Energy Landscape Of Proteins Research Articles

The role of continuous and discrete water structures in protein function

Proteins have evolved to perform numerous roles as specific catalysts and nano-machines. Some of the mechanisms exploited by evolution are clear. Hydrophobicity drives the stabilization energy of folding, charges mediate long-range interactions and facilitate catalysis, and specific geometries and hydrogen bonding patterns facilitate molecular recognition and catalysis. In this work, we examine the energy landscape of protein dynamics in terms of the continuous and discrete water structures that control protein dynamics. We observe that the internal structures at the active site of proteins are constantly shaped by strong interactions with hydration shell and bulk water motions. By describing the energy landscape of proteins in terms of its three component motions; conformational, hydration and protonation, and electronic structure, it is possible to systematically understand protein function.

On destabilization of the Fenna–Matthews–Olson complex of Chlorobaculum tepidum

The Fenna-Matthews-Olson (FMO) complex from the green sulfur bacterium Chlorobaculum tepidum was studied with respect to its stability. We provide a critical assessment of published and recently measured optical spectra. FMO complexes were found to destabilize over time producing spectral shifts, with destabilized samples having significantly higher hole-burning efficiencies; indicating a remodeled protein energy landscape. Observed correlated peak shifts near 825 and 815nm suggest possible correlated (protein) fluctuations. It is proposed that the value of 35cm(-1) widely used for reorganization energy (E λ ), which has important implications for the contributions to the coherence rate (Kreisbeck and Kramer 3:2828-2833, 2012), in various modeling studies of two-dimensional electronic spectra is overestimated. We demonstrate that the value of E λ is most likely about 15-22cm(-1) and suggest that spectra reported in the literature (often measured on different FMO samples) exhibit varied peak positions due to different purification/isolation procedures or destabilization effects.

Modeling of Various Optical Spectra in the Presence of Slow Excitation Energy Transfer in Dimers and Trimers with Weak Interpigment Coupling: FMO as an Example

We present an improved simulation methodology to describe nonphotochemical hole-burned (NPHB) spectra. The model, which includes both frequency-dependent excitation energy transfer (EET) rate distributions and burning following EET, provides reasonable fits of various optical spectra including resonant and nonresonant holes in the case of FMO complex. A qualitative description of the NPHB process in light of a very complex protein energy landscape is briefly discussed. As an example, we show that both resonant and nonresonant HB spectra obtained for the 825 nm band of the trimeric FMO of C. tepidum are consistent with the presence of a relatively slow EET between the lowest energy states of the monomers of the trimer (mostly localized on BChl a 3), with a weak (∼1 cm(-1)) coupling between these states revealed via calculated emission spectra. We argue that the nature of the so-called 825 nm absorption band of the FMO trimer, contrary to the presently accepted consensus, cannot be explained by a single transition.

A Conformational Ensemble Derived Using NMR Methyl Chemical Shifts Reveals a Mechanical Clamping Transition That Gates the Binding of the HU Protein to DNA

Recent improvements in the accuracy of structure-based methods for the prediction of nuclear magnetic resonance chemical shifts have inspired numerous approaches for determining the secondary and tertiary structures of proteins. Such advances also suggest the possibility of using chemical shifts to characterize the conformational fluctuations of these molecules. Here we describe a method of using methyl chemical shifts as restraints in replica-averaged molecular dynamics (MD) simulations, which enables us to determine the conformational ensemble of the HU dimer and characterize the range of motions accessible to its flexible β-arms. Our analysis suggests that the bending action of HU on DNA is mediated by a mechanical clamping mechanism, in which metastable structural intermediates sampled during the hinge motions of the β-arms in the free state are presculpted to bind DNA. These results illustrate that using side-chain chemical shift data in conjunction with MD simulations can provide quantitative information about the free energy landscapes of proteins and yield detailed insights into their functional mechanisms.

Accelerate Sampling in Atomistic Energy Landscapes Using Topology-Based Coarse-Grained Models

We describe a multiscale enhanced sampling (MSES) method where efficient topology-based coarse-grained models are coupled with all-atom ones to enhance the sampling of atomistic protein energy landscape. The bias from the coupling is removed by Hamiltonian replica exchange, thus allowing one to benefit simultaneously from faster transitions of coarse-grained modeling and accuracy of atomistic force fields. The method is demonstrated by calculating the conformational equilibria of several small but nontrivial β-hairpins with varied stabilities.

