QSAR modelling of water quality indices of alkylphenol pollutants
The aim of this study was to determine the degradability of 26 Alkylphenols (APs) by Chemical Oxygen Demand (COD) and/or 5-day Biochemical Oxygen Demand (BOD5), and to describe these data from Quantitative Structure-activity Relationships (QSARs). Statistical analysis techniques, such
as Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least-Squares (PLS) Regression and Neural Network (NN) were carried out to calibrate and validate four-descriptor QSAR models using two different types of descriptor sets. Stable MLR-QSAR models using Leave-One-Out
(LOO) were obtained with high predictability performance: r2 = 0.924, [image omitted] = 0.854 for log (1/BOD) model on 24 APs and r2 = 0.888, [image omitted] = 0.818 for log (1/COD) on all the studied APs. The MLR models, built with four Dragon descriptors selected by Genetic Algorithm
(GA), presented the following performances on 24 APs: r2 = 0.889, [image omitted] = 0.848 for log (1/BOD5) and r2 = 0.885, [image omitted] = 0.834 for log (1/COD) on 26 compounds. From these results, it is expected that the QSAR models generated could be successfully expanded to
predict the biological and chemical activities of structurally diverse AP compounds.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Department of Health Science, School of Natural Science, Dongduk Women's University, Seoul, Korea
QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Structural and Functional Biology (DBSF), University of Insubria, Varese, Italy
Gyeonggi-do Public Health and Enviroment Research Institute 324-1 Pajang-dong, Gyeonggi, Korea
Department of Data and Information, Division of Computer Science and Information, Dongduk Women's University, Seoul, Korea
Department of Environmental and Biomolecular Systems, Oregon Health and Science University, Beaverton, OR, USA
Publication date: December 1, 2007