Frustration in the energy landscapes of multidomain protein misfolding

Navigating the complexities of multi-domain protein folding

Proteome complexity has expanded tremendously over evolutionary time, enabling biological diversification. Much of this complexity is achieved by combining a limited set of structural units into long polypeptides. This widely used evolutionary strategy poses challenges for folding of the resulting multi-domain proteins. As a consequence, their folding differs from that of small single-domain proteins, which generally fold quickly and reversibly. Co-translational processes and chaperone interactions are important aspects of multi-domain protein folding. In this review, we discuss some of the recent experimental progress toward understanding these processes.

Mechanisms and pathology of protein misfolding and aggregation

Despite advances in machine learning-based protein structure prediction, we are still far from fully understanding how proteins fold into their native conformation. The conventional notion that polypeptides fold spontaneously to their biologically active states has gradually been replaced by our understanding that cellular protein folding often requires context-dependent guidance from molecular chaperones in order to avoid misfolding. Misfolded proteins can aggregate into larger structures, such as amyloid fibrils, which perpetuate the misfolding process, creating a self-reinforcing cascade. A surge in amyloid fibril structures has deepened our comprehension of how a single polypeptide sequence can exhibit multiple amyloid conformations, known as polymorphism. The assembly of these polymorphs is not a random process but is influenced by the specific conditions and tissues in which they originate. This observation suggests that, similar to the folding of native proteins, the kinetics of pathological amyloid assembly are modulated by interactions specific to cells and tissues. Here, we review the current understanding of how intrinsic protein conformational propensities are modulated by physiological and pathological interactions in the cell to shape protein misfolding and aggregation pathology.

Unraveling the folding and dimerization properties of the human FoxP subfamily of transcription factors

Human FoxP proteins share a highly conserved DNA-binding domain that dimerizes via three-dimensional domain swapping, although showing varying oligomerization propensities among its members. Here, we present an experimental and computational characterization of all human FoxP proteins to unravel how their amino acid substitutions impact their folding and dimerization mechanism. We solved the crystal structure of the forkhead domain of FoxP4 to then perform a comparison across all members, finding that their sequence changes impact not only the structural heterogeneity of their forkhead domains but also the protein-protein association energy barrier. Lastly, we demonstrate that the accumulation of a monomeric intermediate is an oligomerization-dependent feature rather than a common aspect of monomers and dimers in this protein subfamily.

Potential Self-Peptide Inhibitors of the SARS-CoV-2 Main Protease

The SARS-CoV-2 main protease (Mpro) plays an essential role in viral replication, cleaving viral polyproteins into functional proteins. This makes Mpro an important drug target. Mpro consists of an N-terminal catalytic domain and a C-terminal α-helical domain (MproC). Previous studies have shown that peptides derived from a given protein sequence (self-peptides) can affect the folding and, in turn, the function of that protein. Since the SARS-CoV-1 MproC is known to stabilize its Mpro and regulate its function, we hypothesized that SARS-CoV-2 MproC-derived self-peptides may modulate the folding and the function of SARS-CoV-2 Mpro. To test this, we studied the folding of MproC in the presence of various self-peptides using coarse-grained structure-based models and molecular dynamics simulations. In these simulations of MproC and one self-peptide, we found that two self-peptides, the α1-helix and the loop between α4 and α5 (loop4), could replace the equivalent native sequences in the MproC structure. Replacement of either sequence in full-length Mpro should, in principle, be able to perturb Mpro function albeit through different mechanisms. Some general principles for the rational design of self-peptide inhibitors emerge: The simulations show that prefolded self-peptides are more likely to replace native sequences than those which do not possess structure. Additionally, the α1-helix self-peptide is kinetically stable and once inserted rarely exchanges with the native α1-helix, while the loop4 self-peptide is easily replaced by the native loop4, making it less useful for modulating function. In summary, a prefolded α1-derived peptide should be able to inhibit SARS-CoV-2 Mpro function.

Engineered Amber-Emitting Nano Luciferase and Its Use for Immunobioluminescence Imaging In Vivo

The NanoLuc luciferase (NLuc) and its furimazine (FRZ) substrate have revolutionized bioluminescence (BL) assays and imaging. However, the use of the NLuc-FRZ luciferase-luciferin pair for mammalian tissue imaging is hindered by the low tissue penetration of the emitting blue photons. Here, we present the development of an NLuc mutant, QLuc, which catalyzes the oxidation of a synthetic QTZ luciferin for bright and red-shifted emission peaking at ∼585 nm. Compared to other small single-domain NLuc mutants, this amber-light-emitting luciferase exhibited improved performance for imaging deep-tissue targets in live mice. Leveraging this novel bioluminescent reporter, we further pursued in vivo immunobioluminescence imaging (immunoBLI), which used a fusion protein of a single-chain variable antibody fragment (scFv) and QLuc for molecular imaging of tumor-associated antigens in a xenograft mouse model. As one of the most red-shifted NLuc variants, we expect QLuc to find broad applications in noninvasive mammalian imaging. Moreover, the immunoBLI method complements immunofluorescence imaging and immuno-positron emission tomography (immunoPET), serving as a convenient and nonradioactive molecular imaging tool for animal models in basic and preclinical research.

Co-Translational Folding of Multi-Domain Proteins

The majority of proteins in nature are composed of multiple domains connected in a single polypeptide. How these long sequences fold into functional structures without forming toxic misfolds or aggregates is poorly understood. Their folding is inextricably linked to protein synthesis and interactions with cellular machinery, making mechanistic studies challenging. Recent progress has revealed critical features of multi-domain protein folding in isolation and in the context of translation by the ribosome. In this review, we discuss challenges and progress in understanding multi-domain protein folding, and highlight how molecular interactions shape folding and misfolding pathways. With the development of new approaches and model systems, the stage is now set for mechanistically exploring the folding of large multi-domain proteins.

