Globally the energy landscape of a folding protein resembles a partially rough funnel. The local roughness of the funnel reflects transient trapping of the protein configurations in local free energy minima. The overall funnel shape of the landscape, superimposed on this roughness, arises because the interactions present in the native structure of natural proteins conflict with each other much less than expected if there were no constraints of evolutionary design to achieve reliable and relatively fast folding. The kinetics of folding is best considered as a progressive organization of an ensemble of partially folded structures through which the protein passes through on its way to the folded structure.
The folding mechanisms for several fast folding proteins can be quantitatively described using an energy landscape theory to set up the correspondence with simulations of protein minimalist models. Using these simulations together with analytical theory, we can learn about good (minimally frustrated) folding sequences and non-folding (frustrated) sequences. An important idea that emerges from the energy landscape theory is that subtle features of the protein landscape can profoundly affect the apparent mechanism of folding. The relationship between various characteristic temperatures in the phase diagrams and landmarks in the folding funnel at fixed temperatures can be used to classify different folding behaviors. Experiments on the dependence of the folding and unfolding times, and the stability of these proteins to denaturant concentration and site-directed mutagenesis, and on the early events of folding allow us to infer the global characteristics of the energy landscape.
In addition to need to minimize energetic frustration, the topology of the native fold also plays a major role in the folding mechanism. Some folding motifs are easier to design than others suggesting the possibility that evolution not only selected sequences with sufficiently small energetic frustration but also selected more easily designable native structures. We have demonstrated for several proteins (such as CI2 and SH3) that they are sufficiently well designed (i.e., reduced energetic frustration) that much of the heterogeneity observed in their transition state ensemble (TSE) is determined by topology. Topological effects go beyond the structure of the TSE. The overall structure of the on-route and off-route (traps) intermediates for the folding of more complex proteins is also strongly influenced by topology. Utilizing this theoretical framework, simulations of minimalist models and their connections to more computationally-expensive all-atom simulations, we are now in the process of obtaining a quantitative understanding of the folding problem, which allows for a direct comparison to a new generation of folding experiments. Connections between the folding landscape and protein function will also be discussed.
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