Top Med Chem (2020) 33: 455–486
DOI: 10.1007/7355_2019_80
© Springer Nature Switzerland AG 2019
Published online: 28 November 2019
Structure-Based Design of Epigenetic
Inhibitors
Dina Robaa, Jelena Melesina, Chiara Luise, and Wolfgang Sippl
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457
2 Computational Methods to Predict the Target Interaction of Small Molecules and Their
Binding Affinities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . 458
3 Histone Deacetylases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459
3.1 Zinc-Dependent HDACs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459
3.2 Sirtuins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463
4 Histone Methyltransferases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465
5 Histone Demethylases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469
5.1 LSD1 (KDM1A) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469
5.2 Jumonji Histone Demethylases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472
6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
Abstract Computer-aided and structure-based design methods play an important
role in the development of inhibitors for epigenetic drug targets. Multiple hits have
been discovered over the last years, and several leads have been optimized using
molecular modeling methods, such as virtual screening, molecular docking, binding
free energy calculations, homology modeling, and others. In this chapter, advances
and success stories of computer-assisted development of epigenetic inhibitors are
collected. The presented examples give an overview of successfully applied strategies and emphasize the advantage of guidance and rationalization of experimental
data with computational means.
D. Robaa, J. Melesina, C. Luise, and W. Sippl (*)
Department of Pharmaceutical Chemistry, Martin-Luther University of Halle-Wittenberg,
Halle/Saale, Germany
e-mail: wolfgang.sippl@pharmazie.uni-halle.de
Précédent

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