Predictive energy landscapes for protein–protein association

Abstract

We investigate protein-protein association using the associativememory, water-mediated, structure, and energy model (AWSEM), a coarse-grained protein folding model that has been optimized using energy-landscape theory. The potential was originally parameterized by enforcing a funneled nature for a database of dimeric interfaces but was later further optimized to create funneled folding landscapes for individual monomeric proteins. The ability of the model to predict interfaces was not tested previously. The present results show that simulated annealing of the model indeed is able to predict successfully the native interfaces of eight homodimers and four heterodimers, thus amounting to a flexible docking algorithm. We go on to address the relative importance of monomer geometry, flexibility, and nonnative intermonomeric contacts in the association process for the homodimers. Monomer surface geometry is found to be important in determining the binding interface, but it is insufficient. Using a uniform binding potential rather than the water-mediated potential results in sampling of misbound structures that are geometrically preferred but are nonetheless energetically disfavored by AWSEM, as well as in nature. Depending on the stability of the unbound monomers, nonnative contacts play different roles in the association process. For unstable monomers, thermodynamic states stabilized by nonnative interactions correspond to productive, on-pathway intermediates and can, therefore, catalyze binding through a fly-casting mechanism. For stable monomers, in contrast, states stabilized by nonnative interactions generally correspond to traps that impede binding.binding interface prediction | swapped contacts P rotein-protein interfaces encode information that is key to a molecular understanding of biological functions. The folding of proteins is well understood in the framework of energy landscape theory and its principle of minimal frustration. Are binding landscapes also funneled? Mechanistic consequences of funneled binding landscapes have been investigated using structure-based models (1-5). The agreement of these mechanisms with observation suggests that binding landscapes are generally funneled, explaining why topology is indeed a major factor in determining binding mechanisms (1). A statistical analysis of a large database of protein complexes revealed that for many of the complexes, the binding energy gap is indeed larger than expected knowing the variance of the binding energy (6), the hallmark feature of a funneled landscape (7). When further testing this idea, Papoian et al. discovered that for other complexes, to have a funneled landscape for binding, unanticipated water-mediated interactions were required. They developed a water-mediated potential encoding these interactions (8). This transferable potential was later optimized to create funneled folding landscapes that successfully predict the structure of monomeric proteins (9, 10). Therefore, there is considerable support for the idea that, like folding landsc...

Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

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