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
相关论文
共 50 条
  • [31] The rise of epigenetic drug discovery
    Dymock, Brian W.
    FUTURE MEDICINAL CHEMISTRY, 2016, 8 (13) : 1523 - 1524
  • [32] Improving drug discovery using image-based multiparametric analysis of the epigenetic landscape
    Farhy, Chen
    Hariharan, Santosh
    Ylanko, Jarkko
    Orozco, Luis
    Zeng, Fu-Yue
    Pass, Ian
    Ugarte, Fernando
    Forsberg, E. Camilla
    Huang, Chun-Teng
    Andrews, David W.
    Terskikh, Alexey V.
    ELIFE, 2019, 8
  • [33] Computational drug discovery
    Ou-Yang, Si-sheng
    Lu, Jun-yan
    Kong, Xiang-qian
    Liang, Zhong-jie
    Luo, Cheng
    Jiang, Hualiang
    ACTA PHARMACOLOGICA SINICA, 2012, 33 (09) : 1131 - 1140
  • [34] Computational drug discovery
    Si-sheng Ou-Yang
    Jun-yan Lu
    Xiang-qian Kong
    Zhong-jie Liang
    Cheng Luo
    Hualiang Jiang
    Acta Pharmacologica Sinica, 2012, 33 : 1131 - 1140
  • [35] Activity Landscape and Molecular Modeling to Explore the SAR of Dual Epigenetic Inhibitors: A Focus on G9a and DNMT1
    Lopez-Lopez, Edgar
    Prieto-Martinez, Fernando D.
    Medina-Franco, Jose L.
    MOLECULES, 2018, 23 (12):
  • [36] Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives
    Romano, Joseph D.
    Tatonetti, Nicholas P.
    FRONTIERS IN GENETICS, 2019, 10
  • [37] Modern drug discovery for inflammatory bowel disease:The role of computational methods
    Titilayo Omolara Johnson
    Augustina Oduje Akinsanmi
    Stephen Adakole Ejembi
    Olugbenga Eyitayo Adeyemi
    Jane-Rose Oche
    Grace Inioluwa Johnson
    Abayomi Emmanuel Adegboyega
    World Journal of Gastroenterology, 2023, 29 (02) : 310 - 331
  • [38] COLLABORATIVE APPLICATION OF COMPUTATIONAL CHEMISTRY METHODS IN THE DRUG DISCOVERY OPTIMIZATION PROCESS
    HOWE, WJ
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1992, 204 : 170 - MEDI
  • [39] Overview of computational methods employed in early-stage drug discovery
    Skjevik, Age Aleksander
    Teigen, Knut
    Martinez, Aurora
    FUTURE MEDICINAL CHEMISTRY, 2009, 1 (01) : 49 - 63
  • [40] Chemogenomics in drug discovery: computational methods based on the comparison of binding sites
    Vulpetti, Anna
    Kalliokoski, Tuomo
    Milletti, Francesca
    FUTURE MEDICINAL CHEMISTRY, 2012, 4 (15) : 1971 - 1979