Deorphanizing Peptides Using Structure Prediction

J Chem Inf Model. 2023 May 8;63(9):2651-2655. doi: 10.1021/acs.jcim.3c00378. Epub 2023 Apr 24.

Abstract

Many endogenous peptides rely on signaling pathways to exert their function, but identifying their cognate receptors remains a challenging problem. We investigate the use of AlphaFold-Multimer complex structure prediction together with transmembrane topology prediction for peptide deorphanization. We find that AlphaFold's confidence metrics have strong performance for prioritizing true peptide-receptor interactions. In a library of 1112 human receptors, the method ranks true receptors in the top percentile on average for 11 benchmark peptide-receptor pairs.

Publication types

  • Letter

MeSH terms

  • Humans
  • Peptides* / metabolism
  • Signal Transduction*

Substances

  • Peptides