Heterogeneity of Protein Substates Visualized by Spin-label EPR

The energy landscape of proteins is characterized by a hierarchy of substates, which give rise to conformational heterogeneity at low temperatures. In multiply spin-labeled membranous Na,K-ATPase, this heterogeneous population of conformations is manifest by strong inhomogeneous broadening of the electron paramagnetic resonance (EPR) line shapes and nonexponential spin-echo decays, which undergo a transition to homogeneous broadening and exponential relaxation at higher temperatures (previous study). In this study, we apply these EPR methods to small water-soluble proteins, of the type for which the existence of conformational substates is well established. Both α-helical and β-sheet aqueous proteins that are spin-labeled on a single cysteine residue display spin-echo decays with a single phase-memory time T2M and conventional EPR line shapes with predominantly homogeneous broadening, over a broad range of temperatures from 77 K to ∼ 250 K or higher. Above ∼ 200 K, the residual inhomogeneous broadening is reduced almost to zero. In contrast, both the proteins and the spin label alone, when in a glycerol-water mixture below the glass transition, display heterogeneity in spin-echo phase-memory time and a stronger inhomogeneous broadening of the conventional line shapes, similar to multiply spin-labeled membranous Na,K-ATPase below 200 K. Above 200 K (or the glass transition), a single phase-memory time and predominantly homogeneous broadening are found in both spin-label systems. The results are discussed in terms of solvent-mediated protein transitions, the ability of single spin-label sites to detect conformational heterogeneity, and the desirability of exploring multiple sites for proteins with the size and complexity of the Na,K-ATPase.

Effect of TMAO and betaine on the energy landscape of photosystem I

The accumulation of organic co-solvents in cells is a basic strategy for organisms from various species to increase stress tolerance in extreme environments. Widespread representatives of this class of co-solvents are trimethylamine-N-oxide (TMAO) and betaine; these small molecules are able to stabilize the native conformation of proteins and prevent their aggregation. Despite their importance, detailed experimental studies on the impact of these co-solvents on the energy landscape of proteins have not yet been carried out. We use single-molecule spectroscopy at cryogenic temperatures to examine the influence of these physiological relevant co-solvents on photosystem I (PSI) from Thermosynechococcus elongatus. In contrast to PSI ensemble spectra, which are almost unaffected by the addition of TMAO and betaine, statistical analysis of the fluorescence emission from individual PSI trimers yields insight into the interaction of the co-solvents with PSI. The results show an increased homogeneity upon addition of TMAO or betaine. The number of detectable zero-phonon lines (ZPLs) is reduced, indicating spectral diffusion processes with faster rates. In the framework of energy landscape model these findings indicate that co-solvents lead to reduced barrier heights between energy valleys, and thus efficient screening of protein conformations can take place.

Mapping the Energy and Diffusion Landscapes of Membrane Proteins at the Cell Surface Using High-Density Single-Molecule Imaging and Bayesian Inference: Application to the Multiscale Dynamics of Glycine Receptors in the Neuronal Membrane

Protein mobility is conventionally analyzed in terms of an effective diffusion. Yet, this description often fails to properly distinguish and evaluate the physical parameters (such as the membrane friction) and the biochemical interactions governing the motion. Here, we present a method combining high-density single-molecule imaging and statistical inference to separately map the diffusion and energy landscapes of membrane proteins across the cell surface at ∼100 nm resolution (with acquisition of a few minutes). Upon applying these analytical tools to glycine neurotransmitter receptors at inhibitory synapses, we find that gephyrin scaffolds act as shallow energy traps (∼3 kBT) for glycine neurotransmitter receptors, with a depth modulated by the biochemical properties of the receptor-gephyrin interaction loop. In turn, the inferred maps can be used to simulate the dynamics of proteins in the membrane, from the level of individual receptors to that of the population, and thereby, to model the stochastic fluctuations of physiological parameters (such as the number of receptors at synapses). Overall, our approach provides a powerful and comprehensive framework with which to analyze biochemical interactions in living cells and to decipher the multiscale dynamics of biomolecules in complex cellular environments.

Exploring the Energy Landscape through Ancestral Proteins

How does a protein's energy landscape change over an evolutionary time scale, and could a study of ancestral sequences reveal novel features of the landscape? Although there has been significant advances protein structure prediction from its primary sequence, extracting features of the entire energy landscape remains a challenge. There is limited understanding on how variations in the sequence that take place over the course of an evolutionary time scale change the landscape to yield novel properties and function. Past research on the landscape has focused on extant proteins, which represent only a small portion of proteins that have existed since the origin of life. Examining the ancestors of current proteins should provide additional insight into the properties of proteins and the process of protein evolution, and ultimately, further our understanding of the depth of information encoded within an amino acid sequence. We conducted an ancestral sequence reconstruction of ribonuclease H1, a biophysically well-characterized protein. A total of seven ancestral proteins along the mesophilic and thermophilic lineages were constructed and studied. This study reports on the characterization of the folding pathway and stability of the last common ancestral protein between E. coli and T. thermophilus ribonucleases H.

