Abstract
The in silico modelling of bio-concentration factor (BCF) is of considerable interest in environmental sciences, because it is an accepted indicator for the accumulation potential of chemicals in organisms. Numerous QSAR models have been developed for the BCF, and the majority utilize the octanol/water partition coefficient (logP) to account for the penetration characteristics of the chemicals. The present work used descriptors from a variety of software packages for the development of a multi-linear regression model to estimate BCF. The modelled data set of 473 diverse compounds covers a wide range of log BCF values. In the proposed QSAR model, most of the variation is described by the calculated solubility in water. Other contributing descriptors describe, for instance, hydrophobic surface area, hydrogen bonding and other electronic effects. The model was validated internally by using a variety of statistical approaches. Two external validations were also performed. For the former validation, a subset from the same data source was used. The 2nd external validation was based on an independent data set collected from different resources. All validations showed the consistency of the model. The applicability domain of the model was discussed and described and a thorough outlier analysis was performed.
| Original language | English |
|---|---|
| Pages (from-to) | 711-729 |
| Number of pages | 19 |
| Journal | SAR and QSAR in Environmental Research |
| Volume | 21 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Oct 2010 |
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Keywords
- Applicability domain
- BCF
- Bioconcentration
- QSAR
- Solubility
ASJC Scopus subject areas
- Molecular Medicine
- Bioengineering
- Drug Discovery
Cite this
QSAR model for the prediction of bio-concentration factor using aqueous solubility and descriptors considering various electronic effects. / Piir, G.; Sild, S.; Roncaglioni, A.; Benfenati, E.; Maran, U.
In: SAR and QSAR in Environmental Research, Vol. 21, No. 7, 10.2010, p. 711-729.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - QSAR model for the prediction of bio-concentration factor using aqueous solubility and descriptors considering various electronic effects
AU - Piir, G.
AU - Sild, S.
AU - Roncaglioni, A.
AU - Benfenati, E.
AU - Maran, U.
PY - 2010/10
Y1 - 2010/10
N2 - The in silico modelling of bio-concentration factor (BCF) is of considerable interest in environmental sciences, because it is an accepted indicator for the accumulation potential of chemicals in organisms. Numerous QSAR models have been developed for the BCF, and the majority utilize the octanol/water partition coefficient (logP) to account for the penetration characteristics of the chemicals. The present work used descriptors from a variety of software packages for the development of a multi-linear regression model to estimate BCF. The modelled data set of 473 diverse compounds covers a wide range of log BCF values. In the proposed QSAR model, most of the variation is described by the calculated solubility in water. Other contributing descriptors describe, for instance, hydrophobic surface area, hydrogen bonding and other electronic effects. The model was validated internally by using a variety of statistical approaches. Two external validations were also performed. For the former validation, a subset from the same data source was used. The 2nd external validation was based on an independent data set collected from different resources. All validations showed the consistency of the model. The applicability domain of the model was discussed and described and a thorough outlier analysis was performed.
AB - The in silico modelling of bio-concentration factor (BCF) is of considerable interest in environmental sciences, because it is an accepted indicator for the accumulation potential of chemicals in organisms. Numerous QSAR models have been developed for the BCF, and the majority utilize the octanol/water partition coefficient (logP) to account for the penetration characteristics of the chemicals. The present work used descriptors from a variety of software packages for the development of a multi-linear regression model to estimate BCF. The modelled data set of 473 diverse compounds covers a wide range of log BCF values. In the proposed QSAR model, most of the variation is described by the calculated solubility in water. Other contributing descriptors describe, for instance, hydrophobic surface area, hydrogen bonding and other electronic effects. The model was validated internally by using a variety of statistical approaches. Two external validations were also performed. For the former validation, a subset from the same data source was used. The 2nd external validation was based on an independent data set collected from different resources. All validations showed the consistency of the model. The applicability domain of the model was discussed and described and a thorough outlier analysis was performed.
KW - Applicability domain
KW - BCF
KW - Bioconcentration
KW - QSAR
KW - Solubility
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UR - http://www.scopus.com/inward/citedby.url?scp=78649771398&partnerID=8YFLogxK
U2 - 10.1080/1062936X.2010.528596
DO - 10.1080/1062936X.2010.528596
M3 - Article
C2 - 21120758
AN - SCOPUS:78649771398
VL - 21
SP - 711
EP - 729
JO - SAR and QSAR in Environmental Research
JF - SAR and QSAR in Environmental Research
SN - 1062-936X
IS - 7
ER -