 February 2016.
All research outputs
#20,655,488
of 25,371,288 outputs
Outputs from Drug Design, Development and Therapy
#1,437
of 2,268 outputs
Outputs of similar age
#295,035
of 399,662 outputs
Outputs of similar age from Drug Design, Development and Therapy
#57
of 81 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,268 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.