Interleukin targeting &
affinity optimization

9/24

peptides with KD ~100nM

~10x

affinity improvement

97 nM

best affinity

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Starting peptide and AI-proposed position-specific mutation alphabets

01/ Background

  • The target is a protein from interleukin family.
  • Indication is an inflammatory disease.
  • Starting point:hard-to-drug: large and highly charged.stabilized by the organic linker, with a relatively weak binder affinity (1 µM).
  • Key interactions for the starting peptide were:
    • hydrogen bonds with ASP, ARG and backbone;
    • hydrophobic interactions with LEU;
    • ionic bond with ASP.
  • Main challenges are:
    • Main challenges are:
    • no SAR;
    • no co-crystal structure available.
  • The goal is to increase affinity.

02/ Methodology

  • We modeled peptide-protein complex and used AI-guided optimization with position-specific mutation alphabets (including non-canonical AAs)
  • 100K sequences were screened.
  • 24 peptides were synthesised and tested.

04/ Results

  • Affinity improved:
    • 9/24 peptides have affinity of ~100 nM.
    • best affinity of 97 nM achieved.
    • ~10x affinity improvement overall (1 µM → ~100 nM).
  • Key interactions for the best optimized peptide were:
    • hydrogen bonds with ASP, ARG and backbone;
    • many hydrophobic interactions with LEU and HIS;
    • ionic bond with ASP;
    • intrapeptide PI-cation stacking.
Optimized peptide with key interactions