Login / Signup

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

Eva HespingMing Jang ChuaMarc PfliegerYunan QianLilong DongPrabhakar BachuLigong LiuThomas KurzGillian M FisherTina S Skinner-AdamsRobert C ReidDavid P FairlieKatherine T AndrewsAlain-Dominique J P Gorse
Published in: ACS infectious diseases (2022)
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 (IC 50 = 6, 71, and 84 nM), with 8 to 51-fold selectivity for P. falciparum versus human cells.
Keyphrases
  • plasmodium falciparum
  • histone deacetylase
  • dna methylation
  • structure activity relationship
  • gene expression
  • high resolution
  • deep learning
  • mass spectrometry
  • protein protein
  • amino acid
  • data analysis
  • drug induced