Computational Chemistry/Drug Design

From Wikibooks, open books for an open world
Jump to navigation Jump to search

Previous chapter - Macromolecular chemistry

Computer Aided Drug design[edit | edit source]

Quantum Pharmacology[edit | edit source]

This area covers the use of electronic structure theories to de novo design of drugs, extraction of structure activity relationships and development of pharmacophores to rationalise the drug's mechanism. Computations, proteomics and genomics have advanced considerably since Richard's book and maybe new definitions are needed.

W. G. Richards, Quantum Pharmacology, (Butterworths,London,1977).

QSAR[edit | edit source]

A lot of work goes into developing Quantitative Structure Activity Relationships. This can be done by regression analysis even where there is no adequate model of the active site of the process. Some examples are being extracted from literature which we have in the Chemistry Library, (much literatuire of relevance is in biological and pharmacological journals. Some QSAR work uses classic physical organic chemistry such as the Taft and Hammett equations, whereas in recent work all manner of unusual properties may be incorporated into a QSAR.

There is even interest in exotic artificial intelligence technologies such as neural nets. A new technique in this area is known as Support vector machines.

Hansch, C. and Leo, A. Exploring QSAR: ACS Professional Reference Book, (American Chemical Society, Washington, DC,1995).

Neural Nets to Design Drugs[edit | edit source]

This is a comparatively new area of chemistry / chemo-informatics but it already has a classic textbook:

J. Zupan and J. Gasteiger, Neural Networks in Chemistry and Drug Design: An Introduction, 2nd Edition, Wiley, 1999, ISBN: 3-527-29779-0.

Bibliography[edit | edit source]

  • edited Andrew Vinter and Mark Gardner Molecular modelling and drug design, (Boca Raton:CRC Press,1994), ISBN 0849377722.

Next Chapter - Continuum solvation models