Ranking Peptide Binders by Affinity with AlphaFold**
A previous version of this manuscript has been deposited on a preprint server (https://doi.org/10.1101/2022.03.18.484931).
Abstract
AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding.
Conflict of interest
The authors declare no conflict of interest.
Open Research
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.