Deorphanizing Peptides Using Structure Prediction
Research output: Contribution to journal › Journal article › Research › peer-review
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.
|Journal of Chemical Information and Modeling
|Number of pages
|Published - 2023
© 2023 American Chemical Society.