Advanced Computer-Assisted Techniques in Drug Discovery (Methods and Principles in Medicinal Chemistry)

Advanced Computer-Assisted Techniques in Drug Discovery (Methods and Principles in Medicinal Chemistry), 9783527292486 (3527292489), John Wiley & Sons, 1994

The main objective of this series is to offer a practice-oriented survey of techniques currently used in Medicinal Chemistry. Following the volumes on Hansch analysis and related approaches (Vol. 1) and multivariate analyses (Vol. 2), the present handbook focuses on some new, emerging techniques in drug discovery; emphasis is plated on showing users how to apply these methods and to avoid time-consuming and costly errors.

Four major topics are covered. The first centers on three-dimensional QSAR, and some of the enormous progress achieved in this field is summarized. Both the various 3D-QSAR methods available as well as the chemometric tools for handling the statistical problems involved in 3D-QSAR studies are covered.

Intimately coupled with 3D-QSAR is the current trend in pharmaceutical industry to establish chemical structure databases as a tool for identifying new leads. Correspondingly, in the second section, problems encountered in our understanding of molecular similarity and aspects of compound selection by clustering databases are treated.

The third section covers advanced statistical techniques in drug discovery. Inter alia the approach of Svante Wold to apply PLS to non-linear structure-activity relations deserves to be mentioned here.

Last but not least, the use of neural networks for data analysis in QSAR problems is discussed. Advantages and disadvantages are critically analysed by comparing networks versus statistics.

The editors would like to thank all contributors and VCH publishers for their fruitful cooperation.

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