Computational Methods for Epigenetic Drug Discovery: A Focus on Activity Landscape Modeling

被引:7
|
作者
Jesus Naveja, J. [1 ,2 ]
Iluhi Oviedo-Osornio, C. [1 ]
Medina-Franco, Jose L. [1 ]
机构
[1] Univ Nacl Autonoma Mexico, Fac Quim, Mexico City, DF, Mexico
[2] Univ Nacl Autonoma Mexico, Fac Med, PECEM, Mexico City, DF, Mexico
关键词
HISTONE DEACETYLASE INHIBITORS; ACTIVITY CLIFF GENERATORS; MOLECULAR-MECHANISMS; LEUKEMIA-CELLS; INDEX;
D O I
10.1016/bs.apcsb.2018.01.001
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Epigenetic drug discovery is an emerging strategy against several chronic and complex diseases. The increased interest in epigenetics has boosted the development and maintenance of large information on structure-epigenetic activity relationships for several epigenetic targets. In turn, such large databases-many in the public domain-are a rich source of information to explore their structure-activity relationships (SARs). Herein, we conducted a large-scale analysis of the SAR of epigenetic targets using the concept of activity landscape modeling. A comprehensive quantitative analysis and a novel visual representation of the epigenetic activity landscape enabled the rapid identification of regions of targets with continuous and discontinuous SAR. This information led to the identification of epigenetic targets for which it is anticipated an easier or a more difficult drug-discovery program using conventional hit-to-lead approaches. The insights of this work also enabled the identification of specific structural changes associated with a large shift in biological activity. To the best of our knowledge, this work represents the largest comprehensive SAR analysis of several epigenetic targets and contributes to the better understanding of the epigenetic activity landscape.
引用
收藏
页码:65 / 83
页数:19
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