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 language | English |
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Journal | Journal of Chemical Information and Modeling |
Volume | 63 |
Issue number | 9 |
Number of pages | 5 |
ISSN | 1549-9596 |
DOIs | |
Publication status | Published - 2023 |
Bibliographical note
Publisher Copyright:© 2023 American Chemical Society.