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Molecular Docking and Molecular Dynamics Simulation Studies to Predict Flavonoid Binding on the Surface of DENV2 E Protein

Overview of attention for article published in Interdisciplinary Sciences: Computational Life Sciences, March 2016
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Title
Molecular Docking and Molecular Dynamics Simulation Studies to Predict Flavonoid Binding on the Surface of DENV2 E Protein
Published in
Interdisciplinary Sciences: Computational Life Sciences, March 2016
DOI 10.1007/s12539-016-0157-8
Pubmed ID
Authors

Nurul Azira Ismail, Siti Azma Jusoh

Abstract

Dengue infections are currently estimated to be 390 million cases annually. Yet, there is no vaccine or specific therapy available. Envelope glycoprotein E (E protein) of DENV mediates viral attachment and entry into the host cells. Several flavonoids have been shown to inhibit HIV-1 and hepatitis C virus entry during the virus-host membrane fusion. In this work, molecular docking method was employed to predict the binding of nine flavonoids (baicalin, baicalein, EGCG, fisetin, glabranine, hyperoside, ladanein, quercetin and flavone) to the soluble ectodomain of DENV type 2 (DENV2) E protein. Interestingly, eight flavonoids were found to dock into the same binding pocket located between the domain I and domain II of different subunits of E protein. Consistent docking results were observed not only for the E protein structures of the DENV2-Thai and DENV2-Malaysia (a homology model) but also for the E protein structures of tick-borne encephalitis virus and Japanese encephalitis virus. In addition, molecular dynamics simulations were performed to further evaluate the interaction profile of the docked E protein-flavonoid complexes. Ile4, Gly5, Asp98, Gly100 and Val151 residues of the DENV2-My E protein that aligned to the same residues in the DENV2-Thai E protein form consistent hydrogen bond interactions with baicalein, quercetin and EGCG during the simulations. This study demonstrates flavonoids potentially form interactions with the E protein of DENV2.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 116 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 20 17%
Researcher 16 14%
Student > Ph. D. Student 15 13%
Student > Master 9 8%
Lecturer 4 3%
Other 18 15%
Unknown 35 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 16%
Chemistry 13 11%
Agricultural and Biological Sciences 11 9%
Medicine and Dentistry 6 5%
Pharmacology, Toxicology and Pharmaceutical Science 6 5%
Other 19 16%
Unknown 43 37%
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 15 March 2016.
All research outputs
#18,447,592
of 22,856,968 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#165
of 294 outputs
Outputs of similar age
#218,049
of 299,532 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#5
of 10 outputs
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So far Altmetric has tracked 294 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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