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Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics

With more than 5 million fatalities and close to 300 million reported cases, COVID-19 is the first documented pandemic due to a coronavirus that continues to be a major health challenge. Despite being rapid, uncontrollable, and highly infectious in its spread, it also created incentives for technolo...

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Autores principales: Gupta, Yash, Savytskyi, Oleksandr V., Coban, Matt, Venugopal, Amoghavarsha, Pleqi, Vasili, Weber, Caleb A., Chitale, Rohit, Durvasula, Ravi, Hopkins, Christopher, Kempaiah, Prakasha, Caulfield, Thomas R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613808/
https://www.ncbi.nlm.nih.gov/pubmed/36371228
http://dx.doi.org/10.1016/j.mam.2022.101151
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author Gupta, Yash
Savytskyi, Oleksandr V.
Coban, Matt
Venugopal, Amoghavarsha
Pleqi, Vasili
Weber, Caleb A.
Chitale, Rohit
Durvasula, Ravi
Hopkins, Christopher
Kempaiah, Prakasha
Caulfield, Thomas R.
author_facet Gupta, Yash
Savytskyi, Oleksandr V.
Coban, Matt
Venugopal, Amoghavarsha
Pleqi, Vasili
Weber, Caleb A.
Chitale, Rohit
Durvasula, Ravi
Hopkins, Christopher
Kempaiah, Prakasha
Caulfield, Thomas R.
author_sort Gupta, Yash
collection PubMed
description With more than 5 million fatalities and close to 300 million reported cases, COVID-19 is the first documented pandemic due to a coronavirus that continues to be a major health challenge. Despite being rapid, uncontrollable, and highly infectious in its spread, it also created incentives for technology development and redefined public health needs and research agendas to fast-track innovations to be translated. Breakthroughs in computational biology peaked during the pandemic with renewed attention to making all cutting-edge technology deliver agents to combat the disease. The demand to develop effective treatments yielded surprising collaborations from previously segregated fields of science and technology. The long-standing pharmaceutical industry's aversion to repurposing existing drugs due to a lack of exponential financial gain was overrun by the health crisis and pressures created by front-line researchers and providers. Effective vaccine development even at an unprecedented pace took more than a year to develop and commence trials. Now the emergence of variants and waning protections during the booster shots is resulting in breakthrough infections that continue to strain health care systems. As of now, every protein of SARS-CoV-2 has been structurally characterized and related host pathways have been extensively mapped out. The research community has addressed the druggability of a multitude of possible targets. This has been made possible due to existing technology for virtual computer-assisted drug development as well as new tools and technologies such as artificial intelligence to deliver new leads. Here in this article, we are discussing advances in the drug discovery field related to target-based drug discovery and exploring the implications of known target-specific agents on COVID-19 therapeutic management. The current scenario calls for more personalized medicine efforts and stratifying patient populations early on for their need for different combinations of prognosis-specific therapeutics. We intend to highlight target hotspots and their potential agents, with the ultimate goal of using rational design of new therapeutics to not only end this pandemic but also uncover a generalizable platform for use in future pandemics.
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spelling pubmed-96138082022-10-28 Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics Gupta, Yash Savytskyi, Oleksandr V. Coban, Matt Venugopal, Amoghavarsha Pleqi, Vasili Weber, Caleb A. Chitale, Rohit Durvasula, Ravi Hopkins, Christopher Kempaiah, Prakasha Caulfield, Thomas R. Mol Aspects Med Review With more than 5 million fatalities and close to 300 million reported cases, COVID-19 is the first documented pandemic due to a coronavirus that continues to be a major health challenge. Despite being rapid, uncontrollable, and highly infectious in its spread, it also created incentives for technology development and redefined public health needs and research agendas to fast-track innovations to be translated. Breakthroughs in computational biology peaked during the pandemic with renewed attention to making all cutting-edge technology deliver agents to combat the disease. The demand to develop effective treatments yielded surprising collaborations from previously segregated fields of science and technology. The long-standing pharmaceutical industry's aversion to repurposing existing drugs due to a lack of exponential financial gain was overrun by the health crisis and pressures created by front-line researchers and providers. Effective vaccine development even at an unprecedented pace took more than a year to develop and commence trials. Now the emergence of variants and waning protections during the booster shots is resulting in breakthrough infections that continue to strain health care systems. As of now, every protein of SARS-CoV-2 has been structurally characterized and related host pathways have been extensively mapped out. The research community has addressed the druggability of a multitude of possible targets. This has been made possible due to existing technology for virtual computer-assisted drug development as well as new tools and technologies such as artificial intelligence to deliver new leads. Here in this article, we are discussing advances in the drug discovery field related to target-based drug discovery and exploring the implications of known target-specific agents on COVID-19 therapeutic management. The current scenario calls for more personalized medicine efforts and stratifying patient populations early on for their need for different combinations of prognosis-specific therapeutics. We intend to highlight target hotspots and their potential agents, with the ultimate goal of using rational design of new therapeutics to not only end this pandemic but also uncover a generalizable platform for use in future pandemics. The Authors. Published by Elsevier Ltd. 2023-06 2022-10-28 /pmc/articles/PMC9613808/ /pubmed/36371228 http://dx.doi.org/10.1016/j.mam.2022.101151 Text en © 2022 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 Review
Gupta, Yash
Savytskyi, Oleksandr V.
Coban, Matt
Venugopal, Amoghavarsha
Pleqi, Vasili
Weber, Caleb A.
Chitale, Rohit
Durvasula, Ravi
Hopkins, Christopher
Kempaiah, Prakasha
Caulfield, Thomas R.
Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics
title Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics
title_full Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics
title_fullStr Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics
title_full_unstemmed Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics
title_short Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics
title_sort protein structure-based in-silico approaches to drug discovery: guide to covid-19 therapeutics
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613808/
https://www.ncbi.nlm.nih.gov/pubmed/36371228
http://dx.doi.org/10.1016/j.mam.2022.101151
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