Correlation between the structure and skin permeability of compounds

Abstract A three-descriptor quantitative structure–activity/toxicity relationship (QSAR/QSTR) model was developed for the skin permeability of a sufficiently large data set consisting of 274 compounds, by applying support vector machine (SVM) together with genetic algorithm. The optimal SVM model po...

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Autores principales:	Ruolan Zeng, Jiyong Deng, Limin Dang, Xinliang Yu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f024487036de479e904c78a67ce8eb9c
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spelling	oai:doaj.org-article:f024487036de479e904c78a67ce8eb9c2021-12-02T17:16:11ZCorrelation between the structure and skin permeability of compounds10.1038/s41598-021-89587-52045-2322https://doaj.org/article/f024487036de479e904c78a67ce8eb9c2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89587-5https://doaj.org/toc/2045-2322Abstract A three-descriptor quantitative structure–activity/toxicity relationship (QSAR/QSTR) model was developed for the skin permeability of a sufficiently large data set consisting of 274 compounds, by applying support vector machine (SVM) together with genetic algorithm. The optimal SVM model possesses the coefficient of determination R 2 of 0.946 and root mean square (rms) error of 0.253 for the training set of 139 compounds; and a R 2 of 0.872 and rms of 0.302 for the test set of 135 compounds. Compared with other models reported in the literature, our SVM model shows better statistical performance in a model that deals with more samples in the test set. Therefore, applying a SVM algorithm to develop a nonlinear QSAR model for skin permeability was achieved.Ruolan ZengJiyong DengLimin DangXinliang YuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ruolan Zeng Jiyong Deng Limin Dang Xinliang Yu Correlation between the structure and skin permeability of compounds
description	Abstract A three-descriptor quantitative structure–activity/toxicity relationship (QSAR/QSTR) model was developed for the skin permeability of a sufficiently large data set consisting of 274 compounds, by applying support vector machine (SVM) together with genetic algorithm. The optimal SVM model possesses the coefficient of determination R 2 of 0.946 and root mean square (rms) error of 0.253 for the training set of 139 compounds; and a R 2 of 0.872 and rms of 0.302 for the test set of 135 compounds. Compared with other models reported in the literature, our SVM model shows better statistical performance in a model that deals with more samples in the test set. Therefore, applying a SVM algorithm to develop a nonlinear QSAR model for skin permeability was achieved.
format	article
author	Ruolan Zeng Jiyong Deng Limin Dang Xinliang Yu
author_facet	Ruolan Zeng Jiyong Deng Limin Dang Xinliang Yu
author_sort	Ruolan Zeng
title	Correlation between the structure and skin permeability of compounds
title_short	Correlation between the structure and skin permeability of compounds
title_full	Correlation between the structure and skin permeability of compounds
title_fullStr	Correlation between the structure and skin permeability of compounds
title_full_unstemmed	Correlation between the structure and skin permeability of compounds
title_sort	correlation between the structure and skin permeability of compounds
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f024487036de479e904c78a67ce8eb9c
work_keys_str_mv	AT ruolanzeng correlationbetweenthestructureandskinpermeabilityofcompounds AT jiyongdeng correlationbetweenthestructureandskinpermeabilityofcompounds AT limindang correlationbetweenthestructureandskinpermeabilityofcompounds AT xinliangyu correlationbetweenthestructureandskinpermeabilityofcompounds
_version_	1718381236476444672

Correlation between the structure and skin permeability of compounds

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