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Discovery of selective HDAC6 inhibitors based on a multi-layer virtual screening strategy.

Authors :
Liu X
Yan W
Wang S
Lu M
Yang H
Chai X
Shi H
Zhang Y
Jia Q
Source :
Computers in biology and medicine [Comput Biol Med] 2023 Jun; Vol. 160, pp. 107036. Date of Electronic Publication: 2023 May 12.
Publication Year :
2023

Abstract

The abnormal enhancement of histone deacetylase 6 (HDAC6) has been demonstrated to be closely related to the occurrence and development of various malignant tumors, attracting extensive attention as a promising target for cancer therapy. Currently, only limited selective HDAC6 inhibitors have entered clinical trials, making the rapid discovery of selective HDAC6 inhibitors with safety profiles particularly urgent. In this study, a multi-layer virtual screening workflow was established, and the representative compounds screened were biologically evaluated in combination with enzyme inhibitory and anti-tumor cell proliferation experiments. The experimental results showed that the screened compounds L-25, L-32, L-45 and L-81 exhibited nanomolar inhibitory activity against HDAC6, and exerted a certain degree of anti-proliferative activities against tumor cells, especially the cytotoxicity of L-45 to A375 (IC <subscript>50</subscript>  = 11.23 ± 1.27 μM) and the cytotoxicity of L-81 against HCT-116 (IC <subscript>50</subscript>  = 12.25 ± 1.13 μM). Additionally, the molecular mechanisms underlying the subtype selective inhibitory activities of the selected compounds were further elucidated using computational approaches, and the hotspot residues on HDAC6 contributing to the ligands' binding were identified. In summary, this study established a multi-layer screening scheme to quickly and effectively screen out hit compounds with enzyme inhibitory activity and anti-tumor cell proliferation, providing novel scaffolds for the subsequent anti-tumor drug design based on HDAC6 target.<br />Competing Interests: Declaration of competing interest The authors have no relevant conflicts of interest to disclose.<br /> (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
160
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
37196455
Full Text :
https://doi.org/10.1016/j.compbiomed.2023.107036