The pK(a) Distribution of Drugs: Application to Drug Discovery.

Perspectives in medicinal chemistry Pub Date : 2007-09-17
David T Manallack
{"title":"The pK(a) Distribution of Drugs: Application to Drug Discovery.","authors":"David T Manallack","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>The acid-base dissociation constant (pK(a)) of a drug is a key physicochemical parameter influencing many biopharmaceutical characteristics. While this has been well established, the overall proportion of non-ionizable and ionizable compounds for drug-like substances is not well known. Even less well known is the overall distribution of acid and base pK(a) values. The current study has reviewed the literature with regard to both the proportion of ionizable substances and pK(a) distributions. Further to this a set of 582 drugs with associated pK(a) data was thoroughly examined to provide a representative set of observations. This was further enhanced by delineating the compounds into CNS and non-CNS drugs to investigate where differences exist. Interestingly, the distribution of pK(a) values for single acids differed remarkably between CNS and non-CNS substances with only one CNS compound having an acid pK(a) below 6.1. The distribution of basic substances in the CNS set also showed a marked cut off with no compounds having a pK(a) above 10.5.The pK(a) distributions of drugs are influenced by two main drivers. The first is related to the nature and frequency of occurrence of the functional groups that are commonly observed in pharmaceuticals and the typical range of pK(a) values they span. The other factor concerns the biological targets these compounds are designed to hit. For example, many CNS targets are based on seven transmembrane G protein-coupled receptors (7TM GPCR) which have a key aspartic acid residue known to interact with most ligands. As a consequence, amines are mostly present in the ligands that target 7TM GPCR's and this influences the pK(a) profile of drugs containing basic groups. For larger screening collections of compounds, synthetic chemistry and the working practices of the chemists themselves can influence the proportion of ionizable compounds and consequent pK(a) distributions. The findings from this study expand on current wisdom in pK(a) research and have implications for discovery research with regard to the composition of corporate databases and collections of screening compounds. Rough guidelines have been suggested for the profile of compound collections and will evolve as this research area is expanded.</p>","PeriodicalId":88294,"journal":{"name":"Perspectives in medicinal chemistry","volume":"1 ","pages":"25-38"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2754920/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Perspectives in medicinal chemistry","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The acid-base dissociation constant (pK(a)) of a drug is a key physicochemical parameter influencing many biopharmaceutical characteristics. While this has been well established, the overall proportion of non-ionizable and ionizable compounds for drug-like substances is not well known. Even less well known is the overall distribution of acid and base pK(a) values. The current study has reviewed the literature with regard to both the proportion of ionizable substances and pK(a) distributions. Further to this a set of 582 drugs with associated pK(a) data was thoroughly examined to provide a representative set of observations. This was further enhanced by delineating the compounds into CNS and non-CNS drugs to investigate where differences exist. Interestingly, the distribution of pK(a) values for single acids differed remarkably between CNS and non-CNS substances with only one CNS compound having an acid pK(a) below 6.1. The distribution of basic substances in the CNS set also showed a marked cut off with no compounds having a pK(a) above 10.5.The pK(a) distributions of drugs are influenced by two main drivers. The first is related to the nature and frequency of occurrence of the functional groups that are commonly observed in pharmaceuticals and the typical range of pK(a) values they span. The other factor concerns the biological targets these compounds are designed to hit. For example, many CNS targets are based on seven transmembrane G protein-coupled receptors (7TM GPCR) which have a key aspartic acid residue known to interact with most ligands. As a consequence, amines are mostly present in the ligands that target 7TM GPCR's and this influences the pK(a) profile of drugs containing basic groups. For larger screening collections of compounds, synthetic chemistry and the working practices of the chemists themselves can influence the proportion of ionizable compounds and consequent pK(a) distributions. The findings from this study expand on current wisdom in pK(a) research and have implications for discovery research with regard to the composition of corporate databases and collections of screening compounds. Rough guidelines have been suggested for the profile of compound collections and will evolve as this research area is expanded.

Abstract Image

Abstract Image

Abstract Image

药物的pK(a)分布:药物发现的应用。
药物的酸碱解离常数(pK(a))是影响许多生物制药特性的关键理化参数。虽然这一点已经得到了很好的证实,但药物类物质中不可电离和可电离化合物的总体比例尚不清楚。更鲜为人知的是酸碱pK(a)值的总体分布。本研究回顾了有关可电离物质的比例和pK(a)分布的文献。此外,对582种具有相关pK(a)数据的药物进行了彻底检查,以提供一组具有代表性的观察结果。通过将化合物划分为中枢神经系统和非中枢神经系统药物来研究差异存在的地方,这进一步增强了这一点。有趣的是,单一酸的pK(a)值在CNS和非CNS物质之间的分布存在显著差异,只有一种CNS化合物的酸pK(a)低于6.1。基本物质在CNS组的分布也出现了明显的截断,没有化合物的pK(a)大于10.5。药物的pK(a)分布受到两个主要驱动因素的影响。第一个与药物中常见的官能团的性质和出现频率以及它们所跨越的pK(a)值的典型范围有关。另一个因素与这些化合物设计用来攻击的生物目标有关。例如,许多中枢神经系统靶点是基于7种跨膜G蛋白偶联受体(7TM GPCR),这些受体具有已知与大多数配体相互作用的关键天冬氨酸残基。因此,胺主要存在于靶向7TM GPCR的配体中,这影响了含有碱性基团的药物的pK(a)谱。对于较大的化合物筛选集合,合成化学和化学家本身的工作实践可以影响可电离化合物的比例和随后的pK(a)分布。本研究的发现扩展了目前pK(a)研究的智慧,并对有关公司数据库组成和筛选化合物集合的发现研究具有启示意义。粗略的指导方针已经提出了化合物集合的轮廓,并将随着这一研究领域的扩大而发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信