rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Drug design strategies
    sub title: quantitative approaches
  name:
    name part: Davis, Andrew M.
    name part: (Chemist)
  name:
    name part: Livingstone, D. (David)
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: enk
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (516 pages) : illustrations
  abstract: This book brings together drug design practitioners, all leaders in their field, who are actively advancing the field of quantitative methods to guide drug discovery, from structure-based design to empirical statistical models - from rule-based approaches to toxicology to the fields of bioinformatics and systems biology. The aim of the book is to show how various facets of the drug discovery process can be addressed in a quantitative fashion (ie: numerical analysis to enable robust predictions to be made). Each chapter includes a brief review of the topic showing the historical development of quantitative approaches, a survey/summary of the current state-of-the-art, a selection of well chosen examples with some worked through and an appreciation of what problems remain to be overcome as well as an indication of how the field may develop. After an overview of quantitative approaches to drug design the book describes the development of concepts of "drug-like properties", of quantitative structure-activity relationships and molecular modelling, and in particular, structure-based design approaches to guide lead optimisation. How to manage and describe chemical structures, underpins all quantitative approaches to drug design and these are described in the following chapters. The next chapter covers the value of a quantitative approach, and also the challenge which is to describe the confidence in any prediction, and methods to assess predictive model quality. The later chapters describe the application of quantitative approaches to describing and optimising potency, selectivity, drug metabolism and pharmacokinetic properties and toxicology, and the design of chemical libraries to feed the screening approaches to lead generation that underpin modern drug discovery. Finally the book describes the impact of bioinformatics, current status of predicting ligand affinity direct from the protein structure, and the application of quantitative approaches to predicting environmenta…
  note: edited by David J. Livingstone, Andrew M. Davis.
  note: Electronic resource.
  note: Includes bibliographical references and index.
  subject:
    topic: Drug Design
  subject:
    topic: Drug Discovery
  subject:
    topic: Decision Support Techniques
  subject:
    topic: Models, Chemical
  subject:
    topic: Models, Molecular
  subject:
    topic: Quantitative Structure-Activity Relationship
  subject:
    topic: Computer Simulation
  subject:
    topic: Drugs
    topic: Design
  subject:
    topic: Drugs
    topic: Design
  subject:
    topic: MEDICAL
    topic: Drug Guides
  subject:
    topic: MEDICAL
    topic: Nursing
    topic: Pharmacology
  subject:
    topic: MEDICAL
    topic: Pharmacology
  subject:
    topic: MEDICAL
    topic: Pharmacy
  classification: RS420
  classification: 615.19
  classification: QV 744
  related item:
    title info:
      title: Drug design strategies
    origin info:
      publisher: Cambridge : Royal Society of Chemistry, 2012
    identifier: (OCoLC)759585091
  related item:
    title info:
      title: RSC drug discovery series ; 13
  identifier: 1621981401
  identifier: 1849731675
  identifier: 1849733414
  identifier: 9781621981404
  identifier: 9781849731676
  identifier: 9781849733410
  identifier: 1849731667
  identifier: 9781849731669
  identifier: 00154291
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: COO
    record creation date: 111105
    record change date: 20210728140519.0
    record identifier: in00004357949
    language of cataloging:
      language term: eng