Towards complete descriptions of the free-energy landscapes of proteins

Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure-function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Lastly, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

Sequence grammar underlying the unfolding and phase separation of globular proteins

Aberrant phase separation of globular proteins is associated with many diseases. Here, we use a model protein system to understand how the unfolded states of globular proteins drive phase separation and the formation of unfolded protein deposits (UPODs). We find that for UPODs to form, the concentrations of unfolded molecules must be above a threshold value. Additionally, unfolded molecules must possess appropriate sequence grammars to drive phase separation. While UPODs recruit molecular chaperones, their compositional profiles are also influenced by synergistic physicochemical interactions governed by the sequence grammars of unfolded proteins and cellular proteins. Overall, the driving forces for phase separation and the compositional profiles of UPODs are governed by the sequence grammars of unfolded proteins. Our studies highlight the need for uncovering the sequence grammars of unfolded proteins that drive UPOD formation and cause gain-of-function interactions whereby proteins are aberrantly recruited into UPODs.

Quantitative Agreement between Conformational Substates of Holo Calcium-Loaded Calmodulin Detected by Double Electron-Electron Resonance EPR and Predicted by Molecular Dynamics Simulations

Calcium-loaded calmodulin (CaM/4Ca²⁺) comprises two domains that undergo rigid body reorientation from a predominantly extended conformation to a compact one upon binding target peptides. A recent replica-exchange molecular dynamics (MD) simulation on holo CaM/4Ca²⁺ suggested the existence of distinct structural clusters (substates) along the path from extended to compact conformers in the absence of substrates. Here, we experimentally demonstrate the existence of CaM/4Ca²⁺ substates trapped in local minima by three freezing/annealing regimes (slow, 40 s; intermediate, 1.5 s; fast, 0.5 ms) using pulsed Q-band double electron-electron resonance (DEER) EPR spectroscopy to measure interdomain distances between nitroxide spin-labels positioned at A17C and A128C in the N- and C-terminal domains, respectively. The DEER echo curves were directly fit to population-optimized P(r) pairwise distance distributions calculated from the coordinates of the MD clusters and compact crystal structure. DEER data on fully deuterated CaM/4Ca²⁺ were acquired at multiple values of the second echo period (10-35 μs) and analyzed globally to eliminate instrumental and overfitting artifacts and ensure accurate populations, peak positions, and widths. The DEER data for all three freezing regimes are quantitatively accounted for within experimental error by 5-6 distinct conformers comprising a predominantly populated extended form (60-75%) and progressively more compact states whose populations decrease as the degree of compactness increases. The shortest interdomain separation is found in the compact crystal structure, which has an occupancy of 4-6%. Thus, CaM/4Ca²⁺ samples high energy local minima comprising a few discrete substates of increasing compactness in a rugged energy landscape.

On the capacity and superposition of minima in neural network loss function landscapes

Minima of the loss function landscape (LFL) of a neural network are locally optimal sets of weights that extract and process information from the input data to make outcome predictions. In underparameterised networks, the capacity of the weights may be insufficient to fit all the relevant information. We demonstrate that different local minima specialise in certain aspects of the learning problem, and process the input information differently. This effect can be exploited using a meta-network in which the predictive power from multiple minima of the LFL is combined to produce a better classifier. With this approach, we can increase the area under the receiver operating characteristic curve by around 20 % for a complex learning problem. We propose a theoretical basis for combining minima and show how a meta-network can be trained to select the representative that is used for classification of a specific data item. Finally, we present an analysis of symmetry-equivalent solutions to machine learning problems, which provides a systematic means to improve the efficiency of this approach.

Small Neutral Crowding Solute Effects on Protein Folding Thermodynamic Stability and Kinetics

Molecular crowding is a ubiquitous phenomenon in biological systems, with significant consequences on protein folding and stability. Small compounds, such as the osmolyte trimethylamine N-oxide (TMAO), can also present similar effects. To analyze the effects arising from these solute-like molecules, we performed a series of crowded coarse-grained folding simulations. Two well-known proteins were chosen, CI2 and SH3, modeled by the alpha-carbon-structure-based model. In the simulations, the crowding molecules were represented by low-sized neutral atom beads in different concentrations. The results show that a low level of the volume fraction occupied by neutral agents can change protein stability and folding kinetics for the two systems. However, the kinetics were shown to be unaffected in their respective folding temperatures. The faster kinetics correlates with changes in the folding route for systems at the same temperature, where non-native contacts were shown to be relevant. The transition states of the two systems with and without crowders are similar. In the case of SH3, there are differences in the structuring of two strands, which may be associated with the increase in its folding rate, in addition to the destabilization of the denatured ensemble. The present study also detected a crossover in the thermodynamic stability behavior, previously observed experimentally and theoretically. As the temperature increases, crowders change from destabilizing to stabilizing agents.

