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简而言之:匹配分子对分析——算法、应用与局限

Matched Molecular Pair Analysis in Short: Algorithms, Applications and Limitations.

作者信息

Tyrchan Christian, Evertsson Emma

机构信息

Department of Medicinal Chemistry, RIA iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden.

出版信息

Comput Struct Biotechnol J. 2016 Dec 13;15:86-90. doi: 10.1016/j.csbj.2016.12.003. eCollection 2017.

DOI:10.1016/j.csbj.2016.12.003
PMID:28066532
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5198793/
Abstract

Molecular matched pair (MMP) analysis has been used for more than 40 years within molecular design and is still an important tool to analyse potency data and other compound properties. The methods used to find matched pairs range from manual inspection, through supervised methods to unsupervised methods, which are able to find previously unknown molecular pairs. Recent publications demonstrate the value of automatic MMP analysis of publicly available bioactivity databases. The MMP concept has its limitations, but because of its easy to use and intuitive nature, it will remain one of the most important tools in the toolbox of many drug designers.

摘要

分子匹配对(MMP)分析在分子设计领域已应用了40多年,至今仍是分析活性数据和其他化合物性质的重要工具。用于寻找匹配对的方法从人工检查,到有监督方法,再到无监督方法,后者能够发现此前未知的分子对。近期的出版物展示了对公开可用生物活性数据库进行自动MMP分析的价值。MMP概念有其局限性,但因其易于使用且直观,它仍将是许多药物设计师工具库中最重要的工具之一。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bb0/5198793/3d3bf61fdaaf/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bb0/5198793/9e5d3ed76b1a/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bb0/5198793/3d3bf61fdaaf/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bb0/5198793/9e5d3ed76b1a/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bb0/5198793/3d3bf61fdaaf/gr2.jpg

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