The kinetics of folding-unfolding of a structurally diverse set of four proteins optimized for thermodynamic stability by rational redesign of surface charge-charge interactions is characterized experimentally. The folding rates are faster for designed variants compared with their wild-type proteins, whereas the unfolding rates are largely unaffected. A simple structure-based computational model, which incorporates the Debye-Hückel formalism for the electrostatics, was used and found to qualitatively recapitulate the experimental results. Analysis of the energy landscapes of the designed versus wild-type proteins indicates the differences in refolding rates may be correlated with the degree of frustration of their respective energy landscapes. Our simulations indicate that naturally occurring wild-type proteins have frustrated folding landscapes due to the surface electrostatics. Optimization of the surface electrostatics seems to remove some of that frustration, leading to enhanced formation of native-like contacts in the transition-state ensembles (TSE) and providing a less frustrated energy landscape between the unfolded and TS ensembles. Macroscopically, this results in faster folding rates. Furthermore, analyses of pairwise distances and radii of gyration suggest that the less frustrated energy landscapes for optimized variants are a result of more compact unfolded and TS ensembles. These findings from our modeling demonstrates that this simple model may be used to: (i) gain a detailed understanding of charge-charge interactions and their effects on modulating the energy landscape of protein folding and (ii) qualitatively predict the kinetic behavior of protein surface electrostatic interactions.protein folding | protein stability | charge-charge interaction | energy landscape | computational design T he energy landscape theory provides a conceptual framework to describe the ensemble nature of the protein folding process (1-3). However, a more detailed understanding of contributions from specific types of interactions remains an active area of research (4, 5). Particularly, the question of how interactions between charged residues modulate the funneled energy landscape is not well explored. These interactions are long-range and thus can alter the conformational ensemble at every step of the folding process. The interactions between charged residues are also nonspecific and either attractive or repulsive and therefore their potential effects on the folding energy landscape can be highly complex (6, 7). Traditionally, the modulation of electrostatic interactions in proteins was done by changing the pH or to a lesser degree changing the ionic strength of the solution (8, 9). Such approaches are complicated by the difficulties of predicting the titration properties of individual amino acid residues in the context of ensembles of protein conformations that are sampled during the folding reaction (10). A more attractive approach is to modulate electrostatic interactions via substitutions that perturb the thermody...

Optimization of surface exposed charge-charge interactions in the native state has emerged as an effective means to enhance protein stability; but the effect of electrostatic interactions on the kinetics of protein folding is not well understood. To investigate the kinetic consequences of surface charge optimization, we characterized the folding kinetics of a Fyn SH3 domain variant containing five amino acid substitutions that was computationally designed to optimize surface charge-charge interactions. Our results demonstrate that this optimized Fyn SH3 domain is stabilized primarily through an eight-fold acceleration in the folding rate. Analyses of the constituent single amino acid substitutions indicate that the effects of optimization of charge-charge interactions on folding rate are additive. This is in contrast to the trend seen in folded state stability, and suggests that electrostatic interactions are less specific in the transition state compared to the folded state. Simulations of the transition state using a coarse-grained chain model show that native electrostatic contacts are weakly formed, thereby making the transition state conducive to nonspecific, or even nonnative, electrostatic interactions. Because folding from the unfolded state to the folding transition state for small proteins is accompanied by an increase in charge density, nonspecific electrostatic interactions, that is, generic charge density effects can have a significant contribution to the kinetics of protein folding. Thus, the interpretation of the effects of amino acid substitutions at surface charged positions may be complicated and consideration of only native-state interactions may fail to provide an adequate picture.

Computational design of surface charge-charge interactions has been demonstrated to be an effective way to increase both the thermostability and the stability of proteins. To test the robustness of this approach for proteins with predominantly b-sheet secondary structure, the chicken isoform of the Fyn SH3 domain was used as a model system. Computational analysis of the optimal distribution of surface charges showed that the increase in favorable energy per substitution begins to level off at five substitutions; hence, the designed Fyn sequence contained four charge reversals at existing charged positions and one introduction of a new charge. Three additional variants were also constructed to explore stepwise contributions of these substitutions to Fyn stability. The thermodynamic stabilities of the variants were experimentally characterized using differential scanning calorimetry and far-UV circular dichroism spectroscopy and are in very good agreement with theoretical predictions from the model. The designed sequence was found to have increased the melting temperature, DT m ¼ 12.3 6 0.2°C, and stability, DDG(25°C) ¼ 7.1 6 2.2 kJ/mol, relative to the wild-type protein. The experimental data suggest that a significant increase in stability can be achieved through a very small number of amino acid substitutions. Consistent with a number of recent studies, the presented results clearly argue for a seminal role of surface charge-charge interactions in determining protein stability and suggest that the optimization of surface interactions can be an attractive strategy to complement algorithms optimizing interactions in the protein core to further enhance protein stability.