Effects of electrostatic interactions on global folding and local conformational dynamics of a multidomain Y-family DNA polymerase

The Y-family DNA polymerases specialize in translesion DNA synthesis, which is essential for replicating damaged DNA. The Y-family polymerases, which are made up of four stable domains, exhibit extensive distributions of charged residues, and are responsible for the tight formation of the protein-DNA complex. However, it is still unclear how the electrostatic interactions influence the conformational dynamics of the polymerases. Here, we focus on the case of a prototype Y-family DNA polymerase, Dpo4. Using coarse-grained models including a salt-dependent electrostatic potential, we investigate the effects of the electrostatic interactions on the folding process of Dpo4. Our simulations show that strong electrostatic interactions result in a three-state folding of Dpo4, consistent with the experimental observations. This folding process exhibits low cooperativity led by low salt concentration, where the individual domains fold one by one through one single pathway. Since the refined folding order of domains in multidomain proteins can shrink the configurational space, we suggest that the electrostatic interactions facilitate the Dpo4 folding. In addition, we study the local conformational dynamics of Dpo4 in terms of fluctuation and frustration analyses. We show that the electrostatic interactions can exaggerate the local conformational properties, which are in favor of the large-scale conformational transition of Dpo4 during the functional DNA binding. Our results underline the importance of electrostatic interactions in the conformational dynamics of Dpo4 at both the global and local scale, providing useful guidance in protein engineering at the multidomain level.

Human FoxP Transcription Factors as Tractable Models of the Evolution and Functional Outcomes of Three-Dimensional Domain Swapping

The association of two or more proteins to adopt a quaternary complex is one of the most widespread mechanisms by which protein function is modulated. In this scenario, three-dimensional domain swapping (3D-DS) constitutes one plausible pathway for the evolution of protein oligomerization that exploits readily available intramolecular contacts to be established in an intermolecular fashion. However, analysis of the oligomerization kinetics and thermodynamics of most extant 3D-DS proteins shows its dependence on protein unfolding, obscuring the elucidation of the emergence of 3D-DS during evolution, its occurrence under physiological conditions, and its biological relevance. Here, we describe the human FoxP subfamily of transcription factors as a feasible model to study the evolution of 3D-DS, due to their significantly faster dissociation and dimerization kinetics and lower dissociation constants in comparison to most 3D-DS models. Through the biophysical and functional characterization of FoxP proteins, relevant structural aspects highlighting the evolutionary adaptations of these proteins to enable efficient 3D-DS have been ascertained. Most biophysical studies on FoxP suggest that the dynamics of the polypeptide chain are crucial to decrease the energy barrier of 3D-DS, enabling its fast oligomerization under physiological conditions. Moreover, comparison of biophysical parameters between human FoxP proteins in the context of their minute sequence differences suggests differential evolutionary strategies to favor homoassociation and presages the possibility of heteroassociations, with direct impacts in their gene regulation function.

Binding Dynamics of Disordered Linker Histone H1 with a Nucleosomal Particle

Linker histone H1 is an essential regulatory protein for many critical biological processes, such as eukaryotic chromatin packaging and gene expression. Mis-regulation of H1s is commonly observed in tumor cells, where the balance between different H1 subtypes has been shown to alter the cancer phenotype. Consisting of a rigid globular domain and two highly charged terminal domains, H1 can bind to multiple sites on a nucleosomal particle to alter chromatin hierarchical condensation levels. In particular, the disordered H1 amino- and carboxyl-terminal domains (NTD/CTD) are believed to enhance this binding affinity, but their detailed dynamics and functions remain unclear. In this work, we used a coarse-grained computational model, AWSEM-DNA, to simulate the H1.0b-nucleosome complex, namely chromatosome. Our results demonstrate that H1 disordered domains restrict the dynamics and conformation of both globular H1 and linker DNA arms, resulting in a more compact and rigid chromatosome particle. Furthermore, we identified regions of H1 disordered domains that are tightly tethered to DNA near the entry-exit site. Overall, our study elucidates at near-atomic resolution the way the disordered linker histone H1 modulates nucleosome's structural preferences and conformational dynamics.

A theoretical study of polymorphism in VQIVYK fibrils

The VQIVYK fragment from the Tau protein, also known as PHF6, is essential for aggregation of Tau into neurofibrillary lesions associated with neurodegenerative diseases. VQIVYK itself forms amyloid fibrils composed of paired β-sheets. Therefore, the full Tau protein and VQIVYK fibrils have been intensively investigated. A central issue in these studies is polymorphism, the ability of a protein to fold into more than one structure. Using all-atom molecular simulations, we generate five stable polymorphs of VQIVYK fibrils, establish their relative free energy with umbrella sampling methods, and identify the side chain interactions that provide stability. The two most stable polymorphs, which have nearly equal free energy, are formed by interdigitation of the mostly hydrophobic VIY "face" sides of the β-sheets. Another stable polymorph is formed by interdigitation of the QVK "back" sides. When we turn to examine structures from cryo-electron microscopy experiments on Tau filaments taken from diseased patients or generated in vitro, we find that the pattern of side chain interactions found in the two most stable face-to-face as well as the back-to-back polymorphs are recapitulated in amyloid structures of the full protein. Thus, our studies suggest that the interactions stabilizing PHF6 fibrils explain the amyloidogenicity of the VQIVYK motif within the full Tau protein and provide justification for the use of VQIVYK fibrils as a test bed for the design of molecules that identify or inhibit amyloid structures.

MIRRAGGE - Minimum Information Required for Reproducible AGGregation Experiments

Reports on phase separation and amyloid formation for multiple proteins and aggregation-prone peptides are recurrently used to explore the molecular mechanisms associated with several human diseases. The information conveyed by these reports can be used directly in translational investigation, e.g., for the design of better drug screening strategies, or be compiled in databases for benchmarking novel aggregation-predicting algorithms. Given that minute protocol variations determine different outcomes of protein aggregation assays, there is a strong urge for standardized descriptions of the different types of aggregates and the detailed methods used in their production. In an attempt to address this need, we assembled the Minimum Information Required for Reproducible Aggregation Experiments (MIRRAGGE) guidelines, considering first-principles and the established literature on protein self-assembly and aggregation. This consensus information aims to cover the major and subtle determinants of experimental reproducibility while avoiding excessive technical details that are of limited practical interest for non-specialized users. The MIRRAGGE table (template available in Supplementary Information) is useful as a guide for the design of new studies and as a checklist during submission of experimental reports for publication. Full disclosure of relevant information also enables other researchers to reproduce results correctly and facilitates systematic data deposition into curated databases.

