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Titlebook: In Silico Modeling of Drugs Against Coronaviruses; Computational Tools Kunal Roy Book 2021 The Editor(s) (if applicable) and The Author(s)

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發(fā)表于 2025-3-21 20:05:27 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱In Silico Modeling of Drugs Against Coronaviruses
副標(biāo)題Computational Tools
編輯Kunal Roy
視頻videohttp://file.papertrans.cn/463/462973/462973.mp4
概述Documents protocols and case studies of computational drug design and computational drug repurposing.Features structure-based and ligand-based approaches in drug design.Covers machine learning/deep le
叢書名稱Methods in Pharmacology and Toxicology
圖書封面Titlebook: In Silico Modeling of Drugs Against Coronaviruses; Computational Tools  Kunal Roy Book 2021 The Editor(s) (if applicable) and The Author(s)
描述This essential volume explores a variety of tools and protocols of structure-based (homology modeling, molecular docking, molecular dynamics, protein-protein interaction network) and ligand-based (pharmacophore mapping, quantitative structure-activity relationships or QSARs) drug design for ranking and prioritization of candidate molecules in search of effective treatment strategy against coronaviruses. Beginning with an introductory section that discusses coronavirus interactions with humanity and COVID-19 in particular, the book then continues with sections on tools and methodologies, literature reports and case studies, as well as online tools and databases that can be used for computational anti-coronavirus drug research. Written for the .Methods in Pharmacology and Toxicology. series, chapters include the kind of practical detail and implementation advice that ensures high quality results in the lab.?.Comprehensive and timely, .In Silico Modeling ofDrugs Against Coronaviruses: Computational Tools and Protocols. is an ideal reference for researchers working on the development of novel anti-coronavirus drugs for SARS-CoV-2 and for coronaviruses that will likely appear in the fut
出版日期Book 2021
關(guān)鍵詞Coronavirus; Computational modeling; Drug repurposing; Structure-based modeling; Ligand-based modeling; N
版次1
doihttps://doi.org/10.1007/978-1-0716-1366-5
isbn_softcover978-1-0716-1368-9
isbn_ebook978-1-0716-1366-5Series ISSN 1557-2153 Series E-ISSN 1940-6053
issn_series 1557-2153
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Busines
The information of publication is updating

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發(fā)表于 2025-3-21 23:41:33 | 只看該作者
978-1-0716-1368-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Busines
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發(fā)表于 2025-3-22 02:42:45 | 只看該作者
In Silico Modeling of Drugs Against Coronaviruses978-1-0716-1366-5Series ISSN 1557-2153 Series E-ISSN 1940-6053
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Methods in Pharmacology and Toxicologyhttp://image.papertrans.cn/i/image/462973.jpg
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發(fā)表于 2025-3-22 14:49:50 | 只看該作者
Book 2021protein interaction network) and ligand-based (pharmacophore mapping, quantitative structure-activity relationships or QSARs) drug design for ranking and prioritization of candidate molecules in search of effective treatment strategy against coronaviruses. Beginning with an introductory section that
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發(fā)表于 2025-3-22 21:02:32 | 只看該作者
Transmission, Medical Consequences, and Prevention/Treatment of COVID-19 Infections deemed necessary that new protocols should be launched for the development and evaluation of vaccines and therapeutics. In this chapter, we discuss the spread and/or transmission of SARS-CoV-2 and the associated complications. Moreover, we summarize the therapeutic and prevention options and the most salient features of COVID-19.
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1557-2153 ed approaches in drug design.Covers machine learning/deep leThis essential volume explores a variety of tools and protocols of structure-based (homology modeling, molecular docking, molecular dynamics, protein-protein interaction network) and ligand-based (pharmacophore mapping, quantitative structu
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