
AbstractWe establish a QSPR analysis for the bioconcentration factor of 851 heterogeneous structural compounds. Linear models are proposed via two different approaches: i. the optimal descriptor method implemented in CORAL, and ii. multivariable linear regressions on the best molecular descriptors found with the Replacement Method on 44,216 structural descriptors. Such variables are derived with different freely available softwares, such as PaDEL, PyDescriptor, Mold2, QuBiLs‐MAS and ISIDA/Fragmentor. The same validation set is employed in order to compare the predictive performance between the so‐obtained CORAL and RM based models. Finally, the comparison of several models for the bioconcentration factor confirms the ability of the so‐called index of ideality of correlation to be a criterion of predictive potential in Quantitative Structure‐Property Relationships.
Models, Molecular, BIOCONCENTRATION FACTOR, MOLECULAR DESCRIPTORS, Statistics as Topic, Quantitative Structure-Activity Relationship, Bioaccumulation, MONTE CARLO METHOD, QSPR, CORAL SOFTWARE, https://purl.org/becyt/ford/1.4, https://purl.org/becyt/ford/1, INDEX OF IDEALITY OF CORRELATION, REPLACEMENT METHOD
Models, Molecular, BIOCONCENTRATION FACTOR, MOLECULAR DESCRIPTORS, Statistics as Topic, Quantitative Structure-Activity Relationship, Bioaccumulation, MONTE CARLO METHOD, QSPR, CORAL SOFTWARE, https://purl.org/becyt/ford/1.4, https://purl.org/becyt/ford/1, INDEX OF IDEALITY OF CORRELATION, REPLACEMENT METHOD
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