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Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm

A quantiatative structure property relationship (QSPR) treatment was used to a data set consisting of diverse 3-hydroxypyridine-4-one derivatives to relate the logarithmic function of octanol:water partition coefficients (denoted by log p(o/w)) with theoretical molecular descriptors. Evaluation of a...

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Autores principales: Shahlaei, M., Fassihi, A., Saghaie, L., Zare, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4311292/
https://www.ncbi.nlm.nih.gov/pubmed/25657783
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author Shahlaei, M.
Fassihi, A.
Saghaie, L.
Zare, A.
author_facet Shahlaei, M.
Fassihi, A.
Saghaie, L.
Zare, A.
author_sort Shahlaei, M.
collection PubMed
description A quantiatative structure property relationship (QSPR) treatment was used to a data set consisting of diverse 3-hydroxypyridine-4-one derivatives to relate the logarithmic function of octanol:water partition coefficients (denoted by log p(o/w)) with theoretical molecular descriptors. Evaluation of a test set of 6 compounds with the developed partial least squares (PLS) model revealed that this model is reliable with a good predictability. Since the QSPR study was performed on the basis of theoretical descriptors calculated completely from the molecular structures, the proposed model could potentially provide useful information about the activity of the studied compounds. Various tests and criteria such as leave-one-out cross validation, leave-many-out cross validation, and also criteria suggested by Tropsha were employed to examine the predictability and robustness of the developed model.
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spelling pubmed-43112922015-02-05 Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm Shahlaei, M. Fassihi, A. Saghaie, L. Zare, A. Res Pharm Sci Original Article A quantiatative structure property relationship (QSPR) treatment was used to a data set consisting of diverse 3-hydroxypyridine-4-one derivatives to relate the logarithmic function of octanol:water partition coefficients (denoted by log p(o/w)) with theoretical molecular descriptors. Evaluation of a test set of 6 compounds with the developed partial least squares (PLS) model revealed that this model is reliable with a good predictability. Since the QSPR study was performed on the basis of theoretical descriptors calculated completely from the molecular structures, the proposed model could potentially provide useful information about the activity of the studied compounds. Various tests and criteria such as leave-one-out cross validation, leave-many-out cross validation, and also criteria suggested by Tropsha were employed to examine the predictability and robustness of the developed model. Medknow Publications & Media Pvt Ltd 2014 /pmc/articles/PMC4311292/ /pubmed/25657783 Text en Copyright: © Research in Pharmaceutical Sciences http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Shahlaei, M.
Fassihi, A.
Saghaie, L.
Zare, A.
Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm
title Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm
title_full Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm
title_fullStr Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm
title_full_unstemmed Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm
title_short Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm
title_sort prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4311292/
https://www.ncbi.nlm.nih.gov/pubmed/25657783
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