Effects of Neutral, Capped Ends Versus Charged Ends on the Folding of the Trp-cage Miniprotein

Charge-charge interactions have a significant impact on the free energy landscape of proteins. The role addition or subtraction of charged groups can play in the stabilization or destabilization of meta-stable non-native states of proteins remains relatively unstudied in detail. Problematically, current experimental methods can only indirectly characterize the non-native states of a protein. All-atom molecular dynamics simulations provide a useful tool for studying the non-native states of a protein but are limited in scale to the smallest proteins. Therefore, in order to study effects of charges while ensuring adequate sampling, we choose to simulate a small, fast-folding model protein, the Trp-cage, with replica-exchange molecular dynamics. As most simulations use a neutral end, capped sequence while experiments tend to use a charged end, zwitterionic variant, we chose to simulate and compare the folding of the Trp-cage both with neutral, capped ends and in zwitterionic form with a positively charged N terminus and a negatively charged C terminus. We find that while the native state of the protein remains relatively unchanged, the equilibration time for the charged end simulation is much longer, suggesting a rougher folding landscape. Analysis suggests the formation of meta-stable states characterized by the possession of non-native charge pairs. Furthermore, we also report an increase in beta-sheet content that cannot be directly explained by the formation of a specific non-native charge pair, indicating the addition of charges plays a much more complex role than the direct creation of non-native charge pairs. We finally use string methods to determine the most probable transition path between non-native meta-stable states and the native state in order to better explain the factors resulting in the increase in equilibration time for the simulation.

Exploring the Complex Energy Landscape of Protein Unfolding Under Force

Optical tweezers have enabled the use of extremely low mechanical forces to study the unfolding and refolding of single protein biomolecules. We investigated the complex mechanical behavior of the src SH3 domain, a classical two-state folding protein. When a shearing force is applied on the terminal β-strand, the protein accesses parallel unfolding pathways, as indicated by the biphasic force dependence of the unfolding rates. We characterized the mechanical transition states for the two pathways by developing a protein engineering approach analogous to the phi-value methodology used in bulk studies. Interestingly, the transition state of the high-force unfolding pathway has more similarities with the zero-force, bulk unfolding pathway. The transition state is highly polarized under zero-force conditions and at high forces. However, at intermediate forces, the transition state is very diffuse, as indicated by a phi-value of ∼0.5 for all the src SH3 variants. To the best of our knowledge, this study represents the first instance of an experimentally observed, force-dependent change in the malleability of the transition state structure.

A Zoo of Slow Dynamics

Significantly slow dynamics, namely subdiffusion, is ubiquitous - especially in the biological context. The fingerprint of subdiffusive dynamics is that the mean squared displacement grows sublinearly in time - but there are very different physical mechanisms that can lead to this same behavior! Discerning between the relevant underlying physical realities is crucial to the understanding of the system at hand. A toolbox is presented with the aim of clarifying the differences between the different mechanisms, and presenting possible complications. We focus on a test for discerning between ergodic models, presenting an interesting application which sheds light on the structure of the energy landscape of proteins.

An effective coarse-grained model for biological simulations: recent refinements and validations.

Exploring the free energy landscape of proteins and modeling the corresponding functional aspects presents a major challenge for computer simulation approaches. This challenge is due to the complexity of the landscape and the enormous computer time needed for converging simulations. The use of various simplified coarse grained (CG) models offers an effective way of sampling the landscape, but most current models are not expected to give a reliable description of protein stability and functional aspects. The main problem is associated with insufficient focus on the electrostatic features of the model. In this respect, our recent CG model offers significant advantage as it has been refined while focusing on its electrostatic free energy. Here we review the current state of our model, describing recent refinements, extensions, and validation studies while focusing on demonstrating key applications. These include studies of protein stability, extending the model to include membranes, electrolytes and electrodes, as well as studies of voltage-activated proteins, protein insertion through the translocon, the action of molecular motors, and even the coupling of the stalled ribosome and the translocon. The examples discussed here illustrate the general potential of our approach in overcoming major challenges in studies of structure function correlation in proteins and large macromolecular complexes.

COMPARING FOLDING MECHANISMS OF DIFFERENT PRION PROTEINS BY Gō MODEL

Prions are associated with neurodegenerative diseases induced by transmissible spongiform encephalopathies. The infectious scrapie form is referred to as PrP Sc , which has conformational change from normal prion with predominant α-helical conformation to the abnormal PrP Sc that is rich in β-sheet content. Neurodegenerative diseases have been found from both human and bovine sources, but there are no reports about infected by transmissible spongiform encephalopathies from rabbit, canine and horse sources. Here we used coarse-grained Gō model to compare the difference among human, bovine, rabbit, canine, and horse normal (cellular) prion proteins. The denatured state of normal prion has relation with the conversion from normal to abnormal prion protein, so we used all-atom Gō model to investigate the folding pathway and energy landscape for human prion protein. Through using coarse-grained Gō model, the cooperativity of the five prion proteins was characterized in terms of calorimetric criterion, sigmoidal transition, and free-energy profile. The rabbit and horse prion proteins have higher folding free-energy barrier and cooperativity, and canine prion protein has slightly higher folding free-energy barrier comparing with human and bovine prion proteins. The results from all-atom Gō model confirmed the validity of C α-Gō model. The correlations of our results with previous experimental and theoretical researches were discussed.

