Aa. Gakh et al., PREDICTION OF COMPLEXATION PROPERTIES OF CROWN-ETHERS USING COMPUTATIONAL NEURAL NETWORKS, Journal of inclusion phenomena and molecular recognition in chemistry, 27(3), 1997, pp. 201-213
A computational neural network method was used for the prediction of s
tability constants of simple crown ether complexes. The essence of the
method lies in the ability of a computer neural network to recognize
the structure-property relationships in these host-guest systems. Test
ing of the computational method has demonstrated that stability consta
nts of alkali metal cation (Na+, Kf, Cs+)-crown ether complexes in met
hanol at 25 degrees C can be predicted with an average error of +/-0.3
log K units based on the chemical structure of the crown ethers alone
. The computer model was then used for the preliminary analysis of tre
nds in the stabilities of the above complexes.