About: Chapter 11 Structural Insight Into the Viral 3C-Like Protease Inhibitors: Comparative SAR/QSAR Approaches

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Chapter 11 Structural Insight Into the Viral 3C-Like Protease Inhibitors: Comparative SAR/QSAR Approaches
Creator	Adhikari, Nilanjan Jha, Tarun Saha, Achintya Baidya, Sandip
source	Elsevier; PMC
abstract	Abstract Severe acute respiratory syndrome (SARS), caused by SARS-coronavirus (SARS-CoV), is a dreadful infection worldwide having economic and medical importance and a global threat for health. It was turned into an epidemic in South China followed by a chain of infections across three generations. A number of pathogeneses in human may occur due to the virus. This infection has not been taken into account before the SARS outbreak, and still it is a neglected one. Therefore, there is an urgent need to develop small molecule antivirals to combat the SARS-CoV. No vaccines are available till date though a number of SARS-CoV 3C-like and 3C protease inhibitors were reported. In this chapter, quantitative structure–activity relationship technique is used for development of anti-SARS and anti-HRV drugs and outcome discussed in details. This approach may be a useful strategy to design novel and potential anti-SARS drugs to combat these dreadful viral diseases.
has issue date	2017-12-31(xsd:dateTime)
bibo:doi	10.1016/b978-0-12-809712-0.00011-3
has license	els-covid
sha1sum (hex)	5779e410753e13a0a79f9f872321fe42df49e65c
schema:url	https://doi.org/10.1016/b978-0-12-809712-0.00011-3
resource representing a document's title	Chapter 11 Structural Insight Into the Viral 3C-Like Protease Inhibitors: Comparative SAR/QSAR Approaches
has PubMed Central identifier	PMC7150231
schema:publication	Viral Proteases and Their Inhibitors
resource representing a document's body	covid:5779e410753e13a0a79f9f872321fe42df49e65c#body_text
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