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Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E./
作者:	Telehany, Stephen.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	54 p.
附註:	Source: Masters Abstracts International, Volume: 82-09.
Contained By:	Masters Abstracts International82-09.
標題:	Microbiology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28260755
ISBN:	9798582506720

Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E.
Telehany, Stephen.

Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 54 p.

Source: Masters Abstracts International, Volume: 82-09.

Thesis (M.S.)--State University of New York at Stony Brook, 2020.

This item must not be sold to any third party vendors.

The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne pathogen which can cause severe developmental defects. The primary goal of this work was identification of small molecules as potential ZIKV inhibitors which target the viral envelope glycoprotein (ZIKV E) involved in membrane fusion and viral entry. A homology model of ZIKV E containing the small molecule B-octylglucoside (BOG) was constructed, based on an analogous x-ray structure from Dengue virus, and >4M commercially available compounds were computationally screened using the program DOCK6. A key feature of the screen involved use of similarity-based scoring to identify inhibitor candidates which make similar interaction energy patterns (molecular footprints) as the BOG reference. Fifty-three prioritized compounds underwent experimental testing using cytotoxicity, cell viability, and tissue culture infectious dose 50% (TCID50) assays. Encouragingly, relative to a known control (NITD008), 6 compounds were active in both the cell viability and TCID50 infectivity assay, and they showed activity in a third caspase activity assay. In particular, compounds 8 and 15 (tested at 25 uM), and compound 43 (tested at 10 uM), appeared to provide significant protection to infected cells, indicative of anti-ZIKV activity. Overall, the study highlights how similarity-based scoring can be leveraged to computationally identify potential ZIKV E inhibitors that mimic a known reference (in this case BOG), and the experimentally-verified hits provide a strong starting point for further refinement and optimization efforts.

ISBN: 9798582506720Subjects--Topical Terms:

536250
Microbiology.
Subjects--Index Terms:

Design

Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E.
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300 $a 54 p.
500 $a Source: Masters Abstracts International, Volume: 82-09.
500 $a Advisor: Rizzo, Robert C.
502 $a Thesis (M.S.)--State University of New York at Stony Brook, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne pathogen which can cause severe developmental defects. The primary goal of this work was identification of small molecules as potential ZIKV inhibitors which target the viral envelope glycoprotein (ZIKV E) involved in membrane fusion and viral entry. A homology model of ZIKV E containing the small molecule B-octylglucoside (BOG) was constructed, based on an analogous x-ray structure from Dengue virus, and >4M commercially available compounds were computationally screened using the program DOCK6. A key feature of the screen involved use of similarity-based scoring to identify inhibitor candidates which make similar interaction energy patterns (molecular footprints) as the BOG reference. Fifty-three prioritized compounds underwent experimental testing using cytotoxicity, cell viability, and tissue culture infectious dose 50% (TCID50) assays. Encouragingly, relative to a known control (NITD008), 6 compounds were active in both the cell viability and TCID50 infectivity assay, and they showed activity in a third caspase activity assay. In particular, compounds 8 and 15 (tested at 25 uM), and compound 43 (tested at 10 uM), appeared to provide significant protection to infected cells, indicative of anti-ZIKV activity. Overall, the study highlights how similarity-based scoring can be leveraged to computationally identify potential ZIKV E inhibitors that mimic a known reference (in this case BOG), and the experimentally-verified hits provide a strong starting point for further refinement and optimization efforts.
590 $a School code: 0771.
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653 $a Modelling
653 $a Zika
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