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||Journal of Chemical Information and Modeling|
|Number of pages||5|
|Publication status||Published - 2023|
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