Explicit Characterization of the Free-Energy Landscape of a Protein in the Space of All Its Cα Carbons

By using an approach that allows computing the free energy in high-dimensional spaces together with a clustering technique capable of identifying kinetic attractors stabilized by conformational disorder, we analyze a molecular dynamics trajectory of the Villin headpiece from Lindorff-Larsen, K.; et al. How fast-folding proteins fold. Science 2011, 334, 517-520. We compute its free-energy landscape in the space of all its C_α carbons. This landscape has the shape of a 12-dimensional funnel with the free energy decreasing monotonically as a function of the native contacts. There are no significant folding barriers. The funnel can be partitioned in five regions, three mainly folded and two unfolded, which behave as Markov states. The slowest relaxation time among these states corresponds to the folding transition. The second slowest time is only twice smaller and corresponds to a transition within the unfolded state. This indicates that the unfolded part of the funnel has a nontrivial shape, which induces a sizable kinetic barrier between disordered states.

Simultaneous NMR characterisation of multiple minima in the free energy landscape of an RNA UUCG tetraloop

RNA molecules in solution tend to undergo structural fluctuations of relatively large amplitude and to populate a range of different conformations some of which with low populations. It is still very challenging, however, to characterise the structures of these low populated states and to understand their functional roles. In the present study, we address this problem by using NMR residual dipolar couplings (RDCs) as structural restraints in replica-averaged metadynamics (RAM) simulations. By applying this approach to a 14-mer RNA hairpin containing the prototypical UUCG tetraloop motif, we show that it is possible to construct the free energy landscape of this RNA molecule. This free energy landscapes reveals the surprisingly rich dynamics of the UUCG tetraloop and identifies the multiple substates that exist in equilibrium owing to thermal fluctuations. The approach that we present is general and can be applied to the study of the free energy landscapes of other RNA or RNA-protein systems.

Energy landscapes of a hairpin peptide including NMR chemical shift restraints

Methods recently introduced to improve the efficiency of protein structure prediction simulations by adding a restraint potential to a molecular mechanics force field introduce additional input parameters that can affect the performance. Here we investigate the changes in the energy landscape as the relative weight of the two contributions, force field and restraint potential, is systematically altered, for restraint functions constructed from calculated nuclear magnetic resonance chemical shifts. Benchmarking calculations were performed on a 12-residue peptide, tryptophan zipper 1, which features both secondary structure (a β-hairpin) and specific packing of tryptophan sidechains. Basin-hopping global optimization was performed to assess the efficiency with which lowest-energy structures are located, and the discrete path sampling approach was employed to survey the energy landscapes between unfolded and folded structures. We find that inclusion of the chemical shift restraints improves the efficiency of structure prediction because the energy landscape becomes more funnelled and the proportion of local minima classified as native increases. However, the funnelling nature of the landscape is reduced as the relative contribution of the chemical shift restraint potential is increased past an optimal value.

Structural dynamics and conformational equilibria of SERCA regulatory proteins in membranes by solid-state NMR restrained simulations

Solid-state NMR spectroscopy is emerging as a powerful approach to determine structure, topology, and conformational dynamics of membrane proteins at the atomic level. Conformational dynamics are often inferred and quantified from the motional averaging of the NMR parameters. However, the nature of these motions is difficult to envision based only on spectroscopic data. Here, we utilized restrained molecular dynamics simulations to probe the structural dynamics, topology and conformational transitions of regulatory membrane proteins of the calcium ATPase SERCA, namely sarcolipin and phospholamban, in explicit lipid bilayers. Specifically, we employed oriented solid-state NMR data, such as dipolar couplings and chemical shift anisotropy measured in lipid bicelles, to refine the conformational ensemble of these proteins in lipid membranes. The samplings accurately reproduced the orientations of transmembrane helices and showed a significant degree of convergence with all of the NMR parameters. Unlike the unrestrained simulations, the resulting sarcolipin structures are in agreement with distances and angles for hydrogen bonds in ideal helices. In the case of phospholamban, the restrained ensemble sampled the conformational interconversion between T (helical) and R (unfolded) states for the cytoplasmic region that could not be observed using standard structural refinements with the same experimental data set. This study underscores the importance of implementing NMR data in molecular dynamics protocols to better describe the conformational landscapes of membrane proteins embedded in realistic lipid membranes.

A relationship between the transient structure in the monomeric state and the aggregation propensities of α-synuclein and β-synuclein

α-Synuclein is an intrinsically disordered protein whose aggregation is implicated in Parkinson's disease. A second member of the synuclein family, β-synuclein, shares significant sequence similarity with α-synuclein but is much more resistant to aggregation. β-Synuclein is missing an 11-residue stretch in the central non-β-amyloid component region that forms the core of α-synuclein amyloid fibrils, yet insertion of these residues into β-synuclein to produce the βSHC construct does not markedly increase the aggregation propensity. To investigate the structural basis of these different behaviors, quantitative nuclear magnetic resonance data, in the form of paramagnetic relaxation enhancement-derived interatomic distances, are combined with molecular dynamics simulations to generate ensembles of structures representative of the solution states of α-synuclein, β-synuclein, and βSHC. Comparison of these ensembles reveals that the differing aggregation propensities of α-synuclein and β-synuclein are associated with differences in the degree of residual structure in the C-terminus coupled to the shorter separation between the N- and C-termini in β-synuclein and βSHC, making protective intramolecular contacts more likely.

