Peptide design by optimization on a data-parameterized protein interaction landscape

We applied the high-throughput interaction assay SORTCERY to measure thousands of protein-peptide binding affinities and used the data to parameterize models of the peptide-binding landscape for three members of the Bcl-2 family of proteins. We applied the models to design peptides that bound with high affinity and specificity to just one of Bcl-xL, Mcl-1, or Bfl-1. We designed additional peptides that bound selectively to two out of three of these proteins. The raw data provided are the multiplexed fastq files that serve as inputs to our analysis pipeline. Additional detail is available in our corresponding publication and at the following github repository. https://github.com/KeatingLab/sortcery_design DNA samples from yeast-surface display peptide libraries were deep sequenced after sorting with fluorescence activated cell sorting.