Deorphanizing Peptides Using Structure Prediction

Felix Teufel*, Jan C. Refsgaard, Marina A. Kasimova, Kristine Deibler, Christian T. Madsen, Carsten Stahlhut, Mads Grønborg, Ole Winther, Dennis Madsen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

11 Citations (Scopus)

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.

Original languageEnglish
JournalJournal of Chemical Information and Modeling
Volume63
Issue number9
Number of pages5
ISSN1549-9596
DOIs
Publication statusPublished - 2023

Bibliographical note

Publisher Copyright:
© 2023 American Chemical Society.

Cite this