Decreased amyloidogenicity caused by mutational modulation of surface properties of the immunoglobulin light chain BRE variable domain

Amyloid formation by immunoglobulin light chain (LC) proteins is associated with amyloid light chain (AL) amyloidosis. Destabilization of the native state of the variable domain of the LC (VL) is known to be one of the critical factors in promoting the formation of amyloid fibrils. However, determining the key residues involved in this destabilization remains challenging, because of the existence of a number of intrinsic sequence variations within VL. In this study, we identified the key residues for destabilization of the native state of amyloidogenic VL in the LC of BRE by analyzing the stability of chimeric mutants of BRE and REI VL; the latter immunoglobulin is not associated with AL amyloidosis. The results suggest that the surface-exposed residues N45 and D50 are the key residues in the destabilization of the native state of BRE VL. Point mutations at the corresponding residues in REI VL (K45N, E50D, and K45N/E50D) destabilized the native state and increased amyloidogenicity. However, the reverse mutations in BRE VL (N45K, D50E, and N45K/D50E) re-established the native state and decreased amyloidogenicity. Thus, analyses using chimeras and point mutants successfully elucidated the key residues involved in BRE VL destabilization and increased amyloidogenic propensity. These results also suggest that the modulation of surface properties of wild-type VL may improve their stability and prevent the formation of amyloid fibrils.

Measurement of histidine pKa values and tautomer populations in invisible protein states

The histidine imidazole side chain plays a critical role in protein function and stability. Its importance for catalysis is underscored by the fact that histidines are localized to active sites in ∼ 50% of all enzymes. NMR spectroscopy has become an important tool for studies of histidine side chains through the measurement of site-specific pK(a)s and tautomer populations. To date, such studies have been confined to observable protein ground states; however, a complete understanding of the role of histidine electrostatics in protein function and stability requires that similar investigations be extended to rare, transiently formed conformers that populate the energy landscape, yet are often "invisible" in standard NMR spectra. Here we present NMR experiments and a simple strategy for studies of such conformationally excited states based on measurement of histidine (13)Cγ, (13)Cδ2 chemical shifts and (1)Hε-(13)Cε one-bond scalar couplings. The methodology is first validated and then used to obtain pKa values and tautomer distributions for histidine residues of an invisible on-pathway folding intermediate of the colicin E7 immunity protein. Our results imply that the side chains of H40 and H47 are exposed in the intermediate state and undergo significant conformational rearrangements during folding to the native structure. Further, the pKa values explain the pH-dependent stability differences between native and intermediate states over the pH range 5.5-6.5 and they suggest that imidazole deprotonation is not a barrier to the folding of this protein.

Structural characterization of intrinsically disordered proteins by NMR spectroscopy

Recent advances in NMR methodology and techniques allow the structural investigation of biomolecules of increasing size with atomic resolution. NMR spectroscopy is especially well-suited for the study of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) which are in general highly flexible and do not have a well-defined secondary or tertiary structure under functional conditions. In the last decade, the important role of IDPs in many essential cellular processes has become more evident as the lack of a stable tertiary structure of many protagonists in signal transduction, transcription regulation and cell-cycle regulation has been discovered. The growing demand for structural data of IDPs required the development and adaption of methods such as ¹³C-direct detected experiments, paramagnetic relaxation enhancements (PREs) or residual dipolar couplings (RDCs) for the study of ‘unstructured’ molecules in vitro and in-cell. The information obtained by NMR can be processed with novel computational tools to generate conformational ensembles that visualize the conformations IDPs sample under functional conditions. Here, we address NMR experiments and strategies that enable the generation of detailed structural models of IDPs.

Visualizing transient protein-folding intermediates by tryptophan-scanning mutagenesis

To understand how proteins fold, assemble and function, it is necessary to characterize the structure and dynamics of each state they adopt during their lifetime. Experimental characterization of the transient states of proteins remains a major challenge because high-resolution structural techniques, including NMR and X-ray crystallography, cannot be directly applied to study short-lived protein states. To circumvent this limitation, we show that transient states during protein folding can be characterized by measuring the fluorescence of tryptophan residues, introduced at many solvent-exposed positions to determine whether each position is native-like, denatured-like or non-native-like in the intermediate state. We use this approach to characterize a late-folding-intermediate state of the small globular mammalian protein ubiquitin, and we show the presence of productive non-native interactions that suggest a 'flycatcher' mechanism of concerted binding and folding.

Bioinformatics and variability in drug response: a protein structural perspective

Marketed drugs frequently perform worse in clinical practice than in the clinical trials on which their approval is based. Many therapeutic compounds are ineffective for a large subpopulation of patients to whom they are prescribed; worse, a significant fraction of patients experience adverse effects more severe than anticipated. The unacceptable risk-benefit profile for many drugs mandates a paradigm shift towards personalized medicine. However, prior to adoption of patient-specific approaches, it is useful to understand the molecular details underlying variable drug response among diverse patient populations. Over the past decade, progress in structural genomics led to an explosion of available three-dimensional structures of drug target proteins while efforts in pharmacogenetics offered insights into polymorphisms correlated with differential therapeutic outcomes. Together these advances provide the opportunity to examine how altered protein structures arising from genetic differences affect protein-drug interactions and, ultimately, drug response. In this review, we first summarize structural characteristics of protein targets and common mechanisms of drug interactions. Next, we describe the impact of coding mutations on protein structures and drug response. Finally, we highlight tools for analysing protein structures and protein-drug interactions and discuss their application for understanding altered drug responses associated with protein structural variants.