Relaxation of backbone bond geometry improves protein energy landscape modeling

A key issue in macromolecular structure modeling is the granularity of the molecular representation. A fine-grained representation can approximate the actual structure more accurately, but may require many more degrees of freedom than a coarse-grained representation and hence make conformational search more challenging. We investigate this tradeoff between the accuracy and the size of protein conformational search space for two frequently used representations: one with fixed bond angles and lengths and one that has full flexibility. We performed large-scale explorations of the energy landscapes of 82 protein domains under each model, and find that the introduction of bond angle flexibility significantly increases the average energy gap between native and non-native structures. We also find that incorporating bonded geometry flexibility improves low resolution X-ray crystallographic refinement. These results suggest that backbone bond angle relaxation makes an important contribution to native structure energetics, that current energy functions are sufficiently accurate to capture the energetic gain associated with subtle deformations from chain ideality, and more speculatively, that backbone geometry distortions occur late in protein folding to optimize packing in the native state.

Protein energy landscapes determined by five-dimensional crystallography

Free-energy landscapes decisively determine the progress of enzymatically catalyzed reactions [Cornish-Bowden (2012), Fundamentals of Enzyme Kinetics, 4th ed.]. Time-resolved macromolecular crystallography unifies transient-state kinetics with structure determination [Moffat (2001), Chem. Rev. 101, 1569-1581; Schmidt et al. (2005), Methods Mol. Biol. 305, 115-154; Schmidt (2008), Ultrashort Laser Pulses in Medicine and Biology] because both can be determined from the same set of X-ray data. Here, it is demonstrated how barriers of activation can be determined solely from five-dimensional crystallography, where in addition to space and time, temperature is a variable as well [Schmidt et al. (2010), Acta Cryst. A66, 198-206]. Directly linking molecular structures with barriers of activation between them allows insight into the structural nature of the barrier to be gained. Comprehensive time series of crystallographic data at 14 different temperature settings were analyzed and the entropy and enthalpy contributions to the barriers of activation were determined. One hundred years after the discovery of X-ray scattering, these results advance X-ray structure determination to a new frontier: the determination of energy landscapes.

Energy landscape and dynamics of proteins: An exact analysis of a simplified lattice model

We present the results of exact numerical studies of the energy landscape and the dynamics of a 12-monomer chain with contact interactions encoding the ground state on a square lattice. In spite of its simplicity, the model is shown to exhibit behavior at odds with the standard picture of proteins.

Complex Energy Landscape of a Giant Repeat Protein

Here, we reveal a remarkable complexity in the unfolding of giant HEAT-repeat protein PR65/A, a molecular adaptor for the heterotrimeric PP2A phosphatases. The repeat array ruptures at multiple sites, leading to intermediate states with noncontiguous folded subdomains. There is a dominant sequence of unfolding, which reflects a nonuniform stability distribution across the repeat array and can be rationalized by theoretical models accounting for heterogeneous contact density in the folded structure. Unfolding of certain intermediates is, however, competitive, leading to parallel unfolding pathways. The low-stability, central repeats sample unfolded conformations under physiological conditions, suggesting how folding directs function: certain regions present rigid motifs for molecular recognition, whereas others have the flexibility with which to broaden the search area, as in the fly-casting mechanism. Partial unfolding of PR65/A also impacts catalysis by altering the proximity of bound catalytic subunit and substrate. Thus, the repeat array orchestrates the assembly and activity of PP2A.

Deciphering Protein Stability in Cells

Deciphering Protein Stability in Cells

Folding of proteins in presculpted free energy landscape

Recent studies of the tube model of protein have indicated that the free energy landscape of proteins is presculpted by symmetry of the protein backbone and geometrical constraints played by the hydrogen bonds. In this study, we investigate the role of amino acid sequences in the folding of proteins. We consider two models that are differed by sequence specificity: the tube HP model with hydrophobic (H) and polar (P) sequences, and the tube Go model with native-centric contact potentials. Monte Carlo simulations are carried out for two sequences of length of 48 amino acids, whose ground states are a three-helix bundle and a GB1-like structure. The results show that folding inthe Go model is more cooperative than in the HP model. In the HP model the collapse transition and the folding transition are separated, whereas in the Go model the two transitions coincide.