Cargando…
Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E
[Image: see text] The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne pathogen that can cause severe developmental defects. The primary goal of this work was identification of small molecules as potential ZIKV inhibitors that target the viral envelope glycop...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical Society
2020
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598728/ https://www.ncbi.nlm.nih.gov/pubmed/32876433 http://dx.doi.org/10.1021/acs.biochem.0c00458 |
_version_ | 1783602696047034368 |
---|---|
author | Telehany, Stephen M. Humby, Monica S. McGee, T. Dwight Riley, Sean P. Jacobs, Amy Rizzo, Robert C. |
author_facet | Telehany, Stephen M. Humby, Monica S. McGee, T. Dwight Riley, Sean P. Jacobs, Amy Rizzo, Robert C. |
author_sort | Telehany, Stephen M. |
collection | PubMed |
description | [Image: see text] The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne pathogen that can cause severe developmental defects. The primary goal of this work was identification of small molecules as potential ZIKV inhibitors that target the viral envelope glycoprotein (ZIKV E) involved in membrane fusion and viral entry. A homology model of ZIKV E containing the small molecule β-octyl glucoside (BOG) was constructed, on the basis of an analogous X-ray structure from dengue virus, and >4 million commercially available compounds were computationally screened using the program DOCK6. A key feature of the screen involved the use of similarity-based scoring to identify inhibitor candidates that 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), six compounds were active in both the cell viability assay and the TCID50 infectivity assay, and they showed activity in a third caspase activity assay. In particular, compounds 8 and 15 (tested at 25 μM) and compound 43 (tested at 10 μM) 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. |
format | Online Article Text |
id | pubmed-7598728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American
Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-75987282020-11-02 Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E Telehany, Stephen M. Humby, Monica S. McGee, T. Dwight Riley, Sean P. Jacobs, Amy Rizzo, Robert C. Biochemistry [Image: see text] The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne pathogen that can cause severe developmental defects. The primary goal of this work was identification of small molecules as potential ZIKV inhibitors that target the viral envelope glycoprotein (ZIKV E) involved in membrane fusion and viral entry. A homology model of ZIKV E containing the small molecule β-octyl glucoside (BOG) was constructed, on the basis of an analogous X-ray structure from dengue virus, and >4 million commercially available compounds were computationally screened using the program DOCK6. A key feature of the screen involved the use of similarity-based scoring to identify inhibitor candidates that 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), six compounds were active in both the cell viability assay and the TCID50 infectivity assay, and they showed activity in a third caspase activity assay. In particular, compounds 8 and 15 (tested at 25 μM) and compound 43 (tested at 10 μM) 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. American Chemical Society 2020-09-02 2020-10-06 /pmc/articles/PMC7598728/ /pubmed/32876433 http://dx.doi.org/10.1021/acs.biochem.0c00458 Text en This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Telehany, Stephen M. Humby, Monica S. McGee, T. Dwight Riley, Sean P. Jacobs, Amy Rizzo, Robert C. Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E |
title | Identification of Zika Virus Inhibitors Using Homology
Modeling and Similarity-Based Screening to Target Glycoprotein E |
title_full | Identification of Zika Virus Inhibitors Using Homology
Modeling and Similarity-Based Screening to Target Glycoprotein E |
title_fullStr | Identification of Zika Virus Inhibitors Using Homology
Modeling and Similarity-Based Screening to Target Glycoprotein E |
title_full_unstemmed | Identification of Zika Virus Inhibitors Using Homology
Modeling and Similarity-Based Screening to Target Glycoprotein E |
title_short | Identification of Zika Virus Inhibitors Using Homology
Modeling and Similarity-Based Screening to Target Glycoprotein E |
title_sort | identification of zika virus inhibitors using homology
modeling and similarity-based screening to target glycoprotein e |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598728/ https://www.ncbi.nlm.nih.gov/pubmed/32876433 http://dx.doi.org/10.1021/acs.biochem.0c00458 |
work_keys_str_mv | AT telehanystephenm identificationofzikavirusinhibitorsusinghomologymodelingandsimilaritybasedscreeningtotargetglycoproteine AT humbymonicas identificationofzikavirusinhibitorsusinghomologymodelingandsimilaritybasedscreeningtotargetglycoproteine AT mcgeetdwight identificationofzikavirusinhibitorsusinghomologymodelingandsimilaritybasedscreeningtotargetglycoproteine AT rileyseanp identificationofzikavirusinhibitorsusinghomologymodelingandsimilaritybasedscreeningtotargetglycoproteine AT jacobsamy identificationofzikavirusinhibitorsusinghomologymodelingandsimilaritybasedscreeningtotargetglycoproteine AT rizzorobertc identificationofzikavirusinhibitorsusinghomologymodelingandsimilaritybasedscreeningtotargetglycoproteine |