Protein-protein interactions: organization, cooperativity and mapping in a bottom-up Systems Biology approach.

Understanding and ultimately predicting protein associations is immensely important for functional genomics and drug design. Here, we propose that binding sites have preferred organizations. First, the hot spots cluster within densely packed 'hot regions'. Within these regions, they form networks of interactions. Thus, hot spots located within a hot region contribute cooperatively to the stability of the complex. However, the contributions of separate, independent hot regions are additive. Moreover, hot spots are often already pre-organized in the unbound (free) protein states. Describing a binding site through independent local hot regions has implications for binding site definition, design and parametrization for prediction. The compactness and cooperativity emphasize the similarity between binding and folding. This proposition is grounded in computation and experiment. It explains why summation of the interactions may over-estimate the stability of the complex. Furthermore, statistically, charge-charge coupling of the hot spots is disfavored. However, since within the highly packed regions the solvent is screened, the electrostatic contributions are strengthened. Thus, we propose a new description of protein binding sites: a site consists of (one or a few) self-contained cooperative regions. Since the residue hot spots are those conserved by evolution, proteins binding multiple partners at the same sites are expected to use all or some combination of these regions.