...
首页> 外文期刊>Chemical and Pharmaceutical Bulletin >A Simple Method to Improve the Odds in Finding 'Lead-Like' Compounds from Chemical Libraries
【24h】

A Simple Method to Improve the Odds in Finding 'Lead-Like' Compounds from Chemical Libraries

机译:一种简单的方法来改善从化学图书馆中查找“领先”化合物的几率

获取原文
获取原文并翻译 | 示例
           

摘要

A simple method of virtual screening is proposed.This method uses only chemical characters calculated from two dimensional chemical structures.Local and global chemical characters are represented by molecular fingerprint and trait,respectively.The trait is a newly introduced concept in this paper and it is expressed by a set of two dimensional(2D)molecular descriptors.In this study,both the molecular fingerprint and the trait were used to represent drug-likeness of a group of molecules with a particular pharmacological activity.To learn about the molecular fingerprint and trait specific to a particular group of drugs,we used a database of drugs that are clinically used in Japan now.The molecular fingerprint and trait trained on these real drugs were used to predict drug-likeness of molecules in other chemical databases.In these chemical databases,an appreciable number of compounds that show the relevant pharmacological activity are contained.Some of these compounds are drugs clinically used abroad,but not in Japan.The prediction rate was judged by an enrichment factor.Despite the simplicity of the methodology,practical results were obtained.In the case of beta-adrenergic blockers,the enrichment factor of 66 was attained and nearly 57% of active molecules in the chemical databases were successfully covered.
机译:提出了一种简单的虚拟筛选方法,该方法仅使用从二维化学结构计算出的化学特征。局部和全局化学特征分别由分子指纹和特征表示。特征是本文新引入的概念,由一组二维(2D)分子描述子表达。在这项研究中,分子指纹和性状都被用来代表一组具有特定药理活性的分子的类药物。要了解分子指纹和性状针对特定的一组药物,我们使用了现在在日本临床使用的药物数据库。在这些化学药物上训练的分子指纹和特征被用于预测其他化学数据库中分子的药物相似性。在这些化学数据库中,其中包含相当数量的具有相关药理活性的化合物。其中一些是临床药物在国外使用,但未在日本使用。通过富集因子判断预测率。尽管方法简单,但仍获得了实际结果。在β-肾上腺素能阻滞剂的情况下,达到了66的富集因子,接近57%化学数据库中的活性分子被成功覆盖。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号