Chapter 9 Molecular Similarity: Advances in Methods, Applications and Validations in Virtual Screening and QSAR.

Andreas Bender, Jeremy L Jenkins, Qingliang Li, Sam E Adams, Edward O Cannon, Robert C Glen
{"title":"Chapter 9 Molecular Similarity: Advances in Methods, Applications and Validations in Virtual Screening and QSAR.","authors":"Andreas Bender,&nbsp;Jeremy L Jenkins,&nbsp;Qingliang Li,&nbsp;Sam E Adams,&nbsp;Edward O Cannon,&nbsp;Robert C Glen","doi":"10.1016/S1574-1400(06)02009-3","DOIUrl":null,"url":null,"abstract":"<p><p>This chapter discusses recent developments in some of the areas that exploit the molecular similarity principle, novel approaches to capture molecular properties by the use of novel descriptors, focuses on a crucial aspect of computational models-their validity, and discusses additional ways to examine data available, such as those from high-throughput screening (HTS) campaigns and to gain more knowledge from this data. The chapter also presents some of the recent applications of methods discussed focusing on the successes of virtual screening applications, database clustering and comparisons (such as drug- and in-house-likeness), and the recent large-scale validations of docking and scoring programs. While a great number of descriptors and modeling methods has been proposed until today, the recent trend toward proper model validation is very much appreciated. Although some of their limitations are surely because of underlying principles and limitations of fundamental concepts, others will certainly be eliminated in the future.</p>","PeriodicalId":88823,"journal":{"name":"Annual reports in computational chemistry","volume":"2 ","pages":"141-168"},"PeriodicalIF":0.0000,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1574-1400(06)02009-3","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual reports in computational chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/S1574-1400(06)02009-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2006/11/7 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

This chapter discusses recent developments in some of the areas that exploit the molecular similarity principle, novel approaches to capture molecular properties by the use of novel descriptors, focuses on a crucial aspect of computational models-their validity, and discusses additional ways to examine data available, such as those from high-throughput screening (HTS) campaigns and to gain more knowledge from this data. The chapter also presents some of the recent applications of methods discussed focusing on the successes of virtual screening applications, database clustering and comparisons (such as drug- and in-house-likeness), and the recent large-scale validations of docking and scoring programs. While a great number of descriptors and modeling methods has been proposed until today, the recent trend toward proper model validation is very much appreciated. Although some of their limitations are surely because of underlying principles and limitations of fundamental concepts, others will certainly be eliminated in the future.

Abstract Image

第九章分子相似性:虚拟筛选和QSAR的方法、应用和验证进展。
本章讨论了利用分子相似性原理的一些领域的最新发展,通过使用新颖的描述符来捕获分子特性的新方法,重点关注计算模型的一个关键方面-它们的有效性,并讨论了检查可用数据的其他方法,例如来自高通量筛选(HTS)活动的数据,并从这些数据中获得更多知识。本章还介绍了一些最近讨论的方法的应用,重点是虚拟筛选应用的成功,数据库聚类和比较(如药物和内部相似性),以及最近对接和评分程序的大规模验证。虽然到目前为止已经提出了大量的描述符和建模方法,但最近的趋势是正确的模型验证是非常值得赞赏的。虽然它们的一些限制肯定是由于基本原则和基本概念的限制,但其他的限制肯定会在未来被消除。
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
CiteScore
2.50
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