Cargando…

Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes

There has been considerable recent interest in employing computer models to investigate the relationship between the structure of a molecule and its dermal penetration. Molecular permeation across the epidermis has previously been demonstrated to be determined by a number of physicochemical properti...

Descripción completa

Detalles Bibliográficos
Autores principales: Najib, Omaima N., Kirton, Stewart B., Martin, Gary P., Botha, Michelle J., Sallam, Al-Sayed, Murnane, Darragh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7599860/
https://www.ncbi.nlm.nih.gov/pubmed/33050611
http://dx.doi.org/10.3390/pharmaceutics12100958
_version_ 1783602985094348800
author Najib, Omaima N.
Kirton, Stewart B.
Martin, Gary P.
Botha, Michelle J.
Sallam, Al-Sayed
Murnane, Darragh
author_facet Najib, Omaima N.
Kirton, Stewart B.
Martin, Gary P.
Botha, Michelle J.
Sallam, Al-Sayed
Murnane, Darragh
author_sort Najib, Omaima N.
collection PubMed
description There has been considerable recent interest in employing computer models to investigate the relationship between the structure of a molecule and its dermal penetration. Molecular permeation across the epidermis has previously been demonstrated to be determined by a number of physicochemical properties, for example, the lipophilicity, molecular weight and hydrogen bonding ability of the permeant. However little attention has been paid to modeling the combined effects of permeant properties in tandem with the properties of vehicles used to deliver those permeants or to whether data obtained using synthetic membranes can be correlated with those obtained using human epidermis. This work uses Principal Components Analysis (PCA) to demonstrate that, for studies of the diffusion of three model permeants (caffeine, methyl paraben and butyl paraben) through synthetic membranes, it is the properties of the oily vehicle in which they are applied that dominated the rates of permeation and flux. Simple robust and predictive descriptor-based quantitative structure–permeability relationship (QSPR) models have been developed to support these findings by utilizing physicochemical descriptors of the oily vehicles to quantify the differences in flux and permeation of the model compounds. Interestingly, PCA showed that, for the flux of co-applied model permeants through human epidermis, the permeation of the model permeants was better described by a balance between the physicochemical properties of the vehicle and the permeant rather than being dominated solely by the vehicle properties as in the case of synthetic model membranes. The important influence of permeant solubility in the vehicle along with the solvent uptake on overall permeant diffusion into the membrane was substantiated. These results confirm that care must be taken in interpreting permeation data when synthetic membranes are employed as surrogates for human epidermis; they also demonstrate the importance of considering not only the permeant properties but also those of both vehicle and membrane when arriving at any conclusions relating to permeation data.
format Online
Article
Text
id pubmed-7599860
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75998602020-11-01 Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes Najib, Omaima N. Kirton, Stewart B. Martin, Gary P. Botha, Michelle J. Sallam, Al-Sayed Murnane, Darragh Pharmaceutics Article There has been considerable recent interest in employing computer models to investigate the relationship between the structure of a molecule and its dermal penetration. Molecular permeation across the epidermis has previously been demonstrated to be determined by a number of physicochemical properties, for example, the lipophilicity, molecular weight and hydrogen bonding ability of the permeant. However little attention has been paid to modeling the combined effects of permeant properties in tandem with the properties of vehicles used to deliver those permeants or to whether data obtained using synthetic membranes can be correlated with those obtained using human epidermis. This work uses Principal Components Analysis (PCA) to demonstrate that, for studies of the diffusion of three model permeants (caffeine, methyl paraben and butyl paraben) through synthetic membranes, it is the properties of the oily vehicle in which they are applied that dominated the rates of permeation and flux. Simple robust and predictive descriptor-based quantitative structure–permeability relationship (QSPR) models have been developed to support these findings by utilizing physicochemical descriptors of the oily vehicles to quantify the differences in flux and permeation of the model compounds. Interestingly, PCA showed that, for the flux of co-applied model permeants through human epidermis, the permeation of the model permeants was better described by a balance between the physicochemical properties of the vehicle and the permeant rather than being dominated solely by the vehicle properties as in the case of synthetic model membranes. The important influence of permeant solubility in the vehicle along with the solvent uptake on overall permeant diffusion into the membrane was substantiated. These results confirm that care must be taken in interpreting permeation data when synthetic membranes are employed as surrogates for human epidermis; they also demonstrate the importance of considering not only the permeant properties but also those of both vehicle and membrane when arriving at any conclusions relating to permeation data. MDPI 2020-10-11 /pmc/articles/PMC7599860/ /pubmed/33050611 http://dx.doi.org/10.3390/pharmaceutics12100958 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Najib, Omaima N.
Kirton, Stewart B.
Martin, Gary P.
Botha, Michelle J.
Sallam, Al-Sayed
Murnane, Darragh
Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes
title Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes
title_full Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes
title_fullStr Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes
title_full_unstemmed Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes
title_short Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes
title_sort multivariate analytical approaches to identify key molecular properties of vehicles, permeants and membranes that affect permeation through membranes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7599860/
https://www.ncbi.nlm.nih.gov/pubmed/33050611
http://dx.doi.org/10.3390/pharmaceutics12100958
work_keys_str_mv AT najibomaiman multivariateanalyticalapproachestoidentifykeymolecularpropertiesofvehiclespermeantsandmembranesthataffectpermeationthroughmembranes
AT kirtonstewartb multivariateanalyticalapproachestoidentifykeymolecularpropertiesofvehiclespermeantsandmembranesthataffectpermeationthroughmembranes
AT martingaryp multivariateanalyticalapproachestoidentifykeymolecularpropertiesofvehiclespermeantsandmembranesthataffectpermeationthroughmembranes
AT bothamichellej multivariateanalyticalapproachestoidentifykeymolecularpropertiesofvehiclespermeantsandmembranesthataffectpermeationthroughmembranes
AT sallamalsayed multivariateanalyticalapproachestoidentifykeymolecularpropertiesofvehiclespermeantsandmembranesthataffectpermeationthroughmembranes
AT murnanedarragh multivariateanalyticalapproachestoidentifykeymolecularpropertiesofvehiclespermeantsandmembranesthataffectpermeationthroughmembranes