Description of the Electronic Structure of Organic Chemicals Using Semiempirical and Ab Initio Methods for Development of Toxicological QSARs

Abstract

The quality of quantitative structure-activity relationship (QSAR) models depends on the quality of their constitutive elements including the biological activity, statistical procedure applied, and the physicochemical and structural descriptors. The aim of this study was to assess the comparative use of ab initio and semiempirical quantum chemical calculations for the development of toxicological QSARs applied to a large and chemically diverse data set. A heterogeneous collection of 568 organic compounds with 96 h acute toxicity measured to the fish fathead minnow (Pimephales promelas) was utilized. A total of 162 descriptors were calculated using the semiempirical AM1 Hamiltonian, and 121 descriptors were compiled using an ab initio (B3LYP/6-31G**) method. The QSARs were derived using multiple linear regression (MLR) and partial least squares (PLS) analyses. Statistically similar models were obtained using AM1 and B3LYP calculated descriptors supported by the use of the logarithm of the octanol-water partition coefficient (log K ow). The main difference between the models derived by both MLR and PLS with the two sets of quantum chemical descriptors was concentrated on the type of descriptors selected. It was concluded that for large-scale predictions, irrespective of the mechanism of toxic action, the use of precise but time-consuming ab initio methods does not offer considerable advantage compared to the semiempirical calculations and could be avoided.

Review of (Quantitative) Structure–Activity Relationships for Acute Aquatic Toxicity

“…To compare the robustness of different methods (ab initio and semi-empirical) for calculation of electronic descriptors, a best subset analysis was performed (outliers not excluded) with log K ow and two sets of descriptors [4]. The authors found that the more computer-intensive ab initio calculations do not offer significant improvement when used in models for fish toxicity but different descriptors (suggesting different posteriori mechanistic interpretation) were selected.…”

Guidance Document on the Validation of (Quantitative) Structure-Activity Relationship [(Q)SAR] Models

“…Successful examples of more novel applications of MLR are in the papers: Netzeva et al, 2005;Ren S., 2003;Ghafourian and Cronin, 2005. In some recent publications, particular attention is devoted to model validation for predictivity and chemical domain of applicability, as well as to the descriptor interpretation, thus to the model development according to all the OECD Principles Pavan et al, 2006).…”

Joint Toxicity Evaluation and QSAR Modeling of Aromatic Amines and Phenols to Bacteria

“…Also, the nitro substituent seems to be more toxic than chlorine substituent. For the purpose of comparison, the 15 min Chlorella vulgaris EC 50 values of anilines (Netzeva et al 2004) and the 96 h fathead minnow LC 50 values of anilines and phenols (Netzeva et al 2005) are also shown in Table 1. When the toxicity of five anilines on bacteria was compared with those from C. vulgaris, all the chemicals tested exhibited higher toxicity on bacteria than on C. vulgaris.…”