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In Silico Modeling of Drugs Against Coronaviruses [electronic resource] : Computational Tools and Protocols / edited by Kunal Roy.

Contributor(s): Material type: TextSeries: Methods in Pharmacology and ToxicologyPublisher: New York, NY : Springer US : Imprint: Humana, 2021Edition: 1st ed. 2021Description: XXVI, 788 p. 191 illus., 162 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781071613665
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 579.2 23
  • 616.96 23
LOC classification:
  • QR355-502
Online resources: In: Springer Nature eBookSummary: 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 future.
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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 future.

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