QSPR-based estimation of the half-lives for polychlorinated biphenyl congeners

Abstract

In this study, the depuration half-lives of 62 polychlorinated biphenyl (PCB) congeners in juvenile rainbow trout (Oncorhynchus mykiss) were estimated from their structural features based on QSPR methodology. A genetic algorithm (GA) was applied as a variable subset selection strategy and QSPR models established upon multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and support vector regression (SVR) procedures. Robustness and predictive stability of the constructed models were evaluated through internal and external validation methods. The high numerical values of [Formula: see text] and [Formula: see text], and low RMSE in the case of the MLP NN model, confirm the supremacy of this model as well as nonlinear dependency of molecular structural features to the PCB congeners half-lives. In the best developed QSPR model the following four descriptors are used; lopping centric index (Lop), mean topological charge index of order 1 (JGI1), Geary autocorrelation lag-8/weighted by atomic Sanderson electronegativities (GATS8e) and highest eigenvalue of Burden matrix/weighted by atomic masses (BEHm3). Analysis of the descriptors involved in these models revealed that 2D molecular structural features, compactness and electronegativities are the main factors contributing to the half-lives of PCBs. The structural information presented in this work can be used for further evaluation of half-lives of PCBs and other similar structural compounds in the environment.

Prediction of Depuration Rate Constants for Polychlorinated Biphenyl Congeners

“…Because the PCB congeners possess similar molecular structures, the range of the k d values is relatively narrow. This phenomenon can be found in other properties. , Therefore, the QSAR models based on PCBs can only be used for the prediction of the properties of PCBs.…”

“…The coefficients of determination R 2 from the training set including 43 PCBs are 0.855–0.921. These models are accurate and acceptable …”

“…Descriptor calculation is a key step toward developing QSAR models. All these QSAR models stated above are based on the descriptors obtained from a single molecule in vacuum and gas phase. − Due to the solvent effect, the geometrical structure, frontier orbital energy, and charge distribution of solute molecules in gas and solution may be different, which affect the dissolution and chemical reactions of solutions . In this paper, the integral equation formalism polarizable continuum model (IEF-PCM) was adopted to model the solvent effects in molecular geometry optimization.…”

“…These models are accurate and acceptable. 13 Descriptor calculation is a key step toward developing QSAR models. All these QSAR models stated above are based on the descriptors obtained from a single molecule in vacuum and gas phase.…”

Model-Based Quantum-Chemical Study of the Uptake of Some Polychlorinated Pollutant Compounds by Zucchini Subspecies

“…Jäntschi et al developed a genetic algorithm in order to select pairs of proper structural descriptors able to estimate and predict octanol-water partition coefficients of 206 polychlorinated biphenyls 17 . Other properties, such as depuration rates and toxicity have been also the subject of several QSAR analysis [18][19][20][21][22][23] .…”