从结构预测水溶性。

Predicting aqueous solubility from structure.

作者信息

Delaney John S

机构信息

Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire, RG42 6EY UK.

出版信息

Drug Discov Today. 2005 Feb 15;10(4):289-95. doi: 10.1016/S1359-6446(04)03365-3.

Abstract

The aqueous solubility of a drug is one of the key physical properties that affect both its ADME profile and 'screenability' in HTS. This review critically surveys a range of methods that can be used to predict the solubility of a compound in water and presents some of the main issues that affect the applicability of different techniques. As ever, there are trade-offs to be made between the speed, accuracy and transparency of methods, but current programs can provide estimates to well within an order of magnitude in favourable cases. The need for new ways to predict solubility in more challenging systems (e.g. solvents such as DMSO and charged solutes) is discussed.

摘要

药物的水溶性是影响其药代动力学过程和高通量筛选中“可筛选性”的关键物理性质之一。本综述批判性地审视了一系列可用于预测化合物在水中溶解度的方法,并提出了影响不同技术适用性的一些主要问题。一如既往,在方法的速度、准确性和透明度之间需要进行权衡,但在有利的情况下,当前程序能够提供误差在一个数量级以内的估计值。文中还讨论了预测在更具挑战性的体系(如二甲基亚砜等溶剂和带电溶质)中溶解度的新方法的必要性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索