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决策树用于描述渗透性和溶解度在口服吸收预测中的作用。

Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption.

机构信息

Medway School of Pharmacy, Universities of Kent and Greenwich, Chatham, Kent ME4 4TB, UK.

School of Computing, University of Kent, Canterbury, Kent CT2 7NF, UK.

出版信息

Eur J Med Chem. 2015 Jan 27;90:751-65. doi: 10.1016/j.ejmech.2014.12.006. Epub 2014 Dec 4.

DOI:10.1016/j.ejmech.2014.12.006
PMID:25528330
Abstract

Oral absorption of compounds depends on many physiological, physiochemical and formulation factors. Two important properties that govern oral absorption are in vitro permeability and solubility, which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aqueous solubility, melting point, and maximum dose for the same compounds. The dataset allowed a permeability threshold to be established objectively to predict high or low intestinal absorption. Using this permeability threshold, classification decision trees incorporating a solubility-related parameter such as experimental or predicted solubility, or the melting point based absorption potential (MPbAP), along with structural molecular descriptors were developed and validated to predict oral absorption class. The decision trees were able to determine the individual roles of permeability and solubility in oral absorption process. Poorly permeable compounds with high solubility show low intestinal absorption, whereas poorly water soluble compounds with high or low permeability may have high intestinal absorption provided that they have certain molecular characteristics such as a small polar surface or specific topology.

摘要

化合物的口服吸收取决于许多生理、物理化学和制剂因素。两个重要的控制口服吸收的性质是体外渗透性和溶解度,它们通常被用作人类肠道吸收的指标。尽管如此,这些参数之间的性质和确切关系并不清楚。在这项研究中,我们整理了大量的人类肠道吸收数据集,以及相同化合物的体外渗透性、水溶解度、熔点和最大剂量。该数据集允许客观地建立一个渗透性阈值来预测高或低的肠道吸收。使用这个渗透性阈值,我们结合了一个与溶解度相关的参数,如实验或预测的溶解度,或基于熔点的吸收潜力(MPbAP),以及结构分子描述符,开发并验证了分类决策树来预测口服吸收类别。决策树能够确定渗透性和溶解度在口服吸收过程中的单独作用。高溶解度的低渗透性化合物显示出低的肠道吸收,而高或低渗透性的低水溶性化合物如果具有某些分子特征,如小的极性表面或特定的拓扑结构,则可能具有高的肠道吸收。

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