TITLE:
Prediction of the Hydrophobic Character of Aromatic Amines by Quantum Chemistry and QSPR Methods: The Case of Aniline and Its Derivatives
AUTHORS:
Fatogoma Diarrassouba, Kafoumba Bamba, Nahossé Ziao
KEYWORDS:
Quantum Chemistry, QSPR Model, Statistical Data Analysis, Aniline
JOURNAL NAME:
Computational Chemistry,
Vol.14 No.4,
September
18,
2026
ABSTRACT: This study established a relationship between the water/octanol partition coefficient (LogP) and molecular descriptors from quantum chemistry using a QSPR approach. To this end, a QSPR model based on three molecular descriptors, namely ionization energy (IE), total electronic energy (ET), and dipole moment (μ), was developed. To evaluate the quality, robustness, and predictive power of the resulting model, several statistical and validation parameters were calculated (
R
2
=0.9501
;
R
adjusted
2
=0.9386
; s = 0.2000; F = 82.5446;
Q
LOO
2
=0.9149
;
r
m
2
(
LOO
)
¯
=0.6651
;
Δ
r
m
2
(
LOO
)=0.0000
;
Q
ext
2
=0.9825
;
r
m
2
(
test
)
¯
=0.9013
;
Δ
r
m
2
(
test
)=0.0787
). The values obtained for these different indicators reveal that the developed QSPR model is valid, robust, and efficient for predicting the water/octanol partition coefficient of the studied anilines. This model can therefore be applied to estimate the hydrophobic character of other compounds belonging to the same chemical family, provided they fall within its range of applicability. Consequently, the design of new anilines with specific water/octanol partition coefficients could be facilitated by modulating the three molecular descriptors included in the developed QSPR model.