Intrinsically Disordered Regions of the DNA-Binding Domain of Human FoxP1 Facilitate Domain Swapping

Forkhead box P (FoxP) proteins are unique transcription factors that spatiotemporally regulate gene expression by tethering two chromosome loci together via functional domain-swapped dimers formed through their DNA-binding domains. Further, the differential kinetics on this dimerization mechanism underlie an intricate gene regulation network at physiological conditions. Nonetheless, poor understanding of the structural dynamics and steps of the association process impedes to link the functional domain swapping to human-associated diseases. Here, we have characterized the DNA-binding domain of human FoxP1 by integrating single-molecule Förster resonance energy transfer and hydrogen-deuterium exchange mass spectrometry data with molecular dynamics simulations. Our results confirm the formation of a previously postulated domain-swapped (DS) FoxP1 dimer in solution and reveal the presence of highly populated, heterogeneous, and locally disordered dimeric intermediates along the dimer dissociation pathway. The unique features of FoxP1 provide a glimpse of how intrinsically disordered regions can facilitate domain swapping oligomerization and other tightly regulated association mechanisms relevant in biological processes.

Exploring the interplay between fibrillization and amorphous aggregation channels on the energy landscapes of tau repeat isoforms

Filaments made up of different isoforms of tau protein are associated with a variety of neurodegenerative diseases. Filaments made up of the 4R-tau isoform, which has four repeat regions (R1 to R4), are found in patients suffering from Alzheimer's disease, while filaments made of the 3R-tau isoform, which contains only three repeat units (R1, R3, and R4), are found in patients with Pick's disease (frontotemporal dementia). In this work, a predictive coarse-grained protein force field, the associative memory water-mediated structure and energy model (AWSEM), is used to study the energy landscapes of nucleation of the two different fibrils derived from patients with Pick's and Alzheimer's diseases. The landscapes for nucleating both fibril types contain amorphous oligomers leading to branched structures as well as prefibrillar oligomers. These two classes of oligomers differ in their structural details: The prefibrillar oligomers have more parallel in-register β-strands, which ultimately lead to amyloid fibrils, while the amorphous oligomers are characterized by a near random β-strand stacking, leading to a distinct amorphous phase. The landscape topography suggests that there must be significant structural reordering, or "backtracking," to transit from the amorphous aggregation channel to the fibrillization channel. Statistical mechanical perturbation theory allows us to evaluate the effects of changing concentration on the aggregation free-energy landscapes and to predict the effects of phosphorylation, which is known to facilitate the aggregation of tau repeats.

Successes and challenges in simulating the folding of large proteins

Computational simulations of protein folding can be used to interpret experimental folding results, to design new folding experiments, and to test the effects of mutations and small molecules on folding. However, whereas major experimental and computational progress has been made in understanding how small proteins fold, research on larger, multidomain proteins, which comprise the majority of proteins, is less advanced. Specifically, large proteins often fold via long-lived partially folded intermediates, whose structures, potentially toxic oligomerization, and interactions with cellular chaperones remain poorly understood. Molecular dynamics based folding simulations that rely on knowledge of the native structure can provide critical, detailed information on folding free energy landscapes, intermediates, and pathways. Further, increases in computational power and methodological advances have made folding simulations of large proteins practical and valuable. Here, using serpins that inhibit proteases as an example, we review native-centric methods for simulating the folding of large proteins. These synergistic approaches range from Gō and related structure-based models that can predict the effects of the native structure on folding to all-atom-based methods that include side-chain chemistry and can predict how disease-associated mutations may impact folding. The application of these computational approaches to serpins and other large proteins highlights the successes and limitations of current computational methods and underscores how computational results can be used to inform experiments. These powerful simulation approaches in combination with experiments can provide unique insights into how large proteins fold and misfold, expanding our ability to predict and manipulate protein folding.

Protein tolerance to random circular permutation correlates with thermostability and local energetics of residue-residue contacts

Adenylate kinase (AK) orthologs with a range of thermostabilities were subjected to random circular permutation, and deep mutational scanning was used to evaluate where new protein termini were nondisruptive to activity. The fraction of circularly permuted variants that retained function in each library correlated with AK thermostability. In addition, analysis of the positional tolerance to new termini, which increase local conformational flexibility, showed that bonds were either functionally sensitive to cleavage across all homologs, differentially sensitive, or uniformly tolerant. The mobile AMP-binding domain, which displays the highest calculated contact energies, presented the greatest tolerance to new termini across all AKs. In contrast, retention of function in the lid and core domains was more dependent upon AK melting temperature. These results show that family permutation profiling identifies primary structure that has been selected by evolution for dynamics that are critical to activity within an enzyme family. These findings also illustrate how deep mutational scanning can be applied to protein homologs in parallel to differentiate how topology, stability, and local energetics govern mutational tolerance.

Competition of individual domain folding with inter-domain interaction in WW domain engineered repeat proteins

Engineered repeat proteins have proven to be a fertile ground for studying the competition between folding, misfolding and transient aggregation of tethered protein domains. We examine the interplay between folding and inter-domain interactions of engineered FiP35 WW domain repeat proteins with n = 1 through 5 repeats. We characterize protein expression, thermal and guanidium melts, as well as laser T-jump kinetics. All experimental data is fitted by a global fitting model with two states per domain (U, N), plus a third state M to account for non-native states due to domain interactions present in all but the monomer. A detailed structural model is provided by coarse-grained simulated annealing using the AWSEM Hamiltonian. Tethered FiP35 WW domains with n = 2 and 3 domains are just slightly less stable than the monomer. The n = 4 oligomer is yet less stable, its expression yield is much lower than the monomer's, and depends on the purification tag used. The n = 5 plasmid did not express at all, indicating the sudden onset of aggregation past n = 4. Thus, tethered FiP35 has a critical nucleus size for inter-domain aggregation of n ≈ 4. According to our simulations, misfolded structures become increasingly prevalent as one proceeds from monomer to pentamer, with extended inter-domain beta sheets appearing first, then multi-sheet 'intramolecular amyloid' structures, and finally novel motifs containing alpha helices. We discuss the implications of our results for oligomeric aggregate formation and structure, transient aggregation of proteins whilst folding, as well as for protein evolution that starts with repeat proteins.

Tandem domain swapping: determinants of multidomain protein misfolding

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Domain swapping refers to the exchange of structural elements between protein domains.

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Experiments show that tandem homologous domains are prone to domain swapping.

