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Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emergence has resulted in a global health crisis. As a consequence, discovering an effective therapy that saves lives and slows the spread of the pandemic is a global concern currently. In silico drug repurposing is highly regarded as a pr...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8421083/ https://www.ncbi.nlm.nih.gov/pubmed/34514079 http://dx.doi.org/10.1016/j.imu.2021.100725 |
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author | Elbadwi, Fatima A. Khairy, Elaf A. Alsamani, Fatima O. Mahadi, Mariam A. Abdalrahman, Segood E. Ahmed, Zain Alsharf M. Elsayed, Inas Ibraheem, Walaa Alzain, Abdulrahim A. |
author_facet | Elbadwi, Fatima A. Khairy, Elaf A. Alsamani, Fatima O. Mahadi, Mariam A. Abdalrahman, Segood E. Ahmed, Zain Alsharf M. Elsayed, Inas Ibraheem, Walaa Alzain, Abdulrahim A. |
author_sort | Elbadwi, Fatima A. |
collection | PubMed |
description | Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emergence has resulted in a global health crisis. As a consequence, discovering an effective therapy that saves lives and slows the spread of the pandemic is a global concern currently. In silico drug repurposing is highly regarded as a precise computational method for obtaining fast and reliable results. Transmembrane serine-type 2 (TMPRSS2) is a SARS CoV-2 enzyme that is essential for viral fusion with the host cell. Inhibition of TMPRSS2 may block or lessen the severity of SARS-CoV-2 infection. In this study, we aimed to perform an in silico drug repurposing to identify drugs that can effectively inhibit SARS-CoV-2 TMPRSS2. As there is no 3D structure of TMPRSS2 available, homology modeling was performed to build the 3D structure of human TMPRSS2. 3848 world-approved drugs were screened against the target. Based on docking scores and visual outcomes, the best-fit drugs were chosen. Molecular dynamics (MD) and density functional theory (DFT) studies were also conducted. Five potential drugs (Amikacin, isepamicin, butikacin, lividomycin, paromomycin) exhibited promising binding affinities. In conclusion, these findings empower purposing these agents. |
format | Online Article Text |
id | pubmed-8421083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Authors. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84210832021-09-07 Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies Elbadwi, Fatima A. Khairy, Elaf A. Alsamani, Fatima O. Mahadi, Mariam A. Abdalrahman, Segood E. Ahmed, Zain Alsharf M. Elsayed, Inas Ibraheem, Walaa Alzain, Abdulrahim A. Inform Med Unlocked Article Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emergence has resulted in a global health crisis. As a consequence, discovering an effective therapy that saves lives and slows the spread of the pandemic is a global concern currently. In silico drug repurposing is highly regarded as a precise computational method for obtaining fast and reliable results. Transmembrane serine-type 2 (TMPRSS2) is a SARS CoV-2 enzyme that is essential for viral fusion with the host cell. Inhibition of TMPRSS2 may block or lessen the severity of SARS-CoV-2 infection. In this study, we aimed to perform an in silico drug repurposing to identify drugs that can effectively inhibit SARS-CoV-2 TMPRSS2. As there is no 3D structure of TMPRSS2 available, homology modeling was performed to build the 3D structure of human TMPRSS2. 3848 world-approved drugs were screened against the target. Based on docking scores and visual outcomes, the best-fit drugs were chosen. Molecular dynamics (MD) and density functional theory (DFT) studies were also conducted. Five potential drugs (Amikacin, isepamicin, butikacin, lividomycin, paromomycin) exhibited promising binding affinities. In conclusion, these findings empower purposing these agents. The Authors. Published by Elsevier Ltd. 2021 2021-09-07 /pmc/articles/PMC8421083/ /pubmed/34514079 http://dx.doi.org/10.1016/j.imu.2021.100725 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Elbadwi, Fatima A. Khairy, Elaf A. Alsamani, Fatima O. Mahadi, Mariam A. Abdalrahman, Segood E. Ahmed, Zain Alsharf M. Elsayed, Inas Ibraheem, Walaa Alzain, Abdulrahim A. Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies |
title | Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies |
title_full | Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies |
title_fullStr | Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies |
title_full_unstemmed | Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies |
title_short | Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies |
title_sort | identification of novel transmembrane protease serine type 2 drug candidates for covid-19 using computational studies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8421083/ https://www.ncbi.nlm.nih.gov/pubmed/34514079 http://dx.doi.org/10.1016/j.imu.2021.100725 |
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