Characterization of Skin Penetration Processes of Organic Molecules Using Molecular Similarity and QSAR Analysis
Osvaldo A. Santos‐Filho, A. J. Hopfinger, Tao Zheng
Abstract
Osvaldo A. Santos‐Filho, A. J. Hopfinger, Tao Zheng
Abstract
Molecular similarity and QSAR analyses have been used to develop compact, robust, and definitive models for skin penetration by organic compounds. The QSAR models have been sought to provide an interpretation and characterization of plausible molecular mechanisms of skin penetration. A training set of 40 structurally diverse compounds were selected to be representative of a parent set of 152 compounds in terms of both structural diversity and range in measured skin penetration. The subset of 40 compounds was used in a series of QSAR analyses in the search for the most significant, compact, and straightforward skin penetration QSAR models. Molecular dynamics simulations were employed to determine a set of MI (membrane-interaction) descriptors for each test compound (solute) interacting with a model DMPC monolayer membrane model. The MI-QSAR models may capture features of cellular membrane lateral transverse transport involved in the overall skin penetration process by organic compounds. An additional set of intramolecular solute descriptors, the non-MI-QSAR descriptors, were computed and added to the trial pool of descriptors for building QSAR models. All QSAR models were constructed using multidimensional linear regression fitting and a genetic algorithm optimization function. QSAR models were constructed using only non-MI-QSAR descriptors and using a combination of both these descriptor sets. It was found that a combination of non-MI-QSAR and MI-QSAR descriptors yielded the optimum models, not only with respect to the statistical measures of fit but also regarding model predictivity.
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Molecular similarity and QSAR analyses have been used to develop compact, robust, and definitive models for skin penetration by organic compounds. The QSAR models have been sought to provide an interpretation and characterization of plausible molecular mechanisms of skin penetration. A training set of 40 structurally diverse compounds were selected to be representative of a parent set of 152 compounds in terms of both structural diversity and range in measured skin penetration. The subset of 40 compounds was used in a series of QSAR analyses in the search for the most significant, compact, and straightforward skin penetration QSAR models. Molecular dynamics simulations were employed to determine a set of MI (membrane-interaction) descriptors for each test compound (solute) interacting with a model DMPC monolayer membrane model. The MI-QSAR models may capture features of cellular membrane lateral transverse transport involved in the overall skin penetration process by organic compounds. An additional set of intramolecular solute descriptors, the non-MI-QSAR descriptors, were computed and added to the trial pool of descriptors for building QSAR models. All QSAR models were constructed using multidimensional linear regression fitting and a genetic algorithm optimization function. QSAR models were constructed using only non-MI-QSAR descriptors and using a combination of both these descriptor sets. It was found that a combination of non-MI-QSAR and MI-QSAR descriptors yielded the optimum models, not only with respect to the statistical measures of fit but also regarding model predictivity.
Key concepts: Quantitative structure–activity relationship, Molecular descriptor, Biological system, Chemistry, Applicability domain, Computational chemistry, Stereochemistry, Biology