Extant fold-switching proteins are widespread

Global Fold Switching of the RafH Protein: Diverse Structures with a Conserved Pathway

It is generally believed that a protein's sequence uniquely determines its structure, the basis for a protein to perform biological functions. However, as a representative metamorphic protein, RfaH can be encoded by a single amino acid sequence into two distinct native state structures. Its C-terminal domain (CTD) either takes an all-α-helical configuration to pack tightly with its N-terminal domain (NTD), or the CTD disassociates from the NTD, transforms into an all-β-barrel fold, and further attaches to the ribosome, leaving the NTD exposed to bind RNA polymerases. Therefore, the RfaH protein couples transcription and translation processes. Although previous studies have provided a preliminary understanding of its function, the full course of the conformational change of RfaH-CTD at the atomic level is elusive. We used teDA2, a feature space-based enhanced sampling protocol, to explore the transformation of RfaH-CTD. We found that it undergoes a large-scale structural rearrangement, with characteristic spectra as the fingerprint, and a global unfolding transition with a tighter and energetically moderate molten globule-like nucleus formed in between. The formation of this nucleus limits the possible intermediate conformations, facilitates the formation of secondary and tertiary structures, and thus ensures the efficiency of transformation. The key features along the transition path disclosed from this work are likely associated with the evolution of RfaH, such that encoding a single sequence into multiple folds with distinct biological functions is energetically unhindered.

Curious Case of MAD2 Protein: Diverse Folding Intermediates Leading to Alternate Native States

Anfinsen's dogma postulates that for one sequence there will be only one unique structure that is necessary for the functioning of the protein. However, over the years there have been a number of departures from this postulate. As far as function is considered, there are growing examples of proteins that "moonlight", perform multiple unrelated functions. With the discovery of intrinsically disordered proteins, morpheeins, chameleonic sequences, and metamorphic proteins that can switch folds, we have acquired a more nuanced understanding of protein folding and dynamics. Appearing to apparently contradict the classical folding paradigm, metamorphic proteins are considered exotic species. In this work, we have explored the free energy landscape and folding pathways of the metamorphic protein MAD2 which is an important component of the spindle checkpoint. It coexists in two alternate states: the inactive open state and the active closed state. Using a dual-basin structure-based model approach we have shown that a variety of intermediates and multiple pathways are available to MAD2 to fold into its alternate forms. This approach involves performing molecular dynamics simulations of coarse-grained models of MAD2 where the structural information regarding both of its native conformations is explicitly included in terms of their native contacts in the force field used. Detailed analyses have indicated that some of the contacts within the protein play a key role in determining which folding pathway will be selected and point to a probable long-range communication between the N and the C termini of the protein that seems to control its folding. Finally, our work also provides a rationale for the experimentally observed preference of the ΔC₁₀ variant of MAD2 to exist in the open state.

The stability and dynamics of computationally designed proteins

Protein stability, dynamics and function are intricately linked. Accordingly, protein designers leverage dynamics in their designs and gain insight to their successes and failures by analyzing their proteins' dynamics. Molecular dynamics (MD) simulations are a powerful computational tool for quantifying both local and global protein dynamics. This review highlights studies where MD simulations were applied to characterize the stability and dynamics of designed proteins and where dynamics were incorporated into computational protein design. First, we discuss the structural basis underlying the extreme stability and thermostability frequently observed in computationally designed proteins. Next, we discuss examples of designed proteins, where dynamics were not explicitly accounted for in the design process, whose coordinated motions or active site dynamics, as observed by MD simulation, enhanced or detracted from their function. Many protein functions depend on sizeable or subtle conformational changes, so we finally discuss the computational design of proteins to perform a specific function that requires consideration of motion by multi-state design.

Tools for Characterizing Proteins: Circular Variance, Mutual Proximity, Chameleon Sequences, and Subsequence Propensities

For the characterization of various aspects of protein structures, four useful concepts are discussed: chameleon sequences, circular variance, mutual proximity, and a subsequence-based foldability score. These concepts were used in estimating foldability of globular, intrinsically disordered and fold-switching proteins, properties of protein-protein interfaces, quantifying sphericity, helping to improve protein-protein docking scores, and estimating the effect of mutations on stability. A conjecture about the Achilles' heel of proteins is presented as well.

OUP accepted manuscript

Summary

Motivation. Predicting the native state of a protein has long been considered a gateway problem for understanding protein folding. Recent advances in structural modeling driven by deep learning have achieved unprecedented success at predicting a protein’s crystal structure, but it is not clear if these models are learning the physics of how proteins dynamically fold into their equilibrium structure or are just accurate knowledge-based predictors of the final state.

