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Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range

The n-octanol–water partition coefficient (logP) is an important physicochemical parameter which describes the behavior of organic compounds. In this work, the apparent n-octanol/water partition coefficients (logD) of basic compounds were determined using ion-suppression reversed-phase liquid chroma...

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Autores principales: Qiao, Jun-Qin, Liu, Xiao-Lan, Liang, Chao, Wang, Ju, Lian, Hong-Zhen, Mao, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005301/
https://www.ncbi.nlm.nih.gov/pubmed/36903512
http://dx.doi.org/10.3390/molecules28052270
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author Qiao, Jun-Qin
Liu, Xiao-Lan
Liang, Chao
Wang, Ju
Lian, Hong-Zhen
Mao, Li
author_facet Qiao, Jun-Qin
Liu, Xiao-Lan
Liang, Chao
Wang, Ju
Lian, Hong-Zhen
Mao, Li
author_sort Qiao, Jun-Qin
collection PubMed
description The n-octanol–water partition coefficient (logP) is an important physicochemical parameter which describes the behavior of organic compounds. In this work, the apparent n-octanol/water partition coefficients (logD) of basic compounds were determined using ion-suppression reversed-phase liquid chromatography (IS-RPLC) on a silica-based C18 column. The quantitative structure–retention relationship (QSRR) models between logD and logk(w) (logarithm of retention factor corresponding to 100% aqueous fraction of mobile phase) were established at pH 7.0–10.0. It was found that logD had a poor linear correlation with logk(w) at pH 7.0 and pH 8.0 when strongly ionized compounds were included in the model compounds. However, the linearity of the QSRR model was significantly improved, especially at pH 7.0, when molecular structure parameters such as electrostatic charge n(e) and hydrogen bonding parameters A and B were introduced. External validation experiments further confirmed that the multi-parameter models could accurately predict the logD value of basic compounds not only under strong alkaline conditions, but also under weak alkaline and even neutral conditions. The logD values of basic sample compounds were predicted based on the multi-parameter QSRR models. Compared with previous work, the findings of this study extended the pH range for the determination of the logD values of basic compounds, providing an optional mild pH for IS-RPLC experiments.
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spelling pubmed-100053012023-03-11 Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range Qiao, Jun-Qin Liu, Xiao-Lan Liang, Chao Wang, Ju Lian, Hong-Zhen Mao, Li Molecules Article The n-octanol–water partition coefficient (logP) is an important physicochemical parameter which describes the behavior of organic compounds. In this work, the apparent n-octanol/water partition coefficients (logD) of basic compounds were determined using ion-suppression reversed-phase liquid chromatography (IS-RPLC) on a silica-based C18 column. The quantitative structure–retention relationship (QSRR) models between logD and logk(w) (logarithm of retention factor corresponding to 100% aqueous fraction of mobile phase) were established at pH 7.0–10.0. It was found that logD had a poor linear correlation with logk(w) at pH 7.0 and pH 8.0 when strongly ionized compounds were included in the model compounds. However, the linearity of the QSRR model was significantly improved, especially at pH 7.0, when molecular structure parameters such as electrostatic charge n(e) and hydrogen bonding parameters A and B were introduced. External validation experiments further confirmed that the multi-parameter models could accurately predict the logD value of basic compounds not only under strong alkaline conditions, but also under weak alkaline and even neutral conditions. The logD values of basic sample compounds were predicted based on the multi-parameter QSRR models. Compared with previous work, the findings of this study extended the pH range for the determination of the logD values of basic compounds, providing an optional mild pH for IS-RPLC experiments. MDPI 2023-02-28 /pmc/articles/PMC10005301/ /pubmed/36903512 http://dx.doi.org/10.3390/molecules28052270 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Qiao, Jun-Qin
Liu, Xiao-Lan
Liang, Chao
Wang, Ju
Lian, Hong-Zhen
Mao, Li
Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range
title Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range
title_full Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range
title_fullStr Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range
title_full_unstemmed Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range
title_short Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range
title_sort prediction of the n-octanol/water partition coefficients of basic compounds using multi-parameter qsrr models based on is-rplc retention behavior in a wide ph range
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005301/
https://www.ncbi.nlm.nih.gov/pubmed/36903512
http://dx.doi.org/10.3390/molecules28052270
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