Computational Alanine Scanning of Protein-Protein Interfaces

Abstract

Protein-protein interactions are key components of all signal transduction processes, so methods to alter these interactions promise to become important tools in dissecting function of connectivities in these networks. We have developed a fast computational approach for the prediction of energetically important amino acid residues in protein-protein interfaces (available at http://robetta.bakerlab.org/alaninescan ), which we, following Peter Kollman, have termed "computational alanine scanning." The input consists of a three-dimensional structure of a protein-protein complex; output is a list of "hot spots," or amino acid side chains that are predicted to significantly destabilize the interface when mutated to alanine, analogous to the results of experimental alanine-scanning mutagenesis. 79% of hot spots and 68% of neutral residues were correctly predicted in a test of 233 mutations in 19 protein-protein complexes. A single interface can be analyzed in minutes. The computational methodology has been validated by the successful design of protein interfaces with new specificity and activity, and has yielded new insights into the mechanisms of receptor specificity and promiscuity in biological systems.