A quantitative structure-activity relationship (QSAR) study of dermal absorption using theoretical molecular descriptors

Subhash C Basak; D. Mills; M. M. Mumtaz

doi:10.1080/10629360601033671

A quantitative structure-activity relationship (QSAR) study of dermal absorption using theoretical molecular descriptors

Subhash C Basak, D. Mills, M. M. Mumtaz

Natural Resources Research Institute

Research output: Contribution to journal › Article › peer-review

41 Scopus citations

Abstract

Quantitative structure-activity relationship (QSAR) models were developed for the prediction of dermal absorption based on experimental logK_p data for a diverse set of 101 chemicals obtained from the literature. Molecular descriptors including topostructural (TS), topochemical (TC), shape or three-dimensional (3D) and quantum chemical (QC) indices were calculated. Based on this information, a generic predictive model was created using the diverse set of 101 compounds. In addition, two submodels were prepared for subsets of 79 cyclic and 22 acyclic chemicals. A modified Gram-Schmidt variable reduction algorithm for descriptor thinning was followed by regression analyses using ridge regression (RR), principal components regression (PCR) and partial least squares regression (PLS). The RR results were found to be superior to PLS and PCR regressions. The cross-validated correlation coefficients for the full set and subsets were 0.67-0.87. Computational methods such as QSAR modelling can be used to augment existing data to prioritise chemicals that need to be studied further for toxicological evaluation and risk assessment.

Original language	English (US)
Pages (from-to)	45-55
Number of pages	11
Journal	SAR and QSAR in environmental research
Volume	18
Issue number	1-2
DOIs	https://doi.org/10.1080/10629360601033671
State	Published - Jan 2007

Bibliographical note

Funding Information:
This article represents contribution number 416 from the Center for Water and the Environment of the Natural Resources Research Institute. Research was supported by the Agency for Toxic Substances and Disease Registry, Cooperative Agreement Number 572112. The authors gratefully acknowledge Dr. Selene Chou for helpful discussions.

Keywords

Dermal absorption
Gram-Schmidt orthogonalization
Ridge regression
Topological descriptors

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10.1080/10629360601033671

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abstract = "Quantitative structure-activity relationship (QSAR) models were developed for the prediction of dermal absorption based on experimental logKp data for a diverse set of 101 chemicals obtained from the literature. Molecular descriptors including topostructural (TS), topochemical (TC), shape or three-dimensional (3D) and quantum chemical (QC) indices were calculated. Based on this information, a generic predictive model was created using the diverse set of 101 compounds. In addition, two submodels were prepared for subsets of 79 cyclic and 22 acyclic chemicals. A modified Gram-Schmidt variable reduction algorithm for descriptor thinning was followed by regression analyses using ridge regression (RR), principal components regression (PCR) and partial least squares regression (PLS). The RR results were found to be superior to PLS and PCR regressions. The cross-validated correlation coefficients for the full set and subsets were 0.67-0.87. Computational methods such as QSAR modelling can be used to augment existing data to prioritise chemicals that need to be studied further for toxicological evaluation and risk assessment.",

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note = "Funding Information: This article represents contribution number 416 from the Center for Water and the Environment of the Natural Resources Research Institute. Research was supported by the Agency for Toxic Substances and Disease Registry, Cooperative Agreement Number 572112. The authors gratefully acknowledge Dr. Selene Chou for helpful discussions.",

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KW - Topological descriptors

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A quantitative structure-activity relationship (QSAR) study of dermal absorption using theoretical molecular descriptors

Abstract

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