We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds by means of Quantitative Structure-Property Relationships (QSPR). A conformation-independent representation of the chemical structure is established. The 17,538molecular descriptors derived with PaDEL and EPI Suite softwares are simultaneously analyzed through linear regressions obtained with the Replacement Method variable subset selection technique. The best predictive three-descriptors QSPR is developed on a reduced training set of 93 chemicals, having an acceptable predictive capability on 550 test set compounds. We also establish a model with a single optimal descriptor derived from CORAL freeware. The present approach compares fairly we...
Soil sorption coefficients for nonpolar compounds can easily be modeled with log P(OW)or with connec...
A Quantitative Structure-Property Relationships (QSPRs) study for the prediction of the environmenta...
Quantitative structure-property relationship (QSPR) models were derived for predicting boiling point...
We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds ...
The soil sorption coefficient (Koc) is a key physicochemical parameter to assess the environmental r...
Quantitative structure–property relationship (QSPR) modelling has been used in many scientific field...
The soil sorption partition coefficient (log Koc) of a heterogeneous set of 643 organic non-ionic co...
Several recent studies have shown that n-octanol/water partition coefficients may not be a good pred...
Quantitative Structure-Property Relationship (QSPR) technique was used to develop a simple predictiv...
International audienceA comprehensive review of quantitative structure-activity relationships (QSAR)...
Using a general theory for partition coefficients based on a quantum chemically derived conductor-li...
Soil sorption coefficients for nonpolar compounds can easily be modeled with log P(OW)or with connec...
A Quantitative Structure-Property Relationships (QSPRs) study for the prediction of the environmenta...
Quantitative structure-property relationship (QSPR) models were derived for predicting boiling point...
We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds ...
The soil sorption coefficient (Koc) is a key physicochemical parameter to assess the environmental r...
Quantitative structure–property relationship (QSPR) modelling has been used in many scientific field...
The soil sorption partition coefficient (log Koc) of a heterogeneous set of 643 organic non-ionic co...
Several recent studies have shown that n-octanol/water partition coefficients may not be a good pred...
Quantitative Structure-Property Relationship (QSPR) technique was used to develop a simple predictiv...
International audienceA comprehensive review of quantitative structure-activity relationships (QSAR)...
Using a general theory for partition coefficients based on a quantum chemically derived conductor-li...
Soil sorption coefficients for nonpolar compounds can easily be modeled with log P(OW)or with connec...
A Quantitative Structure-Property Relationships (QSPRs) study for the prediction of the environmenta...
Quantitative structure-property relationship (QSPR) models were derived for predicting boiling point...