Abstract
Water solubility is an important characteristic of a chemical in many aspects. However experimental definition of the endpoint for all substances is impossible. In this study quantitative structure-property relationships (QSPRs) for negative logarithm of water solubility-logS (molL-1) are built up for five random splits into the sub-training set (≈55%), the calibration set (≈25%), and the test set (≈20%). Simplified molecular input-line entry system (SMILES) is used as the representation of the molecular structure. Optimal SMILES-based descriptors are calculated by means of the Monte Carlo method using the CORAL software (http://www.insilico.eu/coral). These one-variable models for water solubility are characterized by the following average values of the statistical characteristics: nsub_train=725-763; ncalib=312-343; ntest=231-261; rsub_train2=0.9211±0.0028; rcalib2=0.9555±0.0045; rtest2=0.9365±0.0073; ssub_train=0.561±0.0086; scalib=0.453±0.0209; stest=0.520±0.0205. Thus, the reproducibility of statistical quality of suggested models for water solubility confirmed for five various splits.
| Original language | English |
|---|---|
| Pages (from-to) | 877-880 |
| Number of pages | 4 |
| Journal | Chemosphere |
| Volume | 90 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Jan 2013 |
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Keywords
- CORAL software
- Monte Carlo technique
- QSPR
- Water solubility
ASJC Scopus subject areas
- Environmental Chemistry
- Chemistry(all)
Cite this
CORAL : QSPR model of water solubility based on local and global SMILES attributes. / Toropov, Andrey A.; Toropova, Alla P.; Benfenati, Emilio; Gini, Giuseppina; Leszczynska, Danuta; Leszczynski, Jerzy.
In: Chemosphere, Vol. 90, No. 2, 01.2013, p. 877-880.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - CORAL
T2 - QSPR model of water solubility based on local and global SMILES attributes
AU - Toropov, Andrey A.
AU - Toropova, Alla P.
AU - Benfenati, Emilio
AU - Gini, Giuseppina
AU - Leszczynska, Danuta
AU - Leszczynski, Jerzy
PY - 2013/1
Y1 - 2013/1
N2 - Water solubility is an important characteristic of a chemical in many aspects. However experimental definition of the endpoint for all substances is impossible. In this study quantitative structure-property relationships (QSPRs) for negative logarithm of water solubility-logS (molL-1) are built up for five random splits into the sub-training set (≈55%), the calibration set (≈25%), and the test set (≈20%). Simplified molecular input-line entry system (SMILES) is used as the representation of the molecular structure. Optimal SMILES-based descriptors are calculated by means of the Monte Carlo method using the CORAL software (http://www.insilico.eu/coral). These one-variable models for water solubility are characterized by the following average values of the statistical characteristics: nsub_train=725-763; ncalib=312-343; ntest=231-261; rsub_train2=0.9211±0.0028; rcalib2=0.9555±0.0045; rtest2=0.9365±0.0073; ssub_train=0.561±0.0086; scalib=0.453±0.0209; stest=0.520±0.0205. Thus, the reproducibility of statistical quality of suggested models for water solubility confirmed for five various splits.
AB - Water solubility is an important characteristic of a chemical in many aspects. However experimental definition of the endpoint for all substances is impossible. In this study quantitative structure-property relationships (QSPRs) for negative logarithm of water solubility-logS (molL-1) are built up for five random splits into the sub-training set (≈55%), the calibration set (≈25%), and the test set (≈20%). Simplified molecular input-line entry system (SMILES) is used as the representation of the molecular structure. Optimal SMILES-based descriptors are calculated by means of the Monte Carlo method using the CORAL software (http://www.insilico.eu/coral). These one-variable models for water solubility are characterized by the following average values of the statistical characteristics: nsub_train=725-763; ncalib=312-343; ntest=231-261; rsub_train2=0.9211±0.0028; rcalib2=0.9555±0.0045; rtest2=0.9365±0.0073; ssub_train=0.561±0.0086; scalib=0.453±0.0209; stest=0.520±0.0205. Thus, the reproducibility of statistical quality of suggested models for water solubility confirmed for five various splits.
KW - CORAL software
KW - Monte Carlo technique
KW - QSPR
KW - Water solubility
UR - http://www.scopus.com/inward/record.url?scp=84869885324&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84869885324&partnerID=8YFLogxK
U2 - 10.1016/j.chemosphere.2012.07.035
DO - 10.1016/j.chemosphere.2012.07.035
M3 - Article
C2 - 22921649
AN - SCOPUS:84869885324
VL - 90
SP - 877
EP - 880
JO - Chemosphere
JF - Chemosphere
SN - 0045-6535
IS - 2
ER -