Electronic-topological study of the structure-activity relationships in a series of piperidine morphinomimetics

ETM-ANN approach application for thiobenzamide and quinolizidine derivatives

The structure anti-influenza activity relationships of thiobenzamide and quinolizidine derivatives, being influenza fusion inhibitors, have been investigated using the electronic-topological method (ETM) and artificial neural network (ANN) method. Molecular fragments specific for active compounds and breaks of activity were calculated for influenza fusion inhibitors by applying the ETM. QSAR descriptors such as molecular weight, E_HOMO, E_LUMO, ΔE, chemical potential, softness, electrophilicity index, dipole moment, and so forth were calculated, and it was found to give good statistical qualities (classified correctly 92%, or 48 compounds from 52 in training set, and 69% or 9 compounds from 13 in the external test set). By using multiple linear regression, several QSAR models were performed with the help of calculated descriptors and the compounds activity data. Among the obtained QSAR models, statistically the most significant one is the one of skeleton 1 with R² = 0.999.

The investigation of structure-activity relationships of tacrine analogues: electronic-topological method

In this study we investigated the structure-activity relationships by using the Electron- Topological Method (ETM) for a class of AChE inhibitors related to tacrine (9-amino-1,2,3,4-tetrahydroacridine) and 11 H-Indeno-[1,2-b]-quinolin-10-ylamine that tetracyclic tacrine analogues, a drug currently in use for the treatment of the AD. Molecular fragments being specific for active and inactive compounds were revealed by using ETM. The result of testing showed the high ability of ETM in predicting the activity and inactivity in investigated series.