Affiliation:
1. Department of Computer Science Dartmouth College Hanover New Hampshire USA
Abstract
AbstractWe propose a high‐throughput method for quantitatively measuring hundreds of protein–peptide binding affinities in parallel. In this assay, a solution of protein is dialyzed into a buffer containing a pool of potential binding peptides, such that upon equilibration the relative abundance of a peptide species is mathematically related to that peptide's dissociation constant, Kd. We use isobaric multiplexed quantitative proteomics to simultaneously determine the relative abundance, and hence the Kd and its associated error, for an entire peptide library. We apply this technique, which we call PEDAL (parallel equilibrium dialysis for affinity learning), to determine accurate Kd's between a PDZ domain and hundreds of peptides, spanning an affinity range of multiple orders of magnitude in a single experiment. PEDAL is a convenient, fast, and low‐cost method for measuring large numbers of protein–peptide affinities in parallel, providing a rare combination of true in‐solution binding equilibria with the ability to multiplex.
Funder
National Institutes of Health
Subject
Molecular Biology,Biochemistry