Excito-repellent and Pesticide-Likeness Properties of Essential Oils on (Fabricius) (Nitidulidae) and (L.) (Silvanidae).

(Fabricius) (Nitidulidae) and (L.) (Silvanidae) are insect pests that cause severe damage in important walnut growing regions in the northwest of Argentina. The current management approaches for these pests involve the use of unsafe phosphorus pesticides whose overuse have led to farmworker poisoning, pest resistance issues, and environmental contamination.

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.

QSAR Study of Biologically Active Essential Oils against Beetles Infesting the Walnut in Catamarca, Argentina.

Essential oils from six species of aromatic plants collected in the Catamarca Province of Argentina were evaluated for their chemical composition and repellent and insecticidal activities against beetles of the genus Carpophilus (Coleoptera: Nitidulidae) and Oryzaephilus (Coleoptera: Silvanidae) that infest the local walnut production. Experimental data were analyzed using generalized estimating equations, with normal distribution and the identity link function. From the spectral information from the tested essential oils, we worked their molecular modeling as mixtures by developing mixture descriptors ( D) that combined the molecular descriptor of each component in the mixture ( d ) and its relative concentration ( x ), i.

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 ) 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.

Application of quantitative structure-property relationship analysis to estimate the vapor pressure of pesticides.

The application of molecular descriptors in describing Quantitative Structure Property Relationships (QSPR) for the estimation of vapor pressure (VP) of pesticides is of ongoing interest. In this study, QSPR models were developed using multiple linear regression (MLR) methods to predict the vapor pressure values of 162 pesticides. Several feature selection methods, namely the replacement method (RM), genetic algorithms (GA), stepwise regression (SR) and forward selection (FS), were used to select the most relevant molecular descriptors from a pool of variables.

QSAR study for carcinogenicity in a large set of organic compounds.

In our continuing efforts to find out acceptable Absorption, Distribution, Metabolization, Elimination and Toxicity (ADMET) properties of organic compounds, we establish linear QSAR models for the carcinogenic potential prediction of 1464 compounds taken from the "Galvez data set", that include many marketed drugs. More than a thousand of geometry-independent molecular descriptors are simultaneously analyzed, obtained with the softwares E-Dragon and Recon. The variable subset selection method employed is the Replacement Method, and also the improved version Enhanced Replacement Method.

Quantitative structure-activity relationships of mosquito larvicidal chalcone derivatives.

The mosquito larvicidal activities of a series of chalcones and some derivatives were subjected to a quantitative structure-activity relationship (QSAR) study, using more than a thousand constitutional, topological, geometrical, and electronic molecular descriptors calculated with Dragon software. The larvicidal activity values for 28 active compounds of the series were predicted, showing in general a good approximation to the experimental values found in the literature. Chalcones having one or both electron-rich rings showed high toxicity.

Prediction of drug intestinal absorption by new linear and non-linear QSPR.

In order to minimize the high attrition rate that usually characterizes drug research and development projects, current medicinal chemists aim to characterize both pharmacological and ADME profiles at the beginning of drug R&D initiatives. Thus, the development of ADME High-Throughput Screening in vitro and in silico ADME models has become an important growing research area. Here we present new linear and non-linear predictive QSPR models to predict the human intestinal absorption rate, which are derived from a medium sized, balanced and diverse training set of organic compounds.