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Recent studies establish a framework to understand the formation of tandem domain swaps.

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Prediction of tandem domain swaps is possible but hindered by the amount of available data.

Tandem homologous domains in proteins are susceptible to misfolding through the formation of domain swaps, non-native conformations involving the exchange of equivalent structural elements between adjacent domains. Cutting-edge biophysical experiments have recently allowed the observation of tandem domain swapping events at the single molecule level. In addition, computer simulations have shed light into the molecular mechanisms of domain swap formation and serve as the basis for methods to systematically predict them. At present, the number of studies on tandem domain swaps is still small and limited to a few domain folds, but they offer important insights into the folding and evolution of multidomain proteins with applications in the field of protein design.

Critical role of histone tail entropy in nucleosome unwinding

The nucleosome is the fundamental packaging unit for the genome. It must remain tightly wound to ensure genome stability while simultaneously being flexible enough to keep the DNA molecule accessible for genome function. The set of physicochemical interactions responsible for the delicate balance between these naturally opposed processes have not been determined due to challenges in resolving partially unwound nucleosome configurations at atomic resolution. Using a near atomistic protein-DNA model and advanced sampling techniques, we calculate the free energy cost of nucleosome DNA unwinding. Our simulations identify a large energetic barrier that decouples the outer and the inner DNA unwinding into two separate processes, occurring on different time scales. This dynamical decoupling allows the exposure of outer DNA at a modest cost to ensure accessibility while keeping the inner DNA and the histone core intact to maintain stability. We also reveal that this energetic barrier arises from a delayed loss of contacts between disordered histone tails and the DNA and is, surprisingly, largely offset by an entropic contribution from these tails. Implications of this enthalpy entropy compensation for the regulation of nucleosome stability and genome function are discussed.

Localizing Frustration in Proteins Using All-Atom Energy Functions

The problems of protein folding and protein design are two sides of the same coin. Protein folding involves exploring a protein's configuration space given a fixed sequence, whereas protein design involves searching in sequence space given a particular target structure. For a protein to fold quickly and reliably, its energy landscape must be biased toward the folded ensemble throughout its configuration space and must lack deep kinetic traps that would otherwise frustrate folding. Evolution has "designed" the sequences of many naturally occurring proteins, through an eons-long process of random mutation and selection, to yield landscapes with a minimal degree of frustration. The task facing humans hoping to design protein sequences that fold into particular structures is to use the available approximate energy functions to sculpt funneled landscapes that work in the laboratory. In this work, we demonstrate how to calculate several localized frustration measures using an all-atom energy function. Specifically, we employ the Rosetta energy function, which has been used successfully to design proteins and which has a natural pairwise decomposition that is suitably solvent-averaged. We calculate these newly developed frustration measures for both a mutated WW domain, FiP35, and a three-helix bundle that was designed completely by humans, Alpha3D. The structure of FiP35 exhibits less localized frustration than that of Alpha3D. A mutation toward the consensus sequence for WW domains in FiP35, which has been shown unexpectedly in experiment to disrupt folding, induces localized frustration by disrupting the hydrophobic core. By performing a limited redesign on the sequence of Alpha3D, we show that some, but not all, mutations that lower the energy also result in decreased frustration. The results suggest that, in addition to being useful for detecting residual frustration in protein structures, optimizing the localized frustration measures presented here may be a useful and automatic means of balancing positive and negative design in protein design tasks.

Characterizing highly dynamic conformational states: The transcription bubble in RNAP-promoter open complex as an example

Bio-macromolecules carry out complicated functions through structural changes. To understand their mechanism of action, the structure of each step has to be characterized. While classical structural biology techniques allow the characterization of a few "structural snapshots" along the enzymatic cycle (usually of stable conformations), they do not cover all (and often fast interconverting) structures in the ensemble, where each may play an important functional role. Recently, several groups have demonstrated that structures of different conformations in solution could be solved by measuring multiple distances between different pairs of residues using single-molecule Förster resonance energy transfer (smFRET) and using them as constrains for hybrid/integrative structural modeling. However, this approach is limited in cases where the conformational dynamics is faster than the technique's temporal resolution. In this study, we combine existing tools that elucidate sub-millisecond conformational dynamics together with hybrid/integrative structural modeling to study the conformational states of the transcription bubble in the bacterial RNA polymerase-promoter open complex (RPo). We measured microsecond alternating laser excitation-smFRET of differently labeled lacCONS promoter dsDNA constructs. We used a combination of burst variance analysis, photon-by-photon hidden Markov modeling, and the FRET-restrained positioning and screening approach to identify two conformational states for RPo. The experimentally derived distances of one conformational state match the known crystal structure of bacterial RPo. The experimentally derived distances of the other conformational state have characteristics of a scrunched RPo. These findings support the hypothesis that sub-millisecond dynamics in the transcription bubble are responsible for transcription start site selection.

Folding pathway of an Ig domain is conserved on and off the ribosome

Most proteins need to fold into a specific 3D structure to function. The mechanism by which isolated proteins fold has been thoroughly studied by experiment and theory. However, in the cell proteins do not fold in isolation but are synthesized as linear chains by the ribosome during translation. It is therefore natural to ask at which point during synthesis proteins fold, and whether this differs from the folding of isolated protein molecules. By studying folding of a well-characterized protein domain, titin I27, stalled at different points during translation, we show that it already folds in the mouth of the ribosome exit tunnel and that the mechanism is almost identical to that of the isolated protein.

Proteins that fold cotranslationally may do so in a restricted configurational space, due to the volume occupied by the ribosome. How does this environment, coupled with the close proximity of the ribosome, affect the folding pathway of a protein? Previous studies have shown that the cotranslational folding process for many proteins, including small, single domains, is directly affected by the ribosome. Here, we investigate the cotranslational folding of an all-β Ig domain, titin I27. Using an arrest peptide-based assay and structural studies by cryo-EM, we show that I27 folds in the mouth of the ribosome exit tunnel. Simulations that use a kinetic model for the force dependence of escape from arrest accurately predict the fraction of folded protein as a function of length. We used these simulations to probe the folding pathway on and off the ribosome. Our simulations—which also reproduce experiments on mutant forms of I27—show that I27 folds, while still sequestered in the mouth of the ribosome exit tunnel, by essentially the same pathway as free I27, with only subtle shifts of critical contacts from the C to the N terminus.

