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Application of computer-based methods to guide the development of novel sirtuin inhibitors

Başlık çevirisi mevcut değil.

  1. Tez No: 402981
  2. Yazar: BERİN KARAMAN
  3. Danışmanlar: PROF. DR. WOLFGANG SIPPL
  4. Tez Türü: Doktora
  5. Konular: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Computer Engineering and Computer Science and Control
  6. Anahtar Kelimeler: epigenetics, sirtuin, Schistosoma mansoni, cancer, docking, homology modeling, MM-GBSA, virtual screening
  7. Yıl: 2015
  8. Dil: İngilizce
  9. Üniversite: Martın Luther Unıversıty Of Halle-Wıttenberg
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: Belirtilmemiş.

Özet

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Özet (Çeviri)

Sirtuins are promising therapeutic targets which have been linked to the pathogenesis of several diseases including metabolic disorders, viral and parasitic diseases, neurodegeneration and cancer. During the last decade much effort has been devoted to discover novel sirtuin modulators with drug like properties. However, most of these compounds showed limited potency and subtype selectivity. Moreover, structural information is not available for most of them. In the current work, as a first step, we addressed the issue of structure-based optimization of sirtuin inhibitors. We demonstrated that protein-inhibitor complexes of sirtuin isoforms can be obtained by means of ligand docking and applying a short molecular dynamics (MD) simulation. This method is faster and less complex than such applications and can be also applied to other protein targets beside sirtuins. We determined a significant correlation between the binding free energy of the compounds estimated by MM-GBSA calculations and in vitro data. The developed MM-GBSA protocol is computationally inexpensive and can be applied as a post-docking filter in virtual screening campaigns to identify novel sirtuin inhibitors. Next, we established the structural basis of Sirt2-selective inhibition with the identification of a new potent drug-like inhibitor; SirReal2. X-ray crystal structures of Sirt2 in complex with SirReal2 revealed a ligand-induced rearrangement of the active site and formation of a yet-unexploited allosteric binding pocket. In order to rationalize the SirReal2-mediated high-isotype selectivity, sequence and structural alignments were performed within the members of sirtuin family. Assuming that SirReal2 binds into the other sirtuin subtypes in a similar fashion, we generated homology models and carried out docking studies of SirReal2. The obtained results demonstrate that the residues that form the SirReal2 binding pocket differ significantly within the sirtuin family and minor sequence variations hamper the correct orientation of SirReal2. Moreover, we developed photoswitchable sirtuin inhibitors by merging the structure of photochromic diarylmaleimides with the pharmacophore of a known sirtuin inhibitor. The new compounds exhibited potent Sirt2-selective inhibition with regard to the Sirt1 and Sirt3 isoforms. Docking studies could explain the structure activity/selectivity relationship observed for these compounds. Addditionally, human Sirt2 inhibitors has been shown to posses strong effects on both the life span and reproduction of Schistosoma mansoni, the main pathogen of schistomiasis. Thus, we expanded our interests into smSirt2 as a new antiparasite target. Upon screening of an in-house library, we identified a number of potent novel smSirt2 inhibitors. Due to the absence of the smSirt2 crystal structure, we first generated a homology model (HM) for this enzyme. We could rationalize the binding interactions of the detected inhibitors with smSirt2-HM by means of docking. In order to decipher the complex nature of sirtuins in cancer, potent and isoform selective sirtuin inhibitors are highly in need. In this context, we established docking- and pharmacophore-based virtual screening methods. The potential of these methods were verified using the newly developed African natural product anticancer database (AfroCancer) and already known anticancer drug targets.

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