Lipid bilayer induces contraction of the denatured state ensemble of a helical-bundle membrane protein

Defining the denatured state ensemble (DSE) and disordered proteins is essential to understanding folding, chaperone action, degradation, and translocation. As compared with water-soluble proteins, the DSE of membrane proteins is much less characterized. Here, we measure the DSE of the helical membrane protein GlpG of Escherichia coli (E. coli) in native-like lipid bilayers. The DSE was obtained using our steric trapping method, which couples denaturation of doubly biotinylated GlpG to binding of two streptavidin molecules. The helices and loops are probed using limited proteolysis and mass spectrometry, while the dimensions are determined using our paramagnetic biotin derivative and double electron–electron resonance spectroscopy. These data, along with our Upside simulations, identify the DSE as being highly dynamic, involving the topology changes and unfolding of some of the transmembrane (TM) helices. The DSE is expanded relative to the native state but only to 15 to 75% of the fully expanded condition. The degree of expansion depends on the local protein packing and the lipid composition. E. coli’s lipid bilayer promotes the association of TM helices in the DSE and, probably in general, facilitates interhelical interactions. This tendency may be the outcome of a general lipophobic effect of proteins within the cell membranes.

The Volumetric Properties of the Transition State Ensemble for Protein Folding

Hydrostatic pressure together with the temperature is an important environmental variable that plays an essential role in biological adaptation of extremophilic organisms. In particular, the effects of hy-drostatic pressure on the rates of the protein folding/unfolding reaction are determined by the magni-tude and sign of the activation volume changes. Here we provide computational description of the ac-tivation volume changes for folding/unfolding reaction, and compare them with the experimental data for six different globular proteins. We find that the volume of the transition state ensemble is always in-between the folded and unfolded states. Based on this, we conclude that hydrostatic pressure will invariably slow down protein folding and accelerate protein unfolding.

Lipid Bilayer Induces Contraction of the Denatured State Ensemble of a Helical-Bundle Membrane Protein

Defining the denatured state ensemble (DSE) and intrinsically disordered proteins is essential to understanding protein folding, chaperone action, degradation, translocation and cell signaling. While a majority of studies have focused on water-soluble proteins, the DSE of membrane proteins is much less characterized. Here, we reconstituted the DSE of a helical bundle membrane protein GlpG of Escherichia coli in native lipid bilayers and measured its conformation and compactness. The DSE was obtained using steric trapping, which couples spontaneous denaturation of a doubly biotinylated GlpG to binding of two bulky monovalent streptavidin molecules. Using limited proteolysis and mass spectrometry, we mapped the flexible regions in the DSE. Using our paramagnetic biotin derivative and double electron-electron resonance spectroscopy, we determined the dimensions of the DSE. Finally, we employed our Upside model for molecular dynamics simulations to generate the DSE including the collapsed and fully expanded states in a bilayer. We find that the DSE is highly dynamic involving the topology changes of transmembrane segments and their unfolding. The DSE is expanded relative to the native state, but only to 55-90% of the fully expanded condition. The degree of expansion depends on the chemical potential with regards to local packing and the lipid composition. Our result suggests that the native lipid bilayer promotes the association of helices in the DSE of membrane proteins and, probably in general, facilitating interhelical interactions. This tendency may be the outcome of a general lipophobic effect of proteins within the cell membranes.

Evolution of dynamical networks enhances catalysis in a designer enzyme

Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by non-Arrhenius behaviour of many natural enzymes1,2. However, its physical origin and relationship to evolution of catalytic activity remain uncertain. Here, we show that directed evolution of a computationally designed Kemp eliminase introduces dynamical changes that give rise to an activation heat capacity absent in the original design3. Extensive molecular dynamics simulations show that evolution results in the closure of solvent exposed loops and better packing of the active site with transition state stabilising residues. Remarkably, these changes give rise to a correlated dynamical network involving the transition state and large parts of the protein. This network tightens the transition state ensemble, which induces an activation heat capacity and thereby nonlinearity in the temperature dependence. Our results have implications for understanding enzyme evolution (e.g. in explaining the role of distal mutations and evolutionary tuning of dynamical responses) and suggest that integrating dynamics with design and evolution will accelerate the development of efficient novel enzymes.

Novel Deep Level Image State Ensemble Enhancement Method for M87 Imaging

Standard spatial domain filters fail to adequately denoise and enhance the contrast of an image. These filters have drawbacks like oversmoothing, diminished texture, and lack of generative capabilities. This paper proposes a new method of image reconstruction, Image State Ensemble Enhancement (ISEE), based on our previous work, Image State Ensemble Decomposition (ISED). Deep level ISEE and ISED have been developed to produce a class of filters that can address these issues. Full-reference and no-reference quality metrics are used to assess the image, and the full reference metrics showed a marked improvement, while the no-reference metrics were often better than the test image. The test image was taken from the Spitzer Space Telescope (SST), and ISEE reconstruction yielded improved structural detail over that of ISED and the original test image. Glare and noise were reduced in a narrow bandwidth, which led to the discovery of a vortex-shaped structure and an outburst in M87′s dusty infrared core. The vortex is located over M87′s visible core and black hole. This is verified with an SST and Hubble Space Telescope (HST) overlay, ISEE processed image. A counter-jet channel was also discovered, and it appears to be the path of the unobservable superluminal counter-jet.

Sampling the Folding Transition State Ensemble in a Tube-Like Model of Protein

We used the tube model with Go-like potential for native contacts to study the folding transition of a designed three-helix bundle and a designed protein G-like structure. It is shown that both proteins in this model are two-state folders with a cooperative folding transition coincided with the collapse transition. We defined the transition states as protein conformations in a small region around the saddle point on a free energy surface with the energy and the conformational root-mean-square deviation (RMSD) from the native state as the coordinates. The transition state region on the free energy surface then was sampled by using the umbrella sampling technique. We show that the transition state ensemble is broad consisting of different conformations that have different folded and unfolded elements.

Temperature, Dynamics, and Enzyme-Catalyzed Reaction Rates

We review the adaptations of enzyme activity to different temperatures. Psychrophilic (cold-adapted) enzymes show significantly different activation parameters (lower activation enthalpies and entropies) from their mesophilic counterparts. Furthermore, there is increasing evidence that the temperature dependence of many enzyme-catalyzed reactions is more complex than is widely believed. Many enzymes show curvature in plots of activity versus temperature that is not accounted for by denaturation or unfolding. This is explained by macromolecular rate theory: A negative activation heat capacity for the rate-limiting chemical step leads directly to predictions of temperature optima; both entropy and enthalpy are temperature dependent. Fluctuations in the transition state ensemble are reduced compared to the ground state. We show how investigations combining experiment with molecular simulation are revealing fundamental details of enzyme thermoadaptation that are relevant for understanding aspects of enzyme evolution. Simulations can calculate relevant thermodynamic properties (such as activation enthalpies, entropies, and heat capacities) and reveal the molecular mechanisms underlying experimentally observed behavior.