QSAR analysis on tacrine-related acetylcholinesterase inhibitors.

Background: The evaluation of the clinical effects of Tacrine has shown efficacy in delaying the deterioration of the symptoms of Alzheimer's disease, while confirming the adverse events consisting mainly in the elevated liver transaminase levels. The study of tacrine analogs presents a continuous interest, and for this reason we establish Quantitative Structure-Activity Relationships on their Acetylcholinesterase inhibitory activity.

Results: Ten groups of new developed Tacrine-related inhibitors are explored, which have been experimentally measured in different biochemical conditions and AChE sources.

Naturally-occurring dimers of flavonoids as anticarcinogens.

Biflavonoids are dimers of flavonoid moieties linked by a C-C or C-O-C bond. Simple, complex, rearranged, natural and ketalized Diels-Alder adducts, benzofuran derivatives, and spirobiflavonoids are some of the structural groups of biflavonoids. These compounds are mainly distributed in the Gymnosperms, Angiosperms (monocots and dicots), ferns (Pteridophyta), and mosses (Bryophyta).

(Iso)flav(an)ones, chalcones, catechins, and theaflavins as anticarcinogens: mechanisms, anti-multidrug resistance and QSAR studies.

Flavonoids have shown anticarcinogenic activity in cancer cell lines, animal models, and some human studies. Quantitative structure-activity relationship (QSAR) models have become useful tools for identification of promising lead compounds in anticancer drug development. However, epidemiological and clinical studies are still scarce.

Advances in the replacement and enhanced replacement method in QSAR and QSPR theories.

The selection of an optimal set of molecular descriptors from a much greater pool of such regression variables is a crucial step in the development of QSAR and QSPR models. The aim of this work is to further improve this important selection process. For this reason three different alternatives for the initial steps of our recently developed enhanced replacement method (ERM) and replacement method (RM) are proposed.

Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds.

The objective of the article was to perform a predictive analysis, based on quantitative structure-property relationships, of the dissociation constants (pK(a)) of different medicinal compounds (e.g., salicylic acid, salbutamol, lidocaine).

Replacement method and enhanced replacement method versus the genetic algorithm approach for the selection of molecular descriptors in QSPR/QSAR theories.

We compare three methods for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. On the one hand is our enhanced replacement method (ERM) and on the other is the simpler replacement method (RM) and the genetic algorithm (GA). These methods avoid the impracticable full search for optimal variables in large sets of molecular descriptors.

QSAR study of flavonoids and biflavonoids as influenza H1N1 virus neuraminidase inhibitors.

We performed a predictive analysis based on Quantitative Structure-Activity Relationships (QSAR) of a very important property of flavonoids which is the inhibition (IC50) of influenza H1N1 virus neuraminidase. The best linear model constructed from 20 molecular structures incorporated four molecular descriptors, selected from more than a thousand geometrical, topological, quantum-mechanical and electronic types of descriptors. The obtained model suggests that the activity depends on the electric charges, masses and polarizabilities of the atoms present in the molecule as well as its conformation.

Predictive modeling of the total deactivation rate constant of singlet oxygen by heterocyclic compounds.

We constructed a predictive model of the total deactivation rate constant (k(t)) of singlet oxygen by heterocyclic compounds that are widespread in biological systems and participate in highly relevant biologic functions related with photochemical processes, by means of quantitative structure-property relationships (QSPR). The study of the reactivity of singlet oxygen with biomolecules provides their antioxidant capability, and the determination of the rate constants allows evaluation of the efficiencies of these processes. Our optimal linear model based on 41 molecular structures, which have not been used previously in a QSPR study, consists of six variables, selected from more than thousand geometrical, topological, quantum-mechanical and electronic types of molecular descriptors.

QSAR prediction of inhibition of aldose reductase for flavonoids.

We performed a predictive analysis based on quantitative structure-activity relationships (QSAR) of an important property of flavonoids, which is the inhibition (IC(50)) of aldose reductase (AR). The importance of AR inhibition is that it prevents cataract formation in diabetic patients. The best linear model constructed from 55 molecular structures incorporated six molecular descriptors, selected from more than a thousand geometrical, topological, quantum-mechanical, and electronic types of descriptors.