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In silico approach reveals N-(5-phenoxythiophen-2-yl)-2-(arylthio)acetamides as promising selective SIRT2 inhibitors: the case of structural optimization of virtual screening-derived hits

  • Mahmut Gozelle
  • , Filiz Bakar-Ates
  • , Alberto MASSAROTTI
  • , Erva Ozkan
  • , Habibe Beyza Gunindi
  • , Yesim Ozkan
  • , Gokcen Eren

Research output: Contribution to journalArticlepeer-review

Abstract

Epigenetic modifications play an essential role in tumor suppression and promotion. Among the diverse range of epigenetic regulators, SIRT2, a member of NAD+-dependent protein deacetylates, has emerged as a crucial regulator of cellular processes, including cell cycle progression, DNA repair, and metabolism, impacting tumor growth and survival. In the present work, a series of N-(5-phenoxythiophen-2-yl)-2-(arylthio)acetamide derivatives were identified following a structural optimization of previously reported virtual screening hits, accompanied by enhanced SIRT2 inhibitory potency. Among the compounds, ST44 and ST45 selectively inhibited SIRT2 with IC50 values of 6.50 and 7.24 mu M, respectively. The predicted binding modes of the two compounds revealed the success of the optimization run. Moreover, ST44 displayed antiproliferative effects on the MCF-7 human breast cancer cell line. Further, the contribution of SIRT2 inhibition in this effect of ST44 was supported by western blotting, affording an increased alpha-tubulin acetylation. Furthermore, molecular dynamics (MD) simulations and binding free energy calculations using molecular mechanics/generalized born surface area (MM-GBSA) method evaluated the accuracy of predicted binding poses and ligand affinities. The results revealed that ST44 exhibited a remarkable level of stability, with minimal deviations from its initial docking conformation. These findings represented a significant improvement over the virtual screening hits and may contribute substantially to our knowledge for further selective SIRT2 drug discovery.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalJournal of Biomolecular Structure and Dynamics
DOIs
Publication statusPublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • SIRT2
  • cytotoxicity
  • molecular modeling
  • thiophene
  • α-tubulin

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