Structural disorder and protein elasticity

An emerging class of disordered proteins underlies the elasticity of many biological tissues. Elastomeric proteins are essential to the function of biological machinery as diverse as the human arterial wall, the capture spiral of spider webs and the jumping mechanism of fleas. In this chapter, we review what is known about the molecular basis and the functional role of structural disorder in protein elasticity. In general, the elastic recoil of proteins is due to a combination of internal energy and entropy. In rubber-like elastomeric proteins, the dominant driving force is the increased entropy of the relaxed state relative to the stretched state. Aggregates of these proteins are intrinsically disordered or fuzzy, with high polypeptide chain entropy. We focus our discussion on the sequence, structure and function of five rubber-like elastomeric proteins, elastin, resilin, spider silk, abductin and ColP. Although we group these disordered elastomers together into one class of proteins, they exhibit a broad range of sequence motifs, mechanical properties and biological functions. Understanding how sequence modulates both disorder and elasticity will help advance the rational design of elastic biomaterials such as artificial skin and vascular grafts.

Malleability of the folding mechanism of the outer membrane protein PagP: parallel pathways and the effect of membrane elasticity

Understanding the interactions between membrane proteins and the lipid bilayer is key to increasing our ability to predict and tailor the folding mechanism, structure and stability of membrane proteins. Here, we have investigated the effects of changing the membrane composition and the relative concentrations of protein and lipid on the folding mechanism of the bacterial outer membrane protein PagP. The folding pathway, monitored by tryptophan fluorescence, was found to be characterized by a burst phase, representing PagP adsorption to the liposome surface, followed by a time course that reflects the folding and insertion of the protein into the membrane. In 1,2-dilauroyl-sn-glycero-3-phosphocholine (diC(12:0)PC) liposomes, the post-adsorption time course fits well to a single exponential at high lipid-to-protein ratios (LPRs), but at low LPRs, a second exponential phase with a slower folding rate constant is observed. Interrupted refolding assays demonstrated that the two exponential phases reflect the presence of parallel folding pathways. Partitioning between these pathways was found to be modulated by the elastic properties of the membrane. Folding into mixed 1,2-dilauroyl-sn-glycero-3-phosphoethanolamine:diC(12:0)PC liposomes resulted in a decrease in PagP adsorption to the liposomes and a switch to the slower folding pathway. By contrast, inclusion of 1,2-dilauroyl-sn-glycero-3-phosphoserine into diC(12:0)PC liposomes resulted in a decrease in the folding rate of the fast pathway. The results highlight the effect of lipid composition in tailoring the folding mechanism of a membrane protein, revealing that membrane proteins have access to multiple, competing folding routes to a unique native structure.

Protein solubility and protein homeostasis: a generic view of protein misfolding disorders

According to the "generic view" of protein aggregation, the ability to self-assemble into stable and highly organized structures such as amyloid fibrils is not an unusual feature exhibited by a small group of peptides and proteins with special sequence or structural properties, but rather a property shared by most proteins. At the same time, through a wide variety of techniques, many of which were originally devised for applications in other disciplines, it has also been established that the maintenance of proteins in a soluble state is a fundamental aspect of protein homeostasis. Taken together, these advances offer a unified framework for understanding the molecular basis of protein aggregation and for the rational development of therapeutic strategies based on the biological and chemical regulation of protein solubility.

How ionic liquids can help to stabilize native proteins

The native state of a globular protein is essential for its biocatalytic function, but is marginally stable against unfolding. While unfolding equilibria are often reversible, folding intermediates and misfolds can promote irreversible protein aggregation into amorphous precipitates or highly ordered amyloid states. Addition of ionic liquids-low-melting organic salts-offers intriguing prospects for stabilizing native proteins and their enzymatic function against these deactivating reaction channels. The huge number of cations and anions that form ionic liquids allows fine-tuning of their solvent properties, which offers robust and efficient strategies for solvent optimization. Going beyond case-by-case studies, this article aims at discussing principles for a rational design of ionic liquid-based formulations in protein chemistry and biocatalysis.

Quantitative approaches to defining normal and aberrant protein homeostasis

Protein homeostasis refers to the ability of cells to generate and regulate the levels of their constituent proteins in terms of conformations, interactions, concentrations and cellular localisation. We discuss here an approach in which physico-chemical properties of proteins and their environments are used to understand the underlying principles governing this process, which is crucial in all living systems. By adopting the strategy of characterising the origins of specific diseases to inform us about normal biology, we are bringing together methods and concepts from chemistry, physics, engineering, genetics and medicine. In particular, we are using a combination of in vitro, in silico and in vivo approaches to study protein homeostasis through the analysis of the effects that result from its perturbation in a select group of specific proteins, from either amino acid mutations, or changes in concentration and solubility, or interactions with other molecules. By developing a coherent and quantitative description of such phenomena, we are finding that it is possible to shed new light on how the physical and chemical properties of the cellular components can provide an understanding of the normal and aberrant behaviour of living systems. Through such an approach it is possible to provide new insights into the origin and consequences of the failure to maintain homeostasis that is associated with neurodegenerative diseases, in particular, and the phenomenon of ageing, in general, and hence provide a framework for the rational design of therapeutic approaches.

