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Biophysical and computational tools ...

Arora, A.

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Biophysical and computational tools in drug discovery

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Biophysical and computational tools in drug discovery/ edited by Anil Kumar Saxena ; with contributions by A. Arora ... [et al.].
其他作者:	Arora, A.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	viii, 402 p. :ill., digital ;24 cm.
內容註:	Kinetic profiling of fragments by TR-FRET -- Role of Structural biology in drug discovery with emphasis on X-ray crystallography -- A computational search for peptide vaccines using novel mathematical descriptors of sequences of emerging pathogens -- Solution NMR methods in Drug Discovery for the series -- Applications of Mass Spectrometry in Herbal Drug Research -- Generative machine learning for drug discovery -- Structure and ligand based virtual screening in drug discovery -- Quantum Chemical and Quantum Dynamics Techniques for Drug Discovery Including Bioinorganic Compounds.
Contained By:	Springer Nature eBook
標題:	Pharmacology. -
電子資源:	https://doi.org/10.1007/978-3-030-85281-8
ISBN:	9783030852818

Biophysical and computational tools in drug discovery
Biophysical and computational tools in drug discovery[electronic resource] /edited by Anil Kumar Saxena ; with contributions by A. Arora ... [et al.]. - Cham :Springer International Publishing :2021. - viii, 402 p. :ill., digital ;24 cm. - Topics in medicinal chemistry,v. 371862-247X ;. - Topics in medicinal chemistry ;v. 37..

Kinetic profiling of fragments by TR-FRET -- Role of Structural biology in drug discovery with emphasis on X-ray crystallography -- A computational search for peptide vaccines using novel mathematical descriptors of sequences of emerging pathogens -- Solution NMR methods in Drug Discovery for the series -- Applications of Mass Spectrometry in Herbal Drug Research -- Generative machine learning for drug discovery -- Structure and ligand based virtual screening in drug discovery -- Quantum Chemical and Quantum Dynamics Techniques for Drug Discovery Including Bioinorganic Compounds.

This book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Forster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals from pharmaceutical industry interested in drug design and discovery.

ISBN: 9783030852818

Standard No.: 10.1007/978-3-030-85281-8doiSubjects--Topical Terms:

634543
Pharmacology.

LC Class. No.: RM301 / .B56 2021

Dewey Class. No.: 615.1

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520 $a This book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Forster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals from pharmaceutical industry interested in drug design and discovery.
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