Results. In this work, we compare the pathways generated by state-of-the-art protein structure prediction methods to experimental data about protein folding pathways. The methods considered were AlphaFold 2, RoseTTAFold, trRosetta, RaptorX, DMPfold, EVfold, SAINT2 and Rosetta. We find evidence that their simulated dynamics capture some information about the folding pathway, but their predictive ability is worse than a trivial classifier using sequence-agnostic features like chain length. The folding trajectories produced are also uncorrelated with experimental observables such as intermediate structures and the folding rate constant. These results suggest that recent advances in structure prediction do not yet provide an enhanced understanding of protein folding.

Availability. The data underlying this article are available in GitHub at https://github.com/oxpig/structure-vs-folding/

Supplementary information

Supplementary data are available at Bioinformatics online.

Reframing the Protein Folding Problem: Entropy as Organizer

It has been a long-standing conviction that a protein's native fold is selected from a vast number of conformers by the optimal constellation of enthalpically favorable interactions. In marked contrast, this Perspective introduces a different mechanism, one that emphasizes conformational entropy as the principal organizer in protein folding while proposing that the conventional view is incomplete. This mechanism stems from the realization that hydrogen bond satisfaction is a thermodynamic necessity. In particular, a backbone hydrogen bond may add little to the stability of the native state, but a completely unsatisfied backbone hydrogen bond would be dramatically destabilizing, shifting the U(nfolded) ⇌ N(ative) equilibrium far to the left. If even a single backbone polar group is satisfied by solvent when unfolded but buried and unsatisfied when folded, that energy penalty alone, approximately +5 kcal/mol, would rival almost the entire free energy of protein stabilization, typically between -5 and -15 kcal/mol under physiological conditions. Consequently, upon folding, buried backbone polar groups must form hydrogen bonds, and they do so by assembling scaffolds of α-helices and/or strands of β-sheet, the only conformers in which, with rare exception, hydrogen bond donors and acceptors are exactly balanced. In addition, only a few thousand viable scaffold topologies are possible for a typical protein domain. This thermodynamic imperative winnows the folding population by culling conformers with unsatisfied hydrogen bonds, thereby reducing the entropy cost of folding. Importantly, conformational restrictions imposed by backbone···backbone hydrogen bonding in the scaffold are sequence-independent, enabling mutation─and thus evolution─without sacrificing the structure.

Secondary-structure switch regulates the substrate binding of a YopJ family acetyltransferase

The Yersinia outer protein J (YopJ) family effectors are widely deployed through the type III secretion system by both plant and animal pathogens. As non-canonical acetyltransferases, the enzymatic activities of YopJ family effectors are allosterically activated by the eukaryote-specific ligand inositol hexaphosphate (InsP6). However, the underpinning molecular mechanism remains undefined. Here we present the crystal structure of apo-PopP2, a YopJ family member secreted by the plant pathogen Ralstonia solanacearum. Structural comparison of apo-PopP2 with the InsP6-bound PopP2 reveals a substantial conformational readjustment centered in the substrate-binding site. Combining biochemical and computational analyses, we further identify a mechanism by which the association of InsP6 with PopP2 induces an α-helix-to-β-strand transition in the catalytic core, resulting in stabilization of the substrate recognition helix in the target protein binding site. Together, our study uncovers the molecular basis governing InsP6-mediated allosteric regulation of YopJ family acetyltransferases and further expands the paradigm of fold-switching proteins.

A high-throughput predictive method for sequence-similar fold switchers

Although most experimentally characterized proteins with similar sequences assume the same folds and perform similar functions, an increasing number of exceptions is emerging. One class of exceptions comprises sequence-similar fold switchers, whose secondary structures shift from α-helix <-> β-sheet through a small number of mutations, a sequence insertion, or a deletion. Predictive methods for identifying sequence-similar fold switchers are desirable because some are associated with disease and/or can perform different functions in cells. Here, we use homology-based secondary structure predictions to identify sequence-similar fold switchers from their amino acid sequences alone. To do this, we predicted the secondary structures of sequence-similar fold switchers using three different homology-based secondary structure predictors: PSIPRED, JPred4, and SPIDER3. We found that α-helix <-> β-strand prediction discrepancies from JPred4 discriminated between the different conformations of sequence-similar fold switchers with high statistical significance (P < 1.8*10-19 ). Thus, we used these discrepancies as a classifier and found that they can often robustly discriminate between sequence-similar fold switchers and sequence-similar proteins that maintain the same folds (Matthews Correlation Coefficient of 0.82). We found that JPred4 is a more robust predictor of sequence-similar fold switchers because of (a) the curated sequence database it uses to produce multiple sequence alignments and (b) its use of sequence profiles based on Hidden Markov Models. Our results indicate that inconsistencies between JPred4 secondary structure predictions can be used to identify some sequence-similar fold switchers from their sequences alone. Thus, the negative information from inconsistent secondary structure predictions can potentially be leveraged to identify sequence-similar fold switchers from the broad base of genomic sequences.

