Prediction of the Deral Penetration of Polycyclic Aromatic Hydrocarbons (PAHs): A hierarchical Qsar Approach

Abstract

Attempts were made to develop hierarchical quantitative structure-activity relationship (QSAR) models for the dermal penetration of polycyclic aromatic hydrocarbons (PAHs) using four classes of theoretical structural parameters; viz., topostructural, topochemical, geometric, and quantum chemical descriptors; and physicochemical properties such as molecular weight (MW) and lipophilicity (log P--octanol/water). The results show that topostructural, topochemical, and geometric descriptors and molecular weight are equally effective in predicting the dermal penetration of PAHs. Quantum chemical parameters did not make any improvements in the predictive power of the QSAR models.

Development of quantitative structure-activity relationship models for vapor pressure estimation using computed molecular descriptors

“…Basak et al formulated the hierarchical quantitative structure-activity relationship (HiQSAR) approach for the estimation of properties, biomedicinal activities, and toxicities of chemicals from computed descriptors. [6][7][8][9][10][11][12][13][14][15][16][17][18] The objective of this HiQSAR/ HiQSPR research has been twofold: description and prediction. The HiQSPR formalism uses progressively more complex indices in the development of models.…”

Quantitative Characterization of Molecular Similarity Spaces: Tools for Computational Toxicology

“…Recently, we have advocated the use of a "hierarchical QSAR approach" involving the TSI, TCI, geometrical, and quantum chemical indices in the successful development of predictive models. 67 " 71 In comparing our study to the work of Hanch and Yoshimoto, 47 it must be pointed out that our models did little to improve on their QSAR analysis as can be seen from However, the LFER approach used by Hansch and Yoshimoto required experimental data for all compounds in the study and significant input from a human expert for the determination of the three "structural" indicator variables. One strength of our approach to this problem is the use of nonempirical theoretical descriptors which can be calculated solely from the chemical structure.…”

“…As a result of this dramatic increase in classification rate for non-mutagens, this model was retained and supplemented by the geometrical indices. Addition of the geometric indices brought the classification rate for mutagens up to 71.5% (an overall decrease of 4.7% from the topostructural model) and retained the classification rate for non-mutagens at 71.9% (an overall increase of 14.6% over the initial model). While these results are by no means spectacular, it is a reasonably accurate model for the prediction of mutagenic activity.…”

Use of Graph Invariants in Quantitative Structure-Activity Relationship Studies

“…Recent review of results of HiQSARs carried out by Basak and coworkers [2,[38][39][40] using topostructural, topochemical, 3-D, and quantum chemical indices for diverse properties, e.g., acute toxicity of benzene derivatives, dermal penetration of polycyclic aromatic hydrocarbons (PAHs), mutagenicity of a congeneric set of amines (heteroaromatic and aromatic) and others indicate that in most of the above mentioned cases TS + TC combination of indices give reasonable predictive models. The addition of 3-D and quantum chemical indices after the use of TS and TC descriptors did very little improvement in model quality.…”