3D-QSAR predictions for bovine serum albumin–water partition coefficients of organic anions using quantum mechanically based descriptors. Issue 3 (22nd December 2016)

• Record Type: Journal Article
• Authors: Linden, Lukas; Goss, Kai-Uwe; Endo, Satoshi
• Is Part Of: Environmental science. Volume 19:Issue 3(2017)
• Page Start: 261
• Page End: 269
• Publication Date: 2016-12-22
• Subjects: Environmental monitoring -- Periodicals; Biological monitoring -- Periodicals; Environmental chemistry -- Periodicals; 363.7363
• DOI: 10.1039/c6em00555a
• Languages: English
• ISSNs: 2050-7887

Abstract

Abstract : The 3D-QSAR model predicts the bovine serum albumin–water partition coefficients for neutral and anionic chemicals influenced by steric effects. Abstract : Ionic organic chemicals are a class of chemicals that is released in the environment in a large amount from anthropogenic sources. Among various chemical and biological processes, binding to serum albumin is particularly relevant for the toxicokinetic behavior of ionic chemicals. Several experimental studies showed that steric effects have a crucial influence on the sorption to bovine serum albumin (BSA). In this study, we investigated whether a 3D quantitative structure–activity relationship (3D-QSAR) model can accurately account for these steric effects by predicting the BSA–water partition coefficients ( K BSA/water ) of neutral and anionic organic chemicals. The 3D-QSAR tested here uses quantum mechanically derived local sigma profiles as descriptors. In general, the 3D-QSAR model was able to predict the partition coefficients of neutral and anionic chemicals with an acceptable quality (RMSEtest set 0.63 ± 0.10, R test set 2 0.52 ± 0.15, both for log K BSA/water ). Particularly notable is that steric effects that cause a large difference in the log K BSA/water values between isomers were successfully reproduced by the model. The prediction of unknown K BSA/water values with the proposed model should contribute to improved environmental and toxicological assessments of chemicals.