Quantitative Structure–Activity Relationships (QSARs) – Applications and Methodology

  • Mark T. D. CroninEmail author
Part of the Challenges and Advances in Computational Chemistry and Physics book series (COCH, volume 8)


The aim of this introduction is to describe briefly the applications and methodologies involved in (Q)SAR and relate these to the various chapters in this volume. This chapter gives the reader an overview of how, why and where in silico methods, including (Q)SAR, have been utilized to predict endpoints as diverse as those from pharmacology and toxicology. It provides an illustration of how all the various topics in this book interweave to form a single coherent area of science.


QSAR In silico methods Resources for QSAR 


  1. 1.
    Topliss JG, Costello RJ (1972) Chance correlations in structure-activity studies using multiple regression analysis. J Med Chem 15:1066–1068.CrossRefGoogle Scholar
  2. 2.
    Schultz TW, Netzeva TI, Cronin MTD (2003) Selection of data sets for QSARs: analyses of Tetrahymena toxicity from aromatic compounds. SAR QSAR Environ Res 14:59–81.CrossRefGoogle Scholar
  3. 3.
    Selassie CD (2003) History of quantitative structure-activity relationships. In: Abraham DJ (ed) Burger’s Medicinal Chemistry and Drug Discovery, 6th edn., Volume 1: Drug Discovery. John Wiley and Sons, Inc., New York.Google Scholar
  4. 4.
    Hansch C, Maloney PP, Fujita T et al. (1962) Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. Nature 194:178–180.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.School of Pharmacy and ChemistryLiverpool John Moores UniversityLiverpoolEngland

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