title: Exploring the charge space of protein-protein association: a proteomic study.
abstract: The rate of association of a protein complex is a function of an intrinsic basal rate and of the magnitude of electrostatic steering. In the present study we analyze the contribution of electrostatics towards the association rate of proteins in a database of 68 transient hetero-protein-protein complexes. Our calculations are based on an upgraded version of the computer algorithm PARE, which was shown to successfully predict the impact of mutations on k(on) by calculating the difference in Columbic energy of interaction of a pair of proteins. HyPare (http://bip.weizmann.ac.il/HyPare), automatically calculates the impact of mutations on a per-residue basis for all residues of a protein-protein interaction, achieving a precision similar to that of PARE. Our calculations show that electrostatics play a marginal role (<10 fold) in determining the rate of association for about half of the complexes in the database. Strong electrostatic steering, which results in an increase of over 100-fold in k(on), was calculated for about 25% of the complexes. Applying HyPare to all 68 complexes in the database shows that a small number of residues are hotspots for association. About 40% of the hotspots are calculated to increase the rate of association upon mutation, and thus increase binding affinity. This is a much higher ratio than found for hotspots for dissociation, where the large majority cause weaker binding. About 40% of the hotspots are located outside the physical boundary of the binding site, making them ideal candidates for protein engineering. Our data shows that a majority of protein-protein complexes are not optimized for fast association. Hotspots are not evenly distributed between all types of amino acids. About 75% of all hotspots are of charged residues. This is understandable, as a charge-reverse mutant changes the total charge by 2. The small number of hydrophobic residues that are hotspots upon mutation probably relates to their location and surrounding. For 18 out of the 68 complexes in the database, experimental values of k(on) are available. For these, a basal rate of association was calculated to be in the range of 10(4)M(-1)s(-1) to 10(7)M(-1)s(-1). Some of these rates were verified independently from experimental mutant data. The basal rates were correlated with the size of the proteins and the shape of the interface.
authors.affiliation: The Weizmann Institute of Science, Rehovot, Israel.
authors.forename: Yossi
authors.initials: Y
authors.lastname: Shaul
authors.forename: Gideon
authors.initials: G
authors.lastname: Schreiber
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry; D001665:Binding Sites; D055592:Biophysical Phenomena; D001703:Biophysics; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D030562:Databases, Protein; D007700:Kinetics; D008958:Models, Molecular; D015233:Models, Statistical; D009154:Mutation; D011485:Protein Binding; D011487:Protein Conformation; D017510:Protein Folding; D025941:Protein Interaction Mapping; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics / Q000379:methods*; D012984:Software; D055672:Static Electricity
chemical_list: D000596:Amino Acids; D011506:Proteins