Docking and QSAR Studies of Aryl-valproic Acid Derivatives to Identify Antiproliferative Agents Targeting the HDAC8

Author(s): Heidy Martínez-Pacheco, Guillermo Ramírez-Galicia, Midalia Vergara-Arias, Jurg Gertsch, Jonathan Manuel Fragoso-Vazquez, David Mendez-Luna, A. L. Abujamra, Cabrera-Perez Laura Cristina, Rosales-Hernandez Martha Cecilia, I Mendoza-Lujambio, Jose Correa-Basurto*.

Journal Name: Anti-Cancer Agents in Medicinal Chemistry

Volume 17 , Issue 7 , 2017

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Abstract:

Background: Histone deacetylase 8 (HDAC8) is a plausible target for the development of novel anticancer drugs using a metal-chelating group and hydrophobic moieties as pharmacophores. It is known that valproic acid (administered as its salt, sodium valproate; VPANa+) is an HDAC8 inhibitor characterized by its hydrophobic chains. Nevertheless, VPA is hepatotoxic and VPA analogues might be explored for less hepatotoxic antiproliferative compounds.

Method: In this work, docking and QSAR studies of 500 aryl-VPA derivatives as possible HDAC8 inhibitors were performed in order to explore and select potential anti-proliferative compounds. Docking results identified π−π, hydrogen bonds as the most important noncovalent interactions between HDAC8 (PDB: 3F07) and the ligands tested, whereas Belm4 was the best QSAR descriptor and classified as a 2D-BCUT descriptor.

Result: Based on theoretical studies, compound DAVP042 was synthesized and evaluated in vitro for its antiproliferative activities on several cancer cell lines (A549-lung, MCF-7-breast, HCT116-colon and U937- lymphoid tissue) in comparison to VPA, as well as for its inhibitory activity on HDAC8 using in vitro models. DAVP042 demonstrated to have antiproliferative activity on all cancer cell lines employed, not only suggesting that this compound should be further studied, but also demonstrating that the methodology herein employed is appropriated to identify new therapeutic candidates.

Keywords: Docking studies, QSAR studies, Artificial Neuron Network, Anticancer test, 2D-BCUT descriptors, derivatives.

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Article Details

VOLUME: 17
ISSUE: 7
Year: 2017
Page: [927 - 940]
Pages: 14
DOI: 10.2174/1871520616666161019143219
Price: $58

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