Optimal descriptors calculated with Simplified Molecular Input Line Entry System (SMILES) notation have been used in quantitative structure-property relationships (QSPR) of half-wave potential of N-benzylsalicylthioamides. The QSPR developed is one-variable model based on the optimal descriptors calculated with the Monte Carlo method. The approach has been checked up with three random splits in...

Quantitative Structure Activity/Property Relationship (QSAR/QSPR) model development is a complex and time-consuming procedure involving data gathering and preparation. It plays an important role in the drug discovery pipeline, which still is mostly done manually. The current paper describes the automated workflow support of the OpenMolGRID system and provides a case study for the automation of ...

A model developed to predict aqueous solubility at different temperatures has been proposed based on quantitative structure-property relationships (QSPR) methodology. The prediction consists of two steps. The first one predicts the value of k parameter in the linear equation lgSw=kT+c, where Sw is the value of solubility and T is the value of temperature. The second step uses Random Forest tech...

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...

Quantitative Structure-Property Relationships (QSPR) are predictive methods of macroscopic properties of substances based on their only molecular structures. If these methods were initially mainly devoted to biology and toxicology, they are nowadays increasingly used for the prediction of physico-chemical properties. In the framework of the European REACH regulation (2006), their developments a...

A QSPR (quantitative structure-property relationship) model for the estimation of the liquid viscosity of a large variety of organic compounds was established using the CODESSA (comprehensive descriptors for structural and statistical analysis) approach. The final model was developed with a calibration set containing 337 compounds. The multilinear regression (MLR) equation that relates ln η to ...

SMILES strings are the most compact text based molecular representations. Implicitly they contain the information needed to compute all kinds of molecular structures and, thus, molecular properties derived from these structures. We show that this implicit information can be accessed directly at SMILES string level without the need to apply explicit time-consuming conversion of the SMILES string...

Dermal absorption of topically applied chemicals usually occurs from complex chemical mixtures; yet, most attempts to quantitate dermal permeability use data collected from single chemical exposure in aqueous solutions. The focus of this research was to develop quantitative structure permeation relationships (QSPR) for predicting chemical absorption from mixtures through skin using two levels o...

Ketones are one of the most common functional groups, and ketone-containing compounds are essential in both the nature and the chemical sciences. As such, the acidities (pKa) of ketones provide valuable information for scientists to screen for biological activities, to determine physical properties or to study reaction mechanisms. Direct measurements of pKa of ketones are not readily available ...

Quantitative structure-property relationships (QSPRs) for estimating the logarithm octanol/water partition coefficients, logK(ow), at 25 degrees C were developed based on fuzzy ARTMAP and back-propagation neural networks using a heterogeneous set of 442 organic compounds. The set of molecular descriptors were derived from molecular connectivity indices and quantum chemical descriptors calculate...