Predictive energy landscapes for folding α-helical transmembrane proteins

Abstract

We explore the hypothesis that the folding landscapes of membrane proteins are funneled once the proteins' topology within the membrane is established. We extend a protein folding model, the associative memory, water-mediated, structure, and energy model (AWSEM) by adding an implicit membrane potential and reoptimizing the force field to account for the differing nature of the interactions that stabilize proteins within lipid membranes, yielding a model that we call AWSEM-membrane. Once the protein topology is set in the membrane, hydrophobic attractions play a lesser role in finding the native structure, whereas polar-polar attractions are more important than for globular proteins. We examine both the quality of predictions made with AWSEM-membrane when accurate knowledge of the topology and secondary structure is available and the quality of predictions made without such knowledge, instead using bioinformatically inferred topology and secondary structure based on sequence alone. When no major errors are made by the bioinformatic methods used to assign the topology of the transmembrane helices, these two types of structure predictions yield roughly equivalent quality structures. Although the predictive energy landscape is transferable and not structure based, within the correct topological sector we find the landscape is indeed very funneled: Thermodynamic landscape analysis indicates that both the total potential energy and the contact energy decrease as native contacts are formed. Nevertheless the near symmetry of different helical packings with respect to native contact formation can result in multiple packings with nearly equal thermodynamic occupancy, especially at temperatures just below collapse.energy landscape theory | molecular dynamics T he folding of globular proteins has come to be well understood starting from Anfinsen's thermodynamic hypothesis (1), by means of statistical energy landscape theory (2-5) and its principle of minimal frustration. Evolution selects the sequences of most globular proteins so that folding is, by and large, thermodynamically controlled and the landscape is dominated by the interactions between residues that are close together in the folded state, i.e., the native contacts. In vivo folding of α-helical transmembrane proteins differs from the usually autonomous folding of globular proteins in that, during translation, another actor, the translocon, generally assists the nascent chain in either translocating across or integrating peptides into the lipid membrane. Topology, by which we mean the "specification of the number of transmembrane helices and their in and/or out orientations across the membrane" (ref. 6, p. 909), in vivo is thus initially established cotranslationally with few exceptions. Large barriers between alternate topologies once the protein is folded, along with the involvement of the translocon catalyst, suggest a role for kinetic control in folding of α-helical transmembrane proteins. In light of these differences, what aspects of energy landscape theory,...

Cooperative folding of a polytopic α-helical membrane protein involves a compact N-terminal nucleus and nonnative loops

“…The origin and significance of anomalous ϕ-values is almost entirely unexplored in the context of membrane proteins and requires additional investigation. The work in this paper provides the information needed for focused molecular dynamics simulations in appropriate membrane-mimicking systems (42) to investigate the existence and molecular details of these nonnative phenomena.…”

What protein folding teaches us about biological function and molecular machines

“…The Principle of Minimal Frustration indicates that a biomolecule's landscape may be described as being relatively smooth, where the native and functional configurations correspond to low-energy minima ( Figure 1). This principle has been instrumental in the development of a broad range of models for biomolecular dynamics in complex environments, such as folding in the presence of membranes [3 ]. One approach to studying minimally frustrated systems is through the use of 'structure-based' models, which span from coarse-grained [4] to all-atom [5] resolution.…”

Topological constraints and modular structure in the folding and functional motions of GlpG, an intramembrane protease

“…The implicit membrane model is described in ref. 19, and the assignment of residues into the intramembrane and extramembrane residues is described in Fig. S1.…”

“…Theoretical (19,20) and experimental (3,4) work suggests that at least some membrane proteins can reversibly fold and unfold without the aid of the translocon or chaperones in vitro. It is therefore likely that membrane protein folding landscapes are funneled, much like globular protein landscapes (21,22).…”