Docking and QSAR studies of aryl-valproic acid derivatives to identify antiproliferative agents targeting the HDAC8

Heidy Martínez-Pacheco, Guillermo Ramírez-Galicia, Midalia Vergara-Arias, Jürg Gertsch, Manuel Jonathan Fragoso-Vázquez, David Méndez-Luna, A. L. Abujamra, Cabrera Pérez Laura Cristina, Rosales Hernández Martha Cecilia, I. Mendoza-Lujambio, JosÉ Correa-Basurto

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

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.

Original languageEnglish
Pages (from-to)927-940
Number of pages14
JournalAnti-Cancer Agents in Medicinal Chemistry
Volume17
Issue number7
DOIs
StatePublished - 2017

Keywords

  • 2D-BCUT descriptors
  • Anticancer test
  • Artificial neuron network
  • Derivatives
  • Docking studies
  • QSAR studies

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