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The Use of the Index of Ideality of Correlation to Build Up Models for Bioconcentration Factor
Author(s) -
Toropova Alla P.,
Duchowicz Pablo R.,
Saavedra Laura M.,
Castro Eduardo A.,
Toropov Andrey A.
Publication year - 2020
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201900070
Subject(s) - bioconcentration , quantitative structure–activity relationship , molecular descriptor , linear regression , set (abstract data type) , correlation , biological system , computer science , mathematics , data mining , statistics , chemistry , machine learning , environmental chemistry , biology , bioaccumulation , geometry , programming language
We 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, Mold 2 , 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.