Surveying the Energy Landscapes of Aβ Fibril Polymorphism

Many unrelated proteins and peptides have been found spontaneously to form amyloid fibers above a critical concentration. Even for a single sequence, however, the amyloid fold is not a single well-defined structure. Although the cross-β hydrogen bonding pattern is common to all amyloids, all other aspects of amyloid fiber structures are sensitive to both the sequence of the aggregating peptides and the solvent conditions under which the aggregation occurs. Amyloid fibers are easy to identify and grossly characterize using microscopy, but their insolubility and aperiodicity along the dimensions transverse to the fiber axis have complicated detailed experimental structural characterization. In this paper, we explore the landscape of possibilities for amyloid protofilament structures that are made up of a single stack of peptides associated in a parallel in-register manner. We view this landscape as a two-dimensional version of the usual three-dimensional protein folding problem: the survey of the two-dimensional folds of protein ribbons. Adopting this view leads to a practical method of predicting stable protofilament structures of arbitrary sequences. We apply this scheme to variants of Aβ, the amyloid forming peptide that is characteristically associated with Alzheimer's disease. Consistent with what is known from experiment, we find that Aβ protofibrils are polymorphic. To our surprise, however, the ribbon-folding landscape of Aβ turned out to be strikingly simple. We confirm that, at the level of the monomeric protofilament, the landscape for the Aβ sequence is reasonably well funneled toward structures that are similar to those that have been determined by experiment. The landscape has more distinct minima than does a typical globular protein landscape but fewer and deeper minima than the landscape of a randomly shuffled sequence having the same overall composition. It is tempting to consider the possibility that the significant degree of funneling of Aβ's ribbon-folding landscape has arisen as a result of natural selection. More likely, however, the intermediate complexity of Aβ's ribbon-folding landscape has come from the post facto selection of the Aβ sequence as an object of study by researchers because only by having a landscape with some degree of funneling can ordered aggregation of such a peptide occur at in vivo concentrations. In addition to predicting polymorph structures, we show that predicted solubilities of polymorphs correlate with experiment and with their elongation free energies computed by coarse-grained molecular dynamics.

Systematic mapping of free energy landscapes of a growing filamin domain during biosynthesis

Efficient synthesis and folding of proteins, avoiding misfolded states, are central to cell function. As folding may be initiated in parallel with translation, key experimental challenges are to map changes that occur in folding free energy landscapes as translation proceeds and to understand how these landscapes might be modulated by the ribosome and auxiliary factors. Here, we study the length-dependent folding of a domain from a tandem repeat protein and solve the structure of a stable folding intermediate. Although destabilized by the ribosome at equilibrium, modeling of the nonequilibrium folding pathway nevertheless indicates a significant role for proline isomerization during translation. We develop a simple model to explore the impact of cotranslational folding kinetics on misfolding hazards.

Cotranslational folding (CTF) is a fundamental molecular process that ensures efficient protein biosynthesis and minimizes the formation of misfolded states. However, the complexity of this process makes it extremely challenging to obtain structural characterizations of CTF pathways. Here, we correlate observations of translationally arrested nascent chains with those of a systematic C-terminal truncation strategy. We create a detailed description of chain length-dependent free energy landscapes associated with folding of the FLN5 filamin domain, in isolation and on the ribosome, and thus, quantify a substantial destabilization of the native structure on the ribosome. We identify and characterize two folding intermediates formed in isolation, including a partially folded intermediate associated with the isomerization of a conserved cis proline residue. The slow folding associated with this process raises the prospect that neighboring unfolded domains might accumulate and misfold during biosynthesis. We develop a simple model to quantify the risk of misfolding in this situation and show that catalysis of folding by peptidyl-prolyl isomerases is sufficient to eliminate this hazard.

Spontaneous refolding of the large multidomain protein malate synthase G proceeds through misfolding traps

Most protein folding studies until now focus on single domain or truncated proteins. Although great insights in the folding of such systems has been accumulated, very little is known regarding the proteins containing multiple domains. It has been shown that the high stability of domains, in conjunction with inter-domain interactions, manifests as a frustrated energy landscape, causing complexity in the global folding pathway. However, multidomain proteins despite containing independently foldable, loosely cooperative sections can fold into native states with amazing speed and accuracy. To understand the complexity in mechanism, studies were conducted previously on the multidomain protein malate synthase G (MSG), an enzyme of the glyoxylate pathway with four distinct and adjacent domains. It was shown that the protein refolds to a functionally active intermediate state at a fast rate, which slowly produces the native state. Although experiments decoded the nature of the intermediate, a full description of the folding pathway was not elucidated. In this study, we use a battery of biophysical techniques to examine the protein's folding pathway. By using multiprobe kinetics studies and comparison with the equilibrium behavior of protein against urea, we demonstrate that the unfolded polypeptide undergoes conformational compaction to a misfolded intermediate within milliseconds of refolding. The misfolded product appears to be stabilized under moderate denaturant concentrations. Further folding of the protein produces a stable intermediate, which undergoes partial unfolding-assisted large segmental rearrangements to achieve the native state. This study reveals an evolved folding pathway of the multidomain protein MSG, which involves surpassing the multiple misfolding traps during refolding.

The Associative Memory, Water Mediated, Structure and Energy Model (AWSEM)-Amylometer: Predicting Amyloid Propensity and Fibril Topology Using an Optimized Folding Landscape Model

Amyloids are fibrillar protein aggregates with simple repeated structural motifs in their cores, usually β-strands but sometimes α-helices. Identifying the amyloid-prone regions within protein sequences is important both for understanding the mechanisms of amyloid-associated diseases and for understanding functional amyloids. Based on the crystal structures of seven cross-β amyloidogenic peptides with different topologies and one recently solved cross-α fiber structure, we have developed a computational approach for identifying amyloidogenic segments in protein sequences using the Associative memory, Water mediated, Structure and Energy Model (AWSEM). The AWSEM-Amylometer performs favorably in comparison with other predictors in predicting aggregation-prone sequences in multiple data sets. The method also predicts well the specific topologies (the relative arrangement of β-strands in the core) of the amyloid fibrils. An important advantage of the AWSEM-Amylometer over other existing methods is its direct connection with an efficient, optimized protein folding simulation model, AWSEM. This connection allows one to combine efficient and accurate search of protein sequences for amyloidogenic segments with the detailed study of the thermodynamic and kinetic roles that these segments play in folding and aggregation in the context of the entire protein sequence. We present new simulation results that highlight the free energy landscapes of peptides that can take on multiple fibril topologies. We also demonstrate how the Amylometer methodology can be straightforwardly extended to the study of functional amyloids that have the recently discovered cross-α fibril architecture.

