Structure-activity relationship investigations of leishmanicidal N-benzylcytisine derivatives.

In vitro leishmanicidal activity of 16 N-benzylcytisine derivatives has been evaluated using Leishmania donovani axenic amastigotes. In general, halogen (bromo-, chloro-) derivatives appeared to be more toxic against parasites than their parent compounds. Quantum-chemical calculations helped to recognize certain patterns in the structure of frontier orbitals related to bioactivity of compounds. Thus, the presence of halogen atom is shown to have a significant effect on both distribution and the energy of LUMOs thereby on potent activity that was also confirmed by Quantitative-Structure Activity Relationship (QSAR) analysis. Experimentally and theoretically observed structure-cytotoxicity relationships are described.

Aconitum and Delphinium sp. alkaloids as antagonist modulators of voltage-gated Na+ channels. AM1/DFT electronic structure investigations and QSAR studies.

Early pharmacological studies of Aconitum and Delphinium sp. alkaloids suggested that these neurotoxins act at site 2 of voltage-gated Na(+) channel and allosterically modulate its function. Understanding structural requirements for these compounds to exhibit binding activity at voltage-gated Na(+) channel has been important in various fields. This paper reports quantum-chemical studies and quantitative structure-activity relationships (QSARs) based on a total of 65 natural alkaloids from two plant species, which includes both blockers and openers of sodium ion channel. A series of 18 antagonist alkaloids (9 blockers and 9 openers) have been studied using AM1 and DFT computational methods in order to reveal their structure-activity (structure-toxicity) relationship at electronic level. An examination of frontier orbitals obtained for ground and protonated forms of the compounds revealed that HOMOs and LUMOs were mainly represented by nitrogen atom and benzyl/benzoylester orbitals with -OH and -OCOCH(3) contributions. The results obtained from this research have confirmed the experimental findings suggesting that neurotoxins acting at type 2 receptor site of voltage-dependent sodium channel are activators and blockers with common structural features and differ only in efficacy. The energetic tendency of HOMO-LUMO energy gap can probably distinguish activators and blockers that have been observed. Genetic Algorithm with Multiple Linear Regression Analysis (GA-MLRA) technique was also applied for the generation of three-descriptor QSAR models for the set of 65 blockers. Additionally to the computational studies, the HOMO-LUMO gap descriptor in each obtained QSAR model has confirmed the crucial role of charge transfer in receptor-ligand interactions. A number of other descriptors such as logP, I(BEG), nNH2, nHDon, nCO have been selected as complementary ones to LUMO and their role in activity alteration has also been discussed.

Aconitum and Delphinium alkaloids "Drug-likeness" descriptors related to toxic mode of action.

Large series of Aconitum and Delphinium alkaloids have been investigated by means of QSAR analysis. Descriptors related to "drug-likeness" of molecules were selected to discriminate between "drugs" and "non-drugs" amongst diterpenoid alkaloids of interest. A usefulness of such approach has been assessed and it proved to give reliable results on whether a particular diterpenoid alkaloid is likely to be either poison or drug. A number of QSAR models with "drug-likeness" descriptors have also been obtained and discussed in terms of their relativity to the mode of toxic action exhibited by the alkaloids. The QSAR models were obtained with r value in the range 0.69-0.94. The q(2) (cross validation of r(2)) values also confirm the statistical significance of our models.

A QSAR toxicity study of a series of alkaloids with the lycoctonine skeleton.

A QSAR toxicity analysis has been performed for a series of 19 alkaloids with the lycoctonine skeleton. GA-MLRA (Genetic Algorithm combined with Multiple Linear Regression Analysis) technique was applied for the generation of two types of QSARs: first, models containing exclusively 3D-descriptors and second, models consisting of physicochemical descriptors. As expected, 3D-descriptor QSARs have better statistical fits. Physicochemical-descriptor containing models, that are in a good agreement with the mode of toxic action exerted by the alkaloids studied, have also been identified and discussed. In particular, TPSA (Topological Polar Surface Area) and nC=O (number of -C(O)- fragments) parameters give the best statistically significant mono- and bidescriptor models (when combined with lipophilicity, MlogP) confirming the importance of H-bonding capability of the alkaloids for binding at the receptor site.