Metabolic Clustering Analysis as a Strategy for Compound Selection in the Drug Discovery Pipeline for Leishmaniasis

ACS Chem Biol. 2018 May 18;13(5):1361-1369. doi: 10.1021/acschembio.8b00204. Epub 2018 Apr 24.

Abstract

A lack of viable hits, increasing resistance, and limited knowledge on mode of action is hindering drug discovery for many diseases. To optimize prioritization and accelerate the discovery process, a strategy to cluster compounds based on more than chemical structure is required. We show the power of metabolomics in comparing effects on metabolism of 28 different candidate treatments for Leishmaniasis (25 from the GSK Leishmania box, two analogues of Leishmania box series, and amphotericin B as a gold standard treatment), tested in the axenic amastigote form of Leishmania donovani. Capillary electrophoresis-mass spectrometry was applied to identify the metabolic profile of Leishmania donovani, and principal components analysis was used to cluster compounds on potential mode of action, offering a medium throughput screening approach in drug selection/prioritization. The comprehensive and sensitive nature of the data has also made detailed effects of each compound obtainable, providing a resource to assist in further mechanistic studies and prioritization of these compounds for the development of new antileishmanial drugs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antiprotozoal Agents / chemistry
  • Antiprotozoal Agents / therapeutic use*
  • Cluster Analysis
  • Drug Discovery*
  • Drug Evaluation, Preclinical / methods
  • Electrophoresis, Capillary
  • High-Throughput Screening Assays
  • Leishmania donovani / drug effects
  • Leishmania donovani / metabolism
  • Leishmaniasis / drug therapy*
  • Mass Spectrometry
  • Metabolomics
  • Principal Component Analysis
  • Protozoan Proteins / metabolism

Substances

  • Antiprotozoal Agents
  • Protozoan Proteins