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Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic

Coronavirus disease 2019 (COVID-19) has made many concerns for healthcare services especially, in finding useful therapeutic(s). Despite the scientists’ struggle to find and/or creating possible drugs, so far there is no treatment with high efficiency for the disease. During the pandemic, researcher...

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Autores principales: Khazeei Tabari, Mohammad Amin, Khoshhal, Hooman, Tafazoli, Alireza, Khandan, Mohanna, Bagheri, Abouzar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7568469/
https://www.ncbi.nlm.nih.gov/pubmed/33102687
http://dx.doi.org/10.1016/j.imu.2020.100458
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author Khazeei Tabari, Mohammad Amin
Khoshhal, Hooman
Tafazoli, Alireza
Khandan, Mohanna
Bagheri, Abouzar
author_facet Khazeei Tabari, Mohammad Amin
Khoshhal, Hooman
Tafazoli, Alireza
Khandan, Mohanna
Bagheri, Abouzar
author_sort Khazeei Tabari, Mohammad Amin
collection PubMed
description Coronavirus disease 2019 (COVID-19) has made many concerns for healthcare services especially, in finding useful therapeutic(s). Despite the scientists’ struggle to find and/or creating possible drugs, so far there is no treatment with high efficiency for the disease. During the pandemic, researchers have performed some molecular analyses to find potential therapeutics out of both the natural and synthetic available medicines. Computer simulations and related data have shown a significant role in drug discovery and development before. In this field, antiviral drugs, phytochemicals, anti-inflammatory agents, etc. were essential groups of compounds tested against COVID-19, using molecular modeling, molecular dynamics (MD), and docking tools. The results indicate promising effects of such compounds to be used in further experimental and clinical trials; Chloroquine, Chloroquine-OH, and Umifenovir as viral entry inhibitors, Remdesivir, Ribavirin, Lopinavir, Ritonavir, and Darunavir as viral replication inhibitors, and Sirolimus are the examples, which were tested clinically on patients after comprehensive assessments of the available data on molecular simulation. This review summarizes the outcomes of various computer simulations data in the battle against COVID-19.
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spelling pubmed-75684692020-10-19 Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic Khazeei Tabari, Mohammad Amin Khoshhal, Hooman Tafazoli, Alireza Khandan, Mohanna Bagheri, Abouzar Inform Med Unlocked Article Coronavirus disease 2019 (COVID-19) has made many concerns for healthcare services especially, in finding useful therapeutic(s). Despite the scientists’ struggle to find and/or creating possible drugs, so far there is no treatment with high efficiency for the disease. During the pandemic, researchers have performed some molecular analyses to find potential therapeutics out of both the natural and synthetic available medicines. Computer simulations and related data have shown a significant role in drug discovery and development before. In this field, antiviral drugs, phytochemicals, anti-inflammatory agents, etc. were essential groups of compounds tested against COVID-19, using molecular modeling, molecular dynamics (MD), and docking tools. The results indicate promising effects of such compounds to be used in further experimental and clinical trials; Chloroquine, Chloroquine-OH, and Umifenovir as viral entry inhibitors, Remdesivir, Ribavirin, Lopinavir, Ritonavir, and Darunavir as viral replication inhibitors, and Sirolimus are the examples, which were tested clinically on patients after comprehensive assessments of the available data on molecular simulation. This review summarizes the outcomes of various computer simulations data in the battle against COVID-19. The Authors. Published by Elsevier Ltd. 2020 2020-10-17 /pmc/articles/PMC7568469/ /pubmed/33102687 http://dx.doi.org/10.1016/j.imu.2020.100458 Text en © 2020 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
Khazeei Tabari, Mohammad Amin
Khoshhal, Hooman
Tafazoli, Alireza
Khandan, Mohanna
Bagheri, Abouzar
Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic
title Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic
title_full Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic
title_fullStr Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic
title_full_unstemmed Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic
title_short Applying computer simulations in battling with COVID-19, using pre-analyzed molecular and chemical data to face the pandemic
title_sort applying computer simulations in battling with covid-19, using pre-analyzed molecular and chemical data to face the pandemic
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7568469/
https://www.ncbi.nlm.nih.gov/pubmed/33102687
http://dx.doi.org/10.1016/j.imu.2020.100458
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