Comparing the energy landscapes for native folding and aggregation of PrP

Protein sequences are evolved to encode generally one folded structure, out of a nearly infinite array of possible folds. Underlying this code is a funneled free energy landscape that guides folding to the native conformation. Protein misfolding and aggregation are also a manifestation of free-energy landscapes. The detailed mechanisms of these processes are poorly understood, but often involve rare, transient species and a variety of different pathways. The inherent complexity of misfolding has hampered efforts to measure aggregation pathways and the underlying energy landscape, especially using traditional methods where ensemble averaging obscures important rare and transient events. We recently studied the misfolding and aggregation of prion protein by examining 2 monomers tethered in close proximity as a dimer, showing how the steps leading to the formation of a stable aggregated state can be resolved in the single-molecule limit and the underlying energy landscape thereby reconstructed. This approach allows a more quantitative comparison of native folding versus misfolding, including fundamental differences in the dynamics for misfolding. By identifying key steps and interactions leading to misfolding, it should help to identify potential drug targets. Here we describe the importance of characterizing free-energy landscapes for aggregation and the challenges involved in doing so, and we discuss how single-molecule studies can help test proposed structural models for PrP aggregates.

Frustration, function and folding

Natural protein molecules are exceptional polymers. Encoded in apparently random strings of amino-acids, these objects perform clear physical tasks that are rare to find by simple chance. Accurate folding, specific binding, powerful catalysis, are examples of basic chemical activities that the great majority of polypeptides do not display, and are thought to be the outcome of the natural history of proteins. Function, a concept genuine to Biology, is at the core of evolution and often conflicts with the physical constraints. Locating the frustration between discrepant goals in a recurrent system leads to fundamental insights about the chances and necessities that shape the encoding of biological information.

Protein structure prediction: making AWSEM AWSEM-ER by adding evolutionary restraints

Protein sequences have evolved to fold into functional structures, resulting in families of diverse protein sequences that all share the same overall fold. One can harness protein family sequence data to infer likely contacts between pairs of residues. In the current study, we combine this kind of inference from coevolutionary information with a coarse-grained protein force field ordinarily used with single sequence input, the Associative memory, Water mediated, Structure and Energy Model (AWSEM), to achieve improved structure prediction. The resulting Associative memory, Water mediated, Structure and Energy Model with Evolutionary Restraints (AWSEM-ER) yields a significant improvement in the quality of protein structure prediction over the single sequence prediction from AWSEM when a sufficiently large number of homologous sequences are available. Free energy landscape analysis shows that the addition of the evolutionary term shifts the free energy minimum to more native-like structures, which explains the improvement in the quality of structures when performing predictions using simulated annealing. Simulations using AWSEM without coevolutionary information have proved useful in elucidating not only protein folding behavior, but also mechanisms of protein function. The success of AWSEM-ER in de novo structure prediction suggests that the enhanced model opens the door to functional studies of proteins even when no experimentally solved structures are available.

Aggregation landscapes of Huntingtin exon 1 protein fragments and the critical repeat length for the onset of Huntington's disease

Huntington's disease (HD) is a neurodegenerative disease caused by an abnormal expansion in the polyglutamine (polyQ) track of the Huntingtin (HTT) protein. The severity of the disease depends on the polyQ repeat length, arising only in patients with proteins having 36 repeats or more. Previous studies have shown that the aggregation of N-terminal fragments (encoded by HTT exon 1) underlies the disease pathology in mouse models and that the HTT exon 1 gene product can self-assemble into amyloid structures. Here, we provide detailed structural mechanisms for aggregation of several protein fragments encoded by HTT exon 1 by using the associative memory, water-mediated, structure and energy model (AWSEM) to construct their free energy landscapes. We find that the addition of the N-terminal 17-residue sequence ([Formula: see text]) facilitates polyQ aggregation by encouraging the formation of prefibrillar oligomers, whereas adding the C-terminal polyproline sequence ([Formula: see text]) inhibits aggregation. The combination of both terminal additions in HTT exon 1 fragment leads to a complex aggregation mechanism with a basic core that resembles that found for the aggregation of pure polyQ repeats using AWSEM. At the extrapolated physiological concentration, although the grand canonical free energy profiles are uphill for HTT exon 1 fragments having 20 or 30 glutamines, the aggregation landscape for fragments with 40 repeats has become downhill. This computational prediction agrees with the critical length found for the onset of HD and suggests potential therapies based on blocking early binding events involving the terminal additions to the polyQ repeats.

The Aggregation Free Energy Landscapes of Polyglutamine Repeats

Aggregates of proteins containing polyglutamine (polyQ) repeats are strongly associated with several neurodegenerative diseases. The length of the repeats correlates with the severity of the disease. Previous studies have shown that pure polyQ peptides aggregate by nucleated growth polymerization and that the size of the critical nucleus (n*) decreases from tetrameric to dimeric and monomeric as length increases from Q₁₈ to Q₂₆. Why the critical nucleus size changes with repeat-length has been unclear. Using the associative memory, water-mediated, structure and energy model, we construct the aggregation free energy landscapes for polyQ peptides of different repeat-lengths. These studies show that the monomer of the shorter repeat-length (Q₂₀) prefers an extended conformation and that its aggregation indeed has a trimeric nucleus (n* ∼ 3), while a longer repeat-length monomer (Q₃₀) prefers a β-hairpin conformation which then aggregates in a downhill fashion at 0.1 mM. For an intermediate length peptide (Q₂₆), there is an equal preference for hairpin and extended forms in the monomer which leads to a mixed inhomogeneous nucleation mechanism for fibrils. The predicted changes of monomeric structure and nucleation mechanism are confirmed by studying the aggregation free energy profile for a polyglutamine repeat with site-specific PG mutations that favor the hairpin form, giving results in harmony with experiments on this system.

Markov state models of protein misfolding

Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity.

