Definitive Metabolite Identification Coupled with Automated Ligand Identification System (ALIS) Technology: A Novel Approach to Uncover Structure-Activity Relationships and Guide Drug Design in a Factor IXa Inhibitor Program

J Med Chem. 2016 Mar 10;59(5):1818-29. doi: 10.1021/acs.jmedchem.5b01293. Epub 2016 Feb 22.

Abstract

A potent and selective Factor IXa (FIXa) inhibitor was subjected to a series of liver microsomal incubations, which generated a number of metabolites. Using automated ligand identification system-affinity selection (ALIS-AS) methodology, metabolites in the incubation mixture were prioritized by their binding affinities to the FIXa protein. Microgram quantities of the metabolites of interest were then isolated through microisolation analytical capabilities, and structurally characterized using MicroCryoProbe heteronuclear 2D NMR techniques. The isolated metabolites recovered from the NMR experiments were then submitted directly to an in vitro FIXa enzymatic assay. The order of the metabolites' binding affinity to the Factor IXa protein from the ALIS assay was completely consistent with the enzymatic assay results. This work showcases an innovative and efficient approach to uncover structure-activity relationships (SARs) and guide drug design via microisolation-structural characterization and ALIS capabilities.

MeSH terms

  • Animals
  • Automation*
  • Dose-Response Relationship, Drug
  • Drug Design*
  • Factor IXa / antagonists & inhibitors*
  • Factor IXa / metabolism
  • Fibrinolytic Agents / chemistry
  • Fibrinolytic Agents / metabolism
  • Fibrinolytic Agents / pharmacology*
  • Humans
  • Ligands
  • Molecular Structure
  • Nuclear Magnetic Resonance, Biomolecular*
  • Rats
  • Structure-Activity Relationship

Substances

  • Fibrinolytic Agents
  • Ligands
  • Factor IXa