Ligand-Based Drug Design - Drug Design and Discovery - page 57

as exemplii ed by compounds 3.2 and 3.4 in Figure 3.2. Furthermore, it has been reported that
bromo, methyl, or tril uoro methyl substitution in the 3 -position is highly favorable for the afi nity.

The interpretation of the contours from the water probe (Figure 3.15b) is less straightforward.
As shown in Equation 3.1, interactions with this probe include vdW as well as hydrogen bond and
electrostatic interactions. Thus, the water probe as well as the methyl probe displays vdW interac-
tions. Consequently, the regions of interest for the water probe are the regions where the contour plot
deviates from the corresponding plot of the methyl probe. The most signii cant of these regions is
encircled in Figure 3.15b. This region has negative PLS coefi cients and a negative E tot value, which
gives a favorable contribution to the afi nity. A hydrogen bond or attractive electrostatic interac-
tion gives a negative interaction energy. Thus, substituents in the 6

′

- position, which may have such
interactions with the water probe, are predicted to give an afi nity increase. An example of this is
the hydroxy group in compound 3.13 .
Contour maps of PLS coefi cients can, as demonstrated earlier, provide information for the
design of new compounds and the positive and negative regions calculated by GOLPE give a picture
of important properties of the binding pocket in the receptor.
In predictions of the afi nity of new compounds it should be noted that the test set used to build
the 3D-QSAR model should have sufi cient structural variation. For instance, if the test set only
contains compounds with a methyl group in a particular position, it is not possible to predict the
activities of larger alkyl groups in this position.

′

FURTHER READINGS
Baroni, M., Costantino, G., Cruciani, G., Riganelli, D., Valigi, R., and Clementi, S. 1993. Generating optimal
linear PLS estimations (GOLPE): An advanced chemometric tool for handling 3D-QSAR problems.
Quant. Struct. Act. Relat . 12:9-20.
Dekermendjian, K., Kahnberg, P., Witt, M.-R., Sterner, O., Nielsen, M., and Liljefors, T. 1999. Structure-
activity relationships and molecular modeling analysis of l avonoids binding to the benzodiazepine site
of the rat brain GABA A receptor complex. J. Med. Chem . 42:4343-4350.
Goodford, P. J. 1985. A computational procedure for determining energetically favorable binding sites on bio-
logically important macromolecules. J. Med. Chem . 28:849-857.
Güner, O.F. (ed.) 2000. Pharmacophore Perception, Development and Use in Drug Design . International
University Line, La Jolla.
Kahnberg, P., Lager, E., Rosenberg, C., Schougaard, J., Camet, L., Sterner, O., Nielsen, E. Ø., Nielsen, M., and
Liljefors, T. 2002. Rei nement and evaluation of a pharmacophore model for l avone derivatives binding
to the benzodiazepine site of the GABA A receptor. J. Med. Chem . 45:4188-4201.
Kahnberg, P., Howard, M. H., Liljefors, T., Nielsen, M., Nielsen, E. Ø., Sterner, O., and Pettersson, I. 2004.
The use of a pharmacophore model for identii cation of novel ligands for the benzodiazepine site of the
GABA A receptor. J. Mol. Graph. Model . 23:253-261.
Wold, S., Johansson, E., and Cocchi, M. 1993. PLS—Partial least squares projections to latent structures.
In 3D QSAR in Drug Design: Theory, Methods, and Applications , Kubinyi, H. (ed.), ESCOM Science
Publishers B.V., Leiden, the Netherlands, pp. 583-618.
Zhang, W., Koehler, K. F., Zhang, P., and Cook, J. M. 1995. Development of a comprehensive pharmacophore
model for the benzodiazepine receptor. Drug Des. Dev . 12:193-248.