QSPR modeling of octanol-water partition coefficient and organic carbon normalized sorption coefficient of diverse organic chemicals using Extended Topochemical Atom (ETA) indices
نویسندگان
چکیده
منابع مشابه
Estimation of the soil-water partition coefficient normalized to organic carbon for ionizable organic chemicals.
The sorption of organic electrolytes to soil was investigated. A dataset consisting of 164 electrolytes, composed of 93 acids, 65 bases, and six amphoters, was collected from literature and databases. The partition coefficient log Kow of the neutral molecule and the dissociation constant pKa were calculated by the software ACD/Labs. The Henderson-Hasselbalch equation was applied to calculate di...
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The present work establishes a quantitative structure-property relationship (QSPR) between topochemical features and odor threshold (OT) of aliphatic alcohols. A data set of 53 aliphatic alcohols was chosen for the analysis employing different chemometric techniques, among which, genetic function approximation with spline option (GFA-spline) showed the most acceptable results in terms of intern...
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A new possibility for estimating the octanol/water coefficient (log P) was investigated using only one descriptor, the semi-empirical electrotopological index (I(SET)). The predictability of four octanol/water partition coefficient (log P) calculation models was compared using a set of 131 aliphatic organic compounds from five different classes. Log P values were calculated employing atomic-con...
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A fragment constant model for prediction of KOC was developed and evaluated with a diverse database of 592 chemicals belonging to 17 classes. The range of experimental KOC covered 7.65 log-units. The 592 chemicals were randomly divided into a training set and a testing set for model development and validation. A general model was then established using the entire database having 74 fragment con...
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A group contribution approach based on atom-type electrotopological state indices for predicting the soil sorption coefficient (log KOC) of a diverse set of 201 organic pesticides is presented. Using a training set of 143 compounds, for which the log KOC values were in the range from 0.42 to 5.31, multiple linear regression (MLR) and artificial neural networks were used to build the models. The...
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ژورنال
عنوان ژورنال: Ecotoxicology and Environmental Safety
سال: 2021
ISSN: 0147-6513
DOI: 10.1016/j.ecoenv.2020.111411