AI-ACCELERATED DRUG DISCOVERY

Stabilizing protein-protein interface

Designing Molecular glue to stabilize the membrane complex

AI revolutionizes the drug discovery process

Background

  • A complex of two proteins with unknown binding sites.
  • A binding pocket was identified by Receptor.AI at the protein-protein interface using a proprietary AI model for the binding site identification.
  • Two low-quality ligands are known with only mediocre binding affinity.
  • The goal is to design “molecular glue” to stabilize the membrane complex of 2 proteins associated with autophagy and neurodegeneration.

Methodology

  • Enamine stock collection of 3.2M compounds was subject to virtual screening.
  • 1000 top-ranked candidate compounds were selected.
  • 387 compounds were used for experimental validation.

Results

  • The experimental validation was conducted on the HEK 293 cell line to assess modulation of target protein expression.
  • Protein expression level was assessed by the Western blot. The hit criteria for the screening was set as a 120% increase in target protein concentration against the control, which resulted in the identification of seven hits.
  • The activity of all seven identified hit compounds, along with the absence of cytotoxicity, was substantiated through dose-response analysis.
  • Four active scaffolds were chosen for future series expansion, specifically the scaffolds of compound 1, 3, 4 and the shared scaffolds of compounds 2, 5-7.
  • The most promising hit compound 2 exhibited a nearly sub-micromolar EC50 in a cellular functional assay with a 400% higher potency compared to the best existing rivals.
The binding pose for the Compound 2 mentioned above
Western blot, Compound 2, HEK 293 cell line, 24h after treatment
Target protein concentration increase: assay Round 1, 50 uM
Dose-Response relationship for Compound 2. Treatment time 24 and 48 hours