A thermodynamic analysis of fibrillar polymorphism

We explore the thermodynamic properties of three different fibrils of the peptide hormone glucagon, formed under different salt conditions (glycine, sulfate and NaCl, respectively), and differing considerably in compactness. The three fibrils display a large variation in the specific heat capacity DeltaC(p) determined by isothermal titration calorimetry. Sulfate fibrils show a negative DeltaC(p) expected from a folding reaction, while the DeltaC(p) for glycine fibrils is essentially zero. NaCl fibrils, which are less stable than the other fibrils, have a large and positive C(p). The predicted change in solvent accessible area is not a useful predictor of fibrillar DeltaC(p) unlike the case for globular proteins. We speculate that strong backbone interactions may lead to the unfavorable burial of polar side residues, water and/or charged groups which all can have major influence on the change in C(p). These results highlight differences in the driving forces of native folding and fibril formation.

Determination of the free energy landscape of alpha-synuclein using spin label nuclear magnetic resonance measurements

Natively unfolded proteins present a challenge for structure determination because they populate highly heterogeneous ensembles of conformations. A useful source of structural information about these states is provided by paramagnetic relaxation enhancement measurements by nuclear magnetic resonance spectroscopy, from which long-range interatomic distances can be estimated. Here we describe a method for using such distances as restraints in molecular dynamics simulations to obtain a mapping of the free energy landscapes of natively unfolded proteins. We demonstrate the method in the case of alpha-synuclein and validate the results by a comparison with electron transfer measurements. Our findings indicate that our procedure provides an accurate estimate of the relative statistical weights of the different conformations populated by alpha-synuclein in its natively unfolded state.

Transient non-native hydrogen bonds promote activation of a signaling protein

Phosphorylation is a common mechanism for activating proteins within signaling pathways. Yet, the molecular transitions between the inactive and active conformational states are poorly understood. Here we quantitatively characterize the free-energy landscape of activation of a signaling protein, nitrogen regulatory protein C (NtrC), by connecting functional protein dynamics of phosphorylation-dependent activation to protein folding and show that only a rarely populated, pre-existing active conformation is energetically stabilized by phosphorylation. Using nuclear magnetic resonance (NMR) dynamics, we test an atomic scale pathway for the complex conformational transition, inferred from molecular dynamics simulations (Lei et al., 2009). The data show that the loss of native stabilizing contacts during activation is compensated by non-native transient atomic interactions during the transition. The results unravel atomistic details of native-state protein energy landscapes by expanding the knowledge about ground states to transition landscapes.

Equilibrium and kinetic approaches for studying oligomeric protein folding

This chapter describes the approaches and considerations necessary for extension of current protein folding methods to the equilibrium and kinetic reactions of oligomeric proteins, using dimers as the primary example. Spectroscopic and transport methods to monitor folding and unfolding transitions are summarized. The data collection and analyses to determine protein stability and kinetic folding mechanisms are discussed in the context of the additional dimension of complexity that arises in higher order folding processes, compared to first order monomeric proteins. As a case study to illustrate the data analysis process, equilibrium, and kinetic data are presented for SmtB, a homodimeric DNA-binding protein from Synechococcus PCC7942.

The Croonian lecture 2006. Structure of the living cell

The smallest viable unit of life is a single cell. To understand life, we need to visualize the structure of the cell as well as all cellular components and their complexes. This is a formidable task that requires sophisticated tools. These have developed from the rudimentary early microscopes of 350 years ago to a toolbox that includes electron microscopes, synchrotrons, high magnetic fields and vast computing power. This lecture briefly reviews the development of biophysical tools and illustrates how they begin to unravel the 'molecular logic of the living state'.

Structure and dynamics of a ribosome-bound nascent chain by NMR spectroscopy

Protein folding in living cells is inherently coupled to protein synthesis and chain elongation. There is considerable evidence that some nascent chains fold into their native structures in a cotranslational manner before release from the ribosome, but, despite its importance, a detailed description of such a process at the atomic level remains elusive. We show here at a residue-specific level that a nascent protein chain can reach its native tertiary structure on the ribosome. By generating translation-arrested ribosomes in which the newly synthesized polypeptide chain is selectively (13)C/(15)N-labeled, we observe, using ultrafast NMR techniques, a large number of resonances of a ribosome-bound nascent chain complex corresponding to a pair of C-terminally truncated immunoglobulin (Ig) domains. Analysis of these spectra reveals that the nascent chain adopts a structure in which a native-like N-terminal Ig domain is tethered to the ribosome by a largely unfolded and highly flexible C-terminal domain. Selective broadening of resonances for a group of residues that are colocalized in the structure demonstrates that there are specific but transient interactions between the ribosome and the N-terminal region of the folded Ig domain. These findings represent a step toward a detailed structural understanding of the cellular processes of cotranslational folding.