Exploring the aggregation free energy landscape of the amyloid-β protein (1-40)

A predictive coarse-grained protein force field [associative memory, water-mediated, structure, and energy model for molecular dynamics (AWSEM)-MD] is used to study the energy landscapes and relative stabilities of amyloid-β protein (1-40) in the monomer and all of its oligomeric forms up to an octamer. We find that an isolated monomer is mainly disordered with a short α-helix formed at the central hydrophobic core region (L17-D23). A less stable hairpin structure, however, becomes increasingly more stable in oligomers, where hydrogen bonds can form between neighboring monomers. We explore the structure and stability of both prefibrillar oligomers that consist of mainly antiparallel β-sheets and fibrillar oligomers with only parallel β-sheets. Prefibrillar oligomers are polymorphic but typically take on a cylindrin-like shape composed of mostly antiparallel β-strands. At the concentration of the simulation, the aggregation free energy landscape is nearly downhill. We use umbrella sampling along a structural progress coordinate for interconversion between prefibrillar and fibrillar forms to identify a conversion pathway between these forms. The fibrillar oligomer only becomes favored over its prefibrillar counterpart in the pentamer where an interconversion bottleneck appears. The structural characterization of the pathway along with statistical mechanical perturbation theory allow us to evaluate the effects of concentration on the free energy landscape of aggregation as well as the effects of the Dutch and Arctic mutations associated with early onset of Alzheimer's disease.

An Internal Disulfide Locks a Misfolded Aggregation-prone Intermediate in Cataract-linked Mutants of Human γD-Crystallin

Considerable mechanistic insight has been gained into amyloid aggregation; however, a large number of non-amyloid protein aggregates are considered "amorphous," and in most cases, little is known about their mechanisms. Amorphous aggregation of γ-crystallins in the eye lens causes cataract, a widespread disease of aging. We combined simulations and experiments to study the mechanism of aggregation of two γD-crystallin mutants, W42R and W42Q: the former a congenital cataract mutation, and the latter a mimic of age-related oxidative damage. We found that formation of an internal disulfide was necessary and sufficient for aggregation under physiological conditions. Two-chain all-atom simulations predicted that one non-native disulfide in particular, between Cys(32) and Cys(41), was likely to stabilize an unfolding intermediate prone to intermolecular interactions. Mass spectrometry and mutagenesis experiments confirmed the presence of this bond in the aggregates and its necessity for oxidative aggregation under physiological conditions in vitro Mining the simulation data linked formation of this disulfide to extrusion of the N-terminal β-hairpin and rearrangement of the native β-sheet topology. Specific binding between the extruded hairpin and a distal β-sheet, in an intermolecular chain reaction similar to domain swapping, is the most probable mechanism of aggregate propagation.

Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell

All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.

A Simple Model of Protein Domain Swapping in Crowded Cellular Environments

Domain swapping in proteins is an important mechanism of functional and structural innovation. However, despite its ubiquity and importance, the physical mechanisms that lead to domain swapping are poorly understood. Here, we present a simple two-dimensional coarse-grained model of protein domain swapping in the cytoplasm. In our model, two-domain proteins partially unfold and diffuse in continuous space. Monte Carlo multiprotein simulations of the model reveal that domain swapping occurs at intermediate temperatures, whereas folded dimers and folded monomers prevail at low temperatures, and partially unfolded monomers predominate at high temperatures. We use a simplified amino acid alphabet consisting of four residue types, and find that the oligomeric state at a given temperature depends on the sequence of the protein. We also show that hinge strain between domains can promote domain swapping, consistent with experimental observations for real proteins. Domain swapping depends nonmonotonically on the protein concentration, with domain-swapped dimers occurring at intermediate concentrations and nonspecific interactions between partially unfolded proteins occurring at high concentrations. For folded proteins, we recover the result obtained in three-dimensional lattice simulations, i.e., that functional dimerization is most prevalent at intermediate temperatures and nonspecific interactions increase at low temperatures.

Protein Folding and Structure Prediction from the Ground Up: The Atomistic Associative Memory, Water Mediated, Structure and Energy Model

The associative memory, water mediated, structure and energy model (AWSEM) is a coarse-grained force field with transferable tertiary interactions that incorporates local in sequence energetic biases using bioinformatically derived structural information about peptide fragments with locally similar sequences that we call memories. The memory information from the protein data bank (PDB) database guides proper protein folding. The structural information about available sequences in the database varies in quality and can sometimes lead to frustrated free energy landscapes locally. One way out of this difficulty is to construct the input fragment memory information from all-atom simulations of portions of the complete polypeptide chain. In this paper, we investigate this approach first put forward by Kwac and Wolynes in a more complete way by studying the structure prediction capabilities of this approach for six α-helical proteins. This scheme which we call the atomistic associative memory, water mediated, structure and energy model (AAWSEM) amounts to an ab initio protein structure prediction method that starts from the ground up without using bioinformatic input. The free energy profiles from AAWSEM show that atomistic fragment memories are sufficient to guide the correct folding when tertiary forces are included. AAWSEM combines the efficiency of coarse-grained simulations on the full protein level with the local structural accuracy achievable from all-atom simulations of only parts of a large protein. The results suggest that a hybrid use of atomistic fragment memory and database memory in structural predictions may well be optimal for many practical applications.

Structural Determinants of Misfolding in Multidomain Proteins

Recent single molecule experiments, using either atomic force microscopy (AFM) or Förster resonance energy transfer (FRET) have shown that multidomain proteins containing tandem repeats may form stable misfolded structures. Topology-based simulation models have been used successfully to generate models for these structures with domain-swapped features, fully consistent with the available data. However, it is also known that some multidomain protein folds exhibit no evidence for misfolding, even when adjacent domains have identical sequences. Here we pose the question: what factors influence the propensity of a given fold to undergo domain-swapped misfolding? Using a coarse-grained simulation model, we can reproduce the known propensities of multidomain proteins to form domain-swapped misfolds, where data is available. Contrary to what might be naively expected based on the previously described misfolding mechanism, we find that the extent of misfolding is not determined by the relative folding rates or barrier heights for forming the domains present in the initial intermediates leading to folded or misfolded structures. Instead, it appears that the propensity is more closely related to the relative stability of the domains present in folded and misfolded intermediates. We show that these findings can be rationalized if the folded and misfolded domains are part of the same folding funnel, with commitment to one structure or the other occurring only at a relatively late stage of folding. Nonetheless, the results are still fully consistent with the kinetic models previously proposed to explain misfolding, with a specific interpretation of the observed rate coefficients. Finally, we investigate the relation between interdomain linker length and misfolding, and propose a simple alchemical model to predict the propensity for domain-swapped misfolding of multidomain proteins.

