QSAR Classification Models for Prediction of Hydroxamate Histone Deacetylase Inhibitor Activity against Malaria Parasites

Eva Hesping, Ming Jang Chua, Marc Pflieger, Yunan Qian, Lilong Dong, Prabhakar Bachu, Ligong Liu, Thomas Kurz, Gillian M. Fisher, Tina S. Skinner-Adams, Robert C. Reid, David P. Fairlie, Katherine T. Andrews, Alain-Dominique J.P. Gorse

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Malaria, caused by Plasmodium parasites, results in >400,000 deaths annually. There is no effective vaccine, and new drugs with novel modes of action are needed because of increasing parasite resistance to current antimalarials. Histone deacetylases (HDACs) are epigenetic regulatory enzymes that catalyze post-translational protein deacetylation and are promising malaria drug targets. Here, we describe quantitative structure–activity relationship models to predict the antiplasmodial activity of hydroxamate-based HDAC inhibitors. The models incorporate P. falciparum in vitro activity data for 385 compounds containing a hydroxamic acid and were subject to internal and external validation. When used to screen 22 new hydroxamate-based HDAC inhibitors for antiplasmodial activity, model A7 (external accuracy 91%) identified three hits that were subsequently verified as having potent in vitro activity against P. falciparum parasites (IC50 = 6, 71, and 84 nM), with 8 to 51-fold selectivity for P. falciparum versus human cells.
Original languageEnglish
Pages (from-to)106–117
Number of pages12
JournalACS Infectious Diseases
Volume8
Issue number1
DOIs
Publication statusPublished - 14 Jan 2022
Externally publishedYes

Keywords

  • Histone deacetylase
  • HDAC inhibitors
  • malaria
  • In silico
  • QSAR
  • in silico
  • histone deacetylase

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