Theoretical framework for NMR residual dipolar couplings in unfolded proteins

A theoretical framework for the prediction of nuclear magnetic resonance (NMR) residual dipolar couplings (RDCs) in unfolded proteins under weakly aligning conditions is presented. The unfolded polypeptide chain is modeled as a random flight chain while the alignment medium is represented by a set of regularly arranged obstacles. For the case of bicelles oriented perpendicular to the magnetic field, a closed-form analytical result is derived. With the obtained analytical expression the RDCs are readily accessible for any locus along the chain, for chains of differing length, and for varying bicelle concentrations. The two general features predicted by the model are (i) RDCs in the center segments of a polypeptide chain are larger than RDCs in the end segments, resulting in a bell-shaped sequential distribution of RDCs, and (ii) couplings are larger for shorter chains than for longer chains at a given bicelle concentration. Experimental data available from the literature confirm the first prediction of the model, providing a tool for recognizing fully unfolded polypeptide chains. With less certainty experimental data appear to support the second prediction as well. However, more systematic experimental studies are needed in order to validate or disprove the predictions of the model. The presented framework is an important step towards a solid theoretical foundation for the analysis of experimentally measured RDCs in unfolded proteins in the case of alignment media such as polyacrylamide gels and neutral bicelle systems which align biomacromolecules by a steric mechanism. Various improvements and generalizations are possible within the suggested approach.

Folding versus aggregation: polypeptide conformations on competing pathways

Protein aggregation has now become recognised as an important and generic aspect of protein energy landscapes. Since the discovery that numerous human diseases are caused by protein aggregation, the biophysical characterisation of misfolded states and their aggregation mechanisms has received increased attention. Utilising experimental techniques and computational approaches established for the analysis of protein folding reactions has ensured rapid advances in the study of pathways leading to amyloid fibrils and amyloid-related aggregates. Here we describe recent experimental and theoretical advances in the elucidation of the conformational properties of dynamic, heterogeneous and/or insoluble protein ensembles populated on complex, multidimensional protein energy landscapes. We discuss current understanding of aggregation mechanisms in this context and describe how the synergy between biochemical, biophysical and cell-biological experiments are beginning to provide detailed insights into the partitioning of non-native species between protein folding and aggregation pathways.

Protein structure determination from NMR chemical shifts

NMR spectroscopy plays a major role in the determination of the structures and dynamics of proteins and other biological macromolecules. Chemical shifts are the most readily and accurately measurable NMR parameters, and they reflect with great specificity the conformations of native and nonnative states of proteins. We show, using 11 examples of proteins representative of the major structural classes and containing up to 123 residues, that it is possible to use chemical shifts as structural restraints in combination with a conventional molecular mechanics force field to determine the conformations of proteins at a resolution of 2 angstroms or better. This strategy should be widely applicable and, subject to further development, will enable quantitative structural analysis to be carried out to address a range of complex biological problems not accessible to current structural techniques.

Intermediates: ubiquitous species on folding energy landscapes?

Although intermediates have long been recognised as fascinating species that form during the folding of large proteins, the role that intermediates play in the folding of small, single-domain proteins has been widely debated. Recent discoveries using new, sensitive methods of detection and studies combining simulation and experiment have now converged on a common vision for folding, involving intermediates as ubiquitous stepping stones en route to the native state. The results suggest that the folding energy landscapes of even the smallest proteins possess significant ruggedness in which intermediates stabilized by both native and non-native interactions are common features.

Determination of conformationally heterogeneous states of proteins

Although conformationally heterogeneous states of proteins are involved in a range of important biological processes, including protein folding and misfolding, and signal transduction, detailed knowledge of their structure and dynamics is still largely missing. Proteins in many of these states are constantly changing shape, such that they are better described as ensembles of conformations rather than in terms of well-defined structures, as is normally the case for native states. Methods in which molecular simulations are combined with experimental measurements are emerging as a powerful route to the accurate determination of the conformational properties of these states of proteins.

The MUMO (minimal under-restraining minimal over-restraining) method for the determination of native state ensembles of proteins

While reliable procedures for determining the conformations of proteins are available, methods for generating ensembles of structures that also reflect their flexibility are much less well established. Here we present a systematic assessment of the ability of ensemble-averaged molecular dynamics simulations with ensemble-averaged NMR restraints to simultaneously reproduce the average structure of proteins and their associated dynamics. We discuss the effects that under-restraining (overfitting) and over-restraining (underfitting) have on the structures generated in ensemble-averaged molecular simulations. We then introduce the MUMO (minimal under-restraining minimal over-restraining) method, a procedure in which different observables are averaged over a different number of molecules. As both over-restraining and under-restraining are significantly reduced in the MUMO method, it is possible to generate ensembles of conformations that accurately characterize both the structure and the dynamics of native states of proteins. The application of the MUMO method to the protein ubiquitin yields a high-resolution structural ensemble with an RDC Q-factor of 0.19.

