Literature DB >> 26372447

Estimation of alkane-water logP for neutral, acidic, and basic compounds using an alkylated polystyrene-divinylbenzene high-performance liquid chromatography column.

Derek A Jensen1, Ronald K Gary2.   

Abstract

Reliable HPLC methods are available to estimate octanol-water partition coefficients, but there is no comparable method for alkane-water partition coefficients that is accurate and applicable across a broad span of logP(alk). This study describes a high-throughput method for determining HPLC-logP(alk), a chromatographic parameter closely related to logP(alk), using an alkylated polystyrene-divinylbenzene column and fast acetonitrile gradient. A structurally diverse set of neutral, acidic, and basic compounds was analyzed under ionization-suppressing pH conditions. In this chromatographic system, the relationship between gradient retention time and isocratic logk was essentially linear. Thus, gradient retention time could be used as the sole input needed to determine an apparent logP(alk)by HPLC. HPLC-logP(alk) showed linear correlation (R(2)>0.96, n=59) with reference logP(alk) values from shake-flask measurements over 8 orders of magnitude, ranging from -2.3 to +5.7. Linear solvation energy relationship (LSER) analysis revealed that the relative contributions of intermolecular forces effecting retention in the fast gradient system or its corresponding isocratic variant were highly similar to those governing partition in bulk alkane-water.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Drug discovery; HPLC; Linear solvation energy relationship (LSER); Lipophilicity; Partition coefficient; ΔlogP

Mesh:

Substances:

Year:  2015        PMID: 26372447     DOI: 10.1016/j.chroma.2015.09.020

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  1 in total

1.  The influence of hydrogen bonding on partition coefficients.

Authors:  Nádia Melo Borges; Peter W Kenny; Carlos A Montanari; Igor M Prokopczyk; Jean F R Ribeiro; Josmar R Rocha; Geraldo Rodrigues Sartori
Journal:  J Comput Aided Mol Des       Date:  2017-01-04       Impact factor: 3.686

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.