We explore the similarities and differences between the energy landscapes of proteins that have been selected by nature and those of some proteins designed by humans. Natural proteins have evolved to function as well as fold, and this is a source of energetic frustration. The sequence of Top7, on the other hand, was designed with architecture alone in mind using only native state stability as the optimization criterion. Its topology had not previously been observed in nature. Experimental studies show that the folding kinetics of Top7 is more complex than the kinetics of folding of otherwise comparable naturally occurring proteins. In this paper, we use structure prediction tools, frustration analysis, and free energy profiles to illustrate the folding landscapes of Top7 and two other proteins designed by Takada. We use both perfectly funneled (structure-based) and predictive (transferable) models to gain insight into the role of topological versus energetic frustration in these systems and show how they differ from those found for natural proteins. We also study how robust the folding of these designs would be to the simplification of the sequences using fewer amino acid types. Simplification using a five amino acid type code results in comparable quality of structure prediction to the full sequence in some cases, while the two-letter simplification scheme dramatically reduces the quality of structure prediction.

We investigate the folding of GlpG, an intramembrane protease, using perfectly funneled structure-based models that implicitly account for the absence or presence of the membrane. These two models are used to describe, respectively, folding in detergent micelles and folding within a bilayer, which effectively constrains GlpG's topology in unfolded and partially folded states. Structural free-energy landscape analysis shows that although the presence of multiple folding pathways is an intrinsic property of GlpG's modular functional architecture, the large entropic cost of organizing helical bundles in the absence of the constraining bilayer leads to pathways that backtrack (i.e., local unfolding of previously folded substructures is required when moving from the unfolded to the folded state along the minimum free-energy pathway). This backtracking explains the experimental observation of thermodynamically destabilizing mutations that accelerate GlpG's folding in detergent micelles. In contrast, backtracking is absent from the model when folding is constrained within a bilayer, the environment in which GlpG has evolved to fold. We also characterize a near-native state with a highly mobile transmembrane helix 5 (TM5) that is significantly populated under folding conditions when GlpG is embedded in a bilayer. Unbinding of TM5 from the rest of the structure exposes GlpG's active site, consistent with studies of the catalytic mechanism of GlpG that suggest that TM5 serves as a substrate gate to the active site.membrane proteins | micelle folding | bilayer folding | folding mechanism | intramembrane proteolysis G lpG is a rhomboid protease that sits and functions in the cell membrane. GlpG's homologs are found across all kingdoms of life. GlpG has been the subject of several biophysical experimental studies aimed toward understanding membrane protein folding and the relationships among protein structure, dynamics, and function (1-5). An extensive experimental φ-value analysis found φ-values significantly different from zero, indicative of structural changes during the rate-limiting step of folding, in transmembrane helices 1 through 5 (TM1-5) and the intervening loops (4). Most of the nonzero φ-values, particularly in TM3-5 and in the large loop L1, were negative, meaning that although the corresponding mutation destabilizes the native state, the mutation nonetheless accelerates folding. The preponderance of negative φ-values was puzzling and unprecedented, and at the time, these effects were tentatively ascribed to nonnative interactions in the transition state ensemble. In this work, we show that, in fact, simple models with perfectly funneled energy landscapes that lack nonnative interactions are able to explain the origin of these negative φ-values and how the values arise when folding in detergent micelles rather than bilayers.α-Helical membrane protein folding is thought to occur in two stages in vivo (6). The first stage, setting up the proper topology of transmembrane helices, is handled by the translocon (7,8)...

We study the energy landscapes for membrane protein oligomerization using the Associative memory, Water mediated, Structure and Energy Model with an implicit membrane potential (AWSEM-membrane), a coarse-grained molecular dynamics model previously optimized under the assumption that the energy landscapes for folding α-helical membrane protein monomers are funneled once their native topology within the membrane is established. In this study we show that the AWSEM-membrane force field is able to sample near native binding interfaces of several oligomeric systems. By predicting candidate structures using simulated annealing, we further show that degeneracies in predicting structures of membrane protein monomers are generally resolved in the folding of the higher order assemblies as is the case in the assemblies of both nicotinic acetylcholine receptor and V-type Na(+)-ATPase dimers. The physics of the phenomenon resembles domain swapping, which is consistent with the landscape following the principle of minimal frustration. We revisit also the classic Khorana study of the reconstitution of bacteriorhodopsin from its fragments, which is the close analogue of the early Anfinsen experiment on globular proteins. Here, we show the retinal cofactor likely plays a major role in selecting the final functional assembly.