Atomic-level characterization of disordered protein ensembles

The roles of unfolded states of proteins in normal folding and in diseases involving aggregation, as well as the prevalence and regulatory functions of intrinsically disordered proteins, have become increasingly recognized. The structural representation of these disordered states as ensembles of interconverting conformers can therefore provide critical insights. Experimental methods can be used to probe ensemble-averaged structural properties of disordered states and computational approaches generate representative ensembles of conformers using experimental restraints. In particular, NMR and small-angle X-ray scattering provide quantitative data that can readily be incorporated into calculations. These techniques have gleaned structural information about denatured, unfolded and intrinsically disordered proteins. The use of experimental data in different computational approaches, including ensemble molecular dynamics simulations and algorithms that assign populations to pregenerated conformers, has highlighted the presence of both local and long-range structure, and the occurrence of native-like and non-native interactions in unfolded and denatured states. Analysis of the resulting ensembles has suggested important implications of this fluctuating structure for folding, aggregation and binding.

Geometry, energetics, and dynamics of hydrogen bonds in proteins: structural information derived from NMR scalar couplings

An accurate description of hydrogen bonds is essential to identify the determinants of protein stability and function as well as folding and misfolding behavior. We describe a method of using J couplings through hydrogen bonds as ensemble-averaged restraints in molecular dynamics simulations. Applications to the cases of ubiquitin and protein G show that these scalar couplings provide powerful structural information that, when used through the methodology that we present here, enables the description of the geometry and energetics of hydrogen bonds with an accuracy approaching that of high-resolution X-ray structures.

BPPred: a Web-based computational tool for predicting biophysical parameters of proteins

We exploit the availability of recent experimental data on a variety of proteins to develop a Web-based prediction algorithm (BPPred) to calculate several biophysical parameters commonly used to describe the folding process. These parameters include the equilibrium m-values, the length of proteins, and the changes upon unfolding in the solvent-accessible surface area, in the heat capacity, and in the radius of gyration. We also show that the knowledge of any one of these quantities allows an estimate of the others to be obtained, and describe the confidence limits with which these estimations can be made. Furthermore, we discuss how the kinetic m-values, or the Beta Tanford values, may provide an estimate of the solvent-accessible surface area and the radius of gyration of the transition state for protein folding. Taken together, these results suggest that BPPred should represent a valuable tool for interpreting experimental measurements, as well as the results of molecular dynamics simulations.

A PDZ domain recapitulates a unifying mechanism for protein folding

A unifying view has been recently proposed according to which the classical diffusion-collision and nucleation-condensation models may represent two extreme manifestations of an underlying common mechanism for the folding of small globular proteins. We report here the characterization of the folding process of the PDZ domain, a protein that recapitulates the three canonical steps involved in this unifying mechanism, namely: (i) the early formation of a weak nucleus that determines the native-like topology of a large portion of the structure, (ii) a global collapse of the entire polypeptide chain, and (iii) the consolidation of the remaining partially structured regions to achieve the native state conformation. These steps, which are clearly detectable in the PDZ domain investigated here, may be difficult to distinguish experimentally in other proteins, which would thus appear to follow one of the two limiting mechanisms. The analysis of the (un)folding kinetics for other three-state proteins (when available) appears consistent with the predictions ensuing from this unifying mechanism, thus providing a powerful validation of its general nature.

Proline and Glycine Control Protein Self-Organization into Elastomeric or Amyloid Fibrils

Elastin provides extensible tissues, including arteries and skin, with the propensity for elastic recoil, whereas amyloid fibrils are associated with tissue-degenerative diseases, such as Alzheimer's. Although both elastin-like and amyloid-like materials result from the self-organization of proteins into fibrils, the molecular basis of their differing physical properties is poorly understood. Using molecular simulations of monomeric and aggregated states, we demonstrate that elastin-like and amyloid-like peptides are separable on the basis of backbone hydration and peptide-peptide hydrogen bonding. The analysis of diverse sequences, including those of elastin, amyloids, spider silks, wheat gluten, and insect resilin, reveals a threshold in proline and glycine composition above which amyloid formation is impeded and elastomeric properties become apparent. The predictive capacity of this threshold is confirmed by the self-assembly of recombinant peptides into either amyloid or elastin-like fibrils. Our findings support a unified model of protein aggregation in which hydration and conformational disorder are fundamental requirements for elastomeric function.

GroEL-mediated protein folding: making the impossible, possible

Protein folding is a spontaneous process that is essential for life, yet the concentrated and complex interior of a cell is an inherently hostile environment for the efficient folding of many proteins. Some proteins-constrained by sequence, topology, size, and function-simply cannot fold by themselves and are instead prone to misfolding and aggregation. This problem is so deeply entrenched that a specialized family of proteins, known as molecular chaperones, evolved to assist in protein folding. Here we examine one essential class of molecular chaperones, the large, oligomeric, and energy utilizing chaperonins or Hsp60s. The bacterial chaperonin GroEL, along with its co-chaperonin GroES, is probably the best-studied example of this family of protein-folding machine. In this review, we examine some of the general properties of proteins that do not fold well in the absence of GroEL and then consider how folding of these proteins is enhanced by GroEL and GroES. Recent experimental and theoretical studies suggest that chaperonins like GroEL and GroES employ a combination of protein isolation, unfolding, and conformational restriction to drive protein folding under conditions where it is otherwise not possible.