Advances in NMR Methods To Map Allosteric Sites: From Models to Translation

The last five years have witnessed major developments in the understanding of the allosteric phenomenon, broadly defined as coupling between remote molecular sites. Such advances have been driven not only by new theoretical models and pharmacological applications of allostery, but also by progress in the experimental approaches designed to map allosteric sites and transitions. Among these techniques, NMR spectroscopy has played a major role given its unique near-atomic resolution and sensitivity to the dynamics that underlie allosteric couplings. Here, we highlight recent progress in the NMR methods tailored to investigate allostery with the goal of offering an overview of which NMR approaches are best suited for which allosterically relevant questions. The picture of the allosteric "NMR toolbox" is provided starting from one of the simplest models of allostery (i.e., the four-state thermodynamic cycle) and continuing to more complex multistate mechanisms. We also review how such an "NMR toolbox" has assisted the elucidation of the allosteric molecular basis for disease-related mutations and the discovery of novel leads for allosteric drugs. From this overview, it is clear that NMR plays a central role not only in experimentally validating transformative theories of allostery, but also in tapping the full translational potential of allosteric systems.

Energy landscapes of a mechanical prion and their implications for the molecular mechanism of long-term memory

Aplysia cytoplasmic polyadenylation element binding (CPEB) protein, a translational regulator that recruits mRNAs and facilitates translation, has been shown to be a key component in the formation of long-term memory. Experimental data show that CPEB exists in at least a low-molecular weight coiled-coil oligomeric form and an amyloid fiber form involving the Q-rich domain (CPEB-Q). Using a coarse-grained energy landscape model, we predict the structures of the low-molecular weight oligomeric form and the dynamics of their transitions to the β-form. Up to the decamer, the oligomeric structures are predicted to be coiled coils. Free energy profiles confirm that the coiled coil is the most stable form for dimers and trimers. The structural transition from α to β is shown to be concentration dependent, with the transition barrier decreasing with increased concentration. We observe that a mechanical pulling force can facilitate the α-helix to β-sheet (α-to-β) transition by lowering the free energy barrier between the two forms. Interactome analysis of the CPEB protein suggests that its interactions with the cytoskeleton could provide the necessary mechanical force. We propose that, by exerting mechanical forces on CPEB oligomers, an active cytoskeleton can facilitate fiber formation. This mechanical catalysis makes possible a positive feedback loop that would help localize the formation of CPEB fibers to active synapse areas and mark those synapses for forming a long-term memory after the prion form is established. The functional role of the CPEB helical oligomers in this mechanism carries with it implications for targeting such species in neurodegenerative diseases.

De Novo Evolutionary Emergence of a Symmetrical Protein Is Shaped by Folding Constraints

Molecular evolution has focused on the divergence of molecular functions, yet we know little about how structurally distinct protein folds emerge de novo. We characterized the evolutionary trajectories and selection forces underlying emergence of β-propeller proteins, a globular and symmetric fold group with diverse functions. The identification of short propeller-like motifs (<50 amino acids) in natural genomes indicated that they expanded via tandem duplications to form extant propellers. We phylogenetically reconstructed 47-residue ancestral motifs that form five-bladed lectin propellers via oligomeric assembly. We demonstrate a functional trajectory of tandem duplications of these motifs leading to monomeric lectins. Foldability, i.e., higher efficiency of folding, was the main parameter leading to improved functionality along the entire evolutionary trajectory. However, folding constraints changed along the trajectory: initially, conflicts between monomer folding and oligomer assembly dominated, whereas subsequently, upon tandem duplication, tradeoffs between monomer stability and foldability took precedence.

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Inferred 47-aminoacid ancestral motifs fold into functional β-propeller assemblies

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Motif duplication, fusion, and diversification yield functional monomeric propellers

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Folding efficiency was the key parameter optimized throughout propeller emergence

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Single-motif precursors in extant genomes support the reconstructed emergence pathway

Reduction of All-Atom Protein Folding Dynamics to One-Dimensional Diffusion

Theoretical models have often modeled protein folding dynamics as diffusion on a low-dimensional free energy surface, a remarkable simplification. However, the accuracy of such an approximation and the number of dimensions required were not clear. For all-atom folding simulations of ten small proteins in explicit solvent we show that the folding dynamics can indeed be accurately described as diffusion on just a single coordinate, the fraction of native contacts (Q). The diffusion models reproduce both folding rates, and finer details such as transition-path durations and diffusive propagators. The Q-averaged diffusion coefficients decrease with chain length, as anticipated from energy landscape theory. Although the Q-diffusion model does not capture transition-path durations for the protein NuG2, we show that this can be accomplished by designing an improved coordinate Qopt. Overall, one-dimensional diffusion on a suitable coordinate turns out to be a remarkably faithful model for the dynamics of the proteins considered.

Transient misfolding dominates multidomain protein folding

Neighbouring domains of multidomain proteins with homologous tandem repeats have divergent sequences, probably as a result of evolutionary pressure to avoid misfolding and aggregation, particularly at the high cellular protein concentrations. Here we combine microfluidic-mixing single-molecule kinetics, ensemble experiments and molecular simulations to investigate how misfolding between the immunoglobulin-like domains of titin is prevented. Surprisingly, we find that during refolding of tandem repeats, independent of sequence identity, more than half of all molecules transiently form a wide range of misfolded conformations. Simulations suggest that a large fraction of these misfolds resemble an intramolecular amyloid-like state reported in computational studies. However, for naturally occurring neighbours with low sequence identity, these transient misfolds disappear much more rapidly than for identical neighbours. We thus propose that evolutionary sequence divergence between domains is required to suppress the population of long-lived, potentially harmful misfolded states, whereas large populations of transient misfolded states appear to be tolerated.

Single molecule kinetics investigations and molecular simulations are useful tools in elucidating protein assembly mechanisms. Here, the authors use these to show that even naturally occurring tandem repeats undergo transient misfolding and that assembly is much more complex than we previously understood.