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タイトル
和文: 
英文:QEX: target-specific druglikeness filter enhances ligand-based virtual screening 
著者
和文: Masahiro Mochizuki, 鈴木翔吾, 柳澤 渓甫, 大上 雅史, 秋山 泰.  
英文: Masahiro Mochizuki, Shogo Suzuki, Yanagisawa K, Ohue M, Akiyama Y..  
言語 English 
掲載誌/書名
和文: 
英文:Molecular Diversity 
巻, 号, ページ Volume 23    issue 1    pp. 11-18
出版年月 2018年7月3日 
出版者
和文: 
英文:Springer 
会議名称
和文: 
英文: 
開催地
和文: 
英文: 
公式リンク https://link.springer.com/article/10.1007/s11030-018-9842-3
 
DOI https://doi.org/10.1007/s11030-018-9842-3
アブストラクト ruglikeness is a useful concept for screening drug candidate compounds. We developed QEX, which is a new druglikeness index specific to individual targets. QEX is an improvement of the quantitative estimate of druglikeness (QED) method, which is a popular quantitative evaluation method of druglikeness proposed by Bickerton et al. QEX models the physicochemical properties of compounds that act on each target protein based on the concept of QED modeling physicochemical properties from information on US Food and Drug Administration-approved drugs. The result of the evaluation of PubChem assay data revealed that QEX showed better performance than the original QED did (the area under the curve value of the receiver operating characteristic curve improved by 0.069-0.236). We also present the c-Src inhibitor filtering results of the QEX constructed using Src family kinase inhibitors as a case study. QEX distinguished the inhibitors and non-inhibitors better than QED did. QEX works efficiently even when datasets of inactive compounds are unavailable. If both active and inactive compounds are present, QEX can be used as an initial filter to enhance the screening ability of conventional ligand-based virtual screenings.

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