Residue-level NMR View of the Urea-driven Equilibrium Folding Transition of SUMO-1 (1-97): Native Preferences Do Not Increase Monotonously

SUMO-1 (1-97) is a crucial protein in the machinery of post-translational modifications. We observed by circular dichroism and fluorescence spectroscopy that urea-induced unfolding of this protein is a complex process with the possibility of occurrence of detectable intermediates along the way. The tertiary structure is completely lost around approximately 4.5 M urea with a transition mid-point at 2.53 M urea, while the secondary structure unfolding seems to show two transitions, with mid-points at 2.42 M and 5.69 M urea. We have elucidated by systematic urea titration, the equilibrium residue level structural and dynamics changes along the entire folding/unfolding transition by multidimensional NMR. With urea dilution, the protein is seen to progressively lose most of the broad beta-domain structural preferences present at 8 M urea, acquire some helical propensities at 5 M urea, and lose some of them again on further dilution of urea. Between 3 M and 2 M urea, the protein starts afresh to acquire native structural features. These observations are contrary to the conventional notion that proteins fold with monotonously increasing native-type preferences. For folding below approximately 3 M urea, the region around the alpha1 helix appears to be a potential folding initiation site. The folding seems to start with a collapse into native-like topologies, at least in parts, and is followed by formation of secondary and tertiary structure, perhaps by cooperative rearrangements. The motional characteristics of the protein show sequence-dependent variation as the concentration of urea is progressively reduced. At the sub-nanosecond level, the features are extremely unusual for denatured states, and only certain segments corresponding to the flexible regions in the native protein display these motions at the different concentrations of urea.

Characterization of the residual structure in the unfolded state of the Δ131Δ fragment of staphylococcal nuclease

The determination of the conformational preferences in unfolded states of proteins constitutes an important challenge in structural biology. We use inter-residue distances estimated from site-directed spin-labeling NMR experimental measurements as ensemble-averaged restraints in all-atom molecular dynamics simulations to characterise the residual structure of the Delta131Delta fragment of staphylococcal nuclease under physiological conditions. Our findings indicate that Delta131Delta under these conditions shows a tendency to form transiently hydrophobic clusters similar to those present in the native state of wild-type staphylococcal nuclease. Only rarely, however, all these interactions are simultaneously realized to generate conformations with an overall native topology.

Amyloid formation under physiological conditions proceeds via a native-like folding intermediate

Although most proteins can assemble into amyloid-like fibrils in vitro under extreme conditions, how proteins form amyloid fibrils in vivo remains unresolved. Identifying rare aggregation-prone species under physiologically relevant conditions and defining their structural properties is therefore an important challenge. By solving the folding mechanism of the naturally amyloidogenic protein beta-2-microglobulin at pH 7.0 and 37 degrees C and correlating the concentrations of different species with the rate of fibril elongation, we identify a specific folding intermediate, containing a non-native trans-proline isomer, as the direct precursor of fibril elongation. Structural analysis using NMR shows that this species is highly native-like but contains perturbation of the edge strands that normally protect beta-sandwich proteins from self-association. The results demonstrate that aggregation pathways can involve self-assembly of highly native-like folding intermediates, and have implications for the prevention of this, and other, amyloid disorders.

Protein unfolding, amyloid fibril formation and configurational energy landscapes under high pressure conditions

High hydrostatic pressure induces conformational changes in proteins ranging from compression of the molecules to loss of native structure. In this tutorial review we describe how the interplay between the volume change and the compressibility leads to pressure-induced unfolding of proteins and dissociation of amyloid fibrils. We also discuss the effect of pressure on protein folding and free energy landscapes. From a molecular viewpoint, pressure effects can be rationalised in terms of packing and hydration of proteins.

The Yin and Yang of protein folding

The study of protein aggregation saw a renaissance in the last decade, when it was discovered that aggregation is the cause of several human diseases, making this field of research one of the most exciting frontiers in science today. Building on knowledge about protein folding energy landscapes, determined using an array of biophysical methods, theory and simulation, new light is now being shed on some of the key questions in protein-misfolding diseases. This review will focus on the mechanisms of protein folding and amyloid fibril formation, concentrating on the role of partially folded states in these processes, the complexity of the free energy landscape, and the potentials for the development of future therapeutic strategies based on a full biophysical description of the combined folding and aggregation free-energy surface.

Mass spectroscopic analysis of Sup35NM prion polymerization

Sup35NM, the prion determining domain of the protein responsible for the yeast prion phenomenon [Psi], has become a powerful model for studying key processes in amyloid-related human diseases. One of these processes is a conformational conversion of soluble precursor protein into insoluble fibrillar structures. In this study, we created a set of Sup35NM mutants and used proteolytic digestion coupled with mass spectroscopy to monitor local structure of the protein during polymerization. Experimental data were compared to a network model and showed that during the conformational conversion residue Arg-28 became highly protected from cleavage, residue Arg-98 remained partially solvent exposed, and residues between 28 and 98 showed an intermediate degree of protection. In addition, we found that a distinct subset of proteolytic polypeptides spanning 28-98 residues segment spontaneously formed stable dimers. This finding suggests that the [29-98] region is the key interacting region of Sup35NM responsible for amyloid conversion.