QSAR models for the fumigant activity prediction of essential oils.

The Quantitative Structure-Activity Relationships (QSAR) theory, which allows predicting the insecticidal activity of chemical compounds through calculations from the molecular structure, is applied on 23 essential oils composed of 402 structurally diverse compounds at different chemical compositions. A large number of 114,871 conformation-independent molecular descriptors are computed through different types of freely available open-source programs. Mixture descriptors are calculated based on molecular descriptors of the essential oil components and their composition. The best resulting three-descriptor linear regression models are established through the Replacement Method variable subset selection approach. The results obtained in the present work are interesting for predicting the fumigant activity of these essential oil complex mixtures, by means of simple non-conformational QSAR models.

The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants.

In advanced water treatment processes, the degradation efficiency of contaminants depends on the reactivity of the hydroxyl radical toward a target micropollutant. The present study predicts the hydroxyl radical rate constant in water (k OH) for 118 emerging micropollutants, by means of quantitative structure-property relationships (QSPR). The conformation-independent QSPR approach is employed, together with a large number of 15,251 molecular descriptors derived with the PaDEL, Epi Suite, and Mold2 freewares. The best multivariable linear regression (MLR) models are found with the replacement method variable subset selection technique. The proposed five-descriptor model has the following statistics for the training set: [Formula: see text], RMS train = 0.21, while for the test set is [Formula: see text], RMS test = 0.11. This QSPR serves as a rational guide for predicting oxidation processes of micropollutants.

QSAR on antiproliferative naphthoquinones based on a conformation-independent approach.

The antiproliferative activities of a series of 36 naphthoquinone derivatives were subjected to a Quantitative Structure-Activity Relationships (QSAR) study. For this purpose a panel of four human cancer cell lines was used, namely HBL-100 (breast), HeLa (cervix), SW-1573 (non-small cell lung) and WiDr (colon). A conformation-independent representation of the chemical structure was established in order to avoid leading with the scarce experimental information on X-ray crystal structure of the drug interaction. The 1179 theoretical descriptors derived with E-Dragon and Recon software were simultaneously analyzed through linear regression models based on the Replacement Method variable subset selection technique. The established models were validated and tested through the use of external test sets of compounds, the Leave-One-Out Cross Validation method, Y-Randomization and Applicability Domain analysis.

Sustainable synthesis of flavonoid derivatives, QSAR study and insecticidal activity against the fall armyworm, Spodoptera frugiperda (Lep.: Noctuidae).

A simple, clean, solvent-free preparation of flavones by the use of a silica-supported Preyssler heteropolyacid as reusable catalyst is described. High selectivity and very good yields (87-94%) were obtained in short reaction times (7-13 min). Bioassays for insecticidal activity against Spodoptera frugiperda were carried out with a set of flavones. Bioassays showed that some of the flavones had moderate insecticidal activity. Quantitative structure-activity relationships were established on the available data with the purpose of predicting the insecticidal activity of a number of structurally related flavones. A relationship between the molecular structure and biological activity is proposed.

QSAR analysis on Spodoptera litura antifeedant activities for flavone derivatives.

We establish useful models that relate experimentally measured biological activities of compounds to their molecular structure. The pED(50) feeding inhibition on Spodoptera litura species exhibited by aurones, chromones, 3-coumarones and flavones is analyzed in this work through the hypothesis encompassed in the Quantitative Structure-Activity Relationships (QSAR) Theory. This constitutes a first necessary computationally based step during the design of more bio-friendly repellents that could lead to insights for improving the insecticidal activities of the investigated compounds. After optimizing the molecular structure of each furane and pyrane benzoderivative with the semiempirical molecular orbitals method PM3, more than a thousand of constitutional, topological, geometrical and electronic descriptors are calculated and multiparametric linear regression models are established on the antifeedant potencies. The feature selection method employed in this study is the Replacement Method, which has proven to be successful in previous analyzes. We establish the QSAR both for the complete molecular set of compounds and also for each chemical class, so that acceptably describing the variation of the inhibitory activities from the knowledge of their structure and thus achieving useful predictive results. The main interest of developing trustful QSAR models is that these enable the prediction of compounds having no experimentally measured activities for any reason. Therefore, the structure-activity relationships are further employed for investigating the antifeedant activity on previously synthesized 2-,7-substituted benzopyranes, which do not pose any measured values on the biological expression. One of them, 2-(alpha-naphtyl)-4H-1-benzopyran-4-one, results in a promising structure to be experimentally analyzed as it has predicted pED(50)=1.162.

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. As a practical application, we used the obtained QSAR model to predict the AR inhibitory effect of newly synthesized flavonoids that present 2-, 7-substitutions in the benzopyrane backbone.

QSAR modeling of the interaction of flavonoids with GABA(A) receptor.

Experimentally assigned values to binding affinity constants of flavonoid ligands towards the benzodiazepine site of the GABA(A) receptor complex were compiled from several publications, and enabled to perform a predictive analysis based on Quantitative Structure-Activity Relationships (QSAR). The best linear model established on 78 molecular structures incorporated four molecular descriptors, selected from more than a thousand of geometrical, topological, quantum-mechanical and electronic types of descriptors and calculated by Dragon software. An application of this QSAR equation was performed by estimating the binding affinities for some newly synthesized flavonoids displaying 2-,7-substitutions in the benzopyrane backbone which still do not have experimentally measured potencies.