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Farmakologi

Quantitative Drug Design

A Critical Introduction, Second Edition

Udgivet af Taylor & Francis Ltd

Bogdetaljer

  • Hæftet
  • 292 sider
  • Engelsk
ISBN 9780367384142
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Since the publication of the first edition, the field has changed dramatically. Scientists can now explicitly consider 3D features in quantitative structure-activity relationship (QSAR) studies and often have the 3D structure of the macromolecular target to guide the 3D QSAR. Improvements in computer hardware and softw…

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Bogdetaljer
Forfatter Yvonne C. Martin
Forlag Taylor & Francis Ltd
Kategori Farmakologi
ISBN-13 9780367384142
EAN 9780367384142
Format Hæftet
Sprog Engelsk
sider 292
Undertitel - A Critical Introduction, Second Edition
Produktbeskrivelse
Since the publication of the first edition, the field has changed dramatically. Scientists can now explicitly consider 3D features in quantitative structure-activity relationship (QSAR) studies and often have the 3D structure of the macromolecular target to guide the 3D QSAR. Improvements in computer hardware and software have also made the methods more accessible to scientists. Taking these developments into account, Quantitative Drug Design: A Critical Introduction, Second Edition shows scientists how to apply QSAR techniques at a state-of-the-art level.New to the Second EditionA new chapter on methods that identify the 3D conformations to use for 3D QSARNew discussions on partial least squares, multidimensional scaling, clustering, support vector machines, kNN potency prediction, and recursive partitioningExpanded case studies that include the results of data that has been re-analyzed using newer methodsA new case study on the discovery of novel dopaminergics with pharmacophore mapping and CoMFAA new case study on the application of CoMFA to series in which the 3D structure of the ligand-protein complex is knownBased on the authors four decades of experience in all areas of ligand-based computer-assisted drug design, this invaluable book describes how to transform ligand structure-activity relationships into models that predict the potency or activity/inactivity of new molecules. It will help you avoid traps when dealing with quantitative drug design.

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