Specific binding-induced modulation of the XCL1 metamorphic equilibrium

The metamorphic protein XCL1 switches between two distinct native structures with different functions in the human immune system. This structural interconversion requires complete rearrangement of all hydrogen bonding networks, yet fold-switching occurs spontaneously and reversibly in solution. One structure occupies the canonical α-β chemokine fold and binds XCL1's cognate G-protein coupled receptor, while the other structure occupies a dimeric, all-β fold that binds glycosaminoglycans and has antimicrobial activity. Both of these functions are important for the biologic role of XCL1 in the immune system, and each structure is approximately equally populated under near-physiologic conditions. Recent work has begun to illuminate XCL1's role in combatting infection and cancer. However, without a way to control XCL1's dynamic structural interconversion, it is difficult to study the role of XCL1 fold-switching in human health and disease. Thus, a molecular tool that can regulate the fractional population of the two XCL1 structures is needed. Here, we find by heparin affinity chromatography and NMR that an engineered XCL1 variant called CC5 can trigger a dose-dependent shift in XCL1's metamorphic equilibrium such that the receptor binding structure is depleted, and the antimicrobial structure is more heavily populated. This shift likely occurs due to formation of XCL1-CC5 heterodimers in which both protomers occupy the β-sheet structure. These findings lay the groundwork for future studies seeking to understand the functional role of XCL1 metamorphosis, as well as studies screening for a drug-like molecule that can therapeutically target XCL1 by tuning its metamorphic equilibrium. Moreover, the proof of concept presented here suggests that protein metamorphosis is druggable, opening numerous avenues for controlling biological function of metamorphic proteins by altering the population of their multiple native states.

Identification and characterization of metamorphic proteins: Current and future perspectives

Proteins that can reversibly alternate between distinctly different folds under native conditions are described as being metamorphic. The "metamorphome" is the collection of all metamorphic proteins in the proteome, but it remains unknown the extent to which the proteome is populated by this class of proteins. We propose that uncovering the metamorphome will require a synergy of computational screening of protein sequences to identify potential metamorphic behavior and validation through experimental techniques. This perspective discusses computational and experimental approaches that are currently used to predict and characterize metamorphic proteins as well as the need for developing improved methodologies. Since metamorphic proteins act as molecular switches, understanding their properties and behavior could lead to novel applications of these proteins as sensors in biological or environmental contexts.

A sequence-based method for predicting extant fold switchers that undergo α-helix ↔ β-strand transitions

Extant fold‐switching proteins remodel their secondary structures and change their functions in response to cellular stimuli, regulating biological processes and affecting human health. Despite their biological importance, these proteins remain understudied. Predictive methods are needed to expedite the process of discovering and characterizing more of these shapeshifting proteins. Most previous approaches require a solved structure or all‐atom simulations, greatly constraining their use. Here, we propose a high‐throughput sequence‐based method for predicting extant fold switchers that transition from α‐helix in one conformation to β‐strand in the other. This method leverages two previous observations: (a) α‐helix ↔ β‐strand prediction discrepancies from JPred4 are a robust predictor of fold switching, and (b) the fold‐switching regions (FSRs) of some extant fold switchers have different secondary structure propensities when expressed by themselves (isolated FSRs) than when expressed within the context of their parent protein (contextualized FSRs). Combining these two observations, we ran JPred4 on 99‐fold‐switching proteins and found strong correspondence between predicted and experimentally observed α‐helix ↔ β‐strand discrepancies. To test the overall robustness of this finding, we randomly selected regions of proteins not expected to switch folds (single‐fold proteins) and found significantly fewer predicted α‐helix ↔ β‐strand discrepancies. Combining these discrepancies with the overall percentage of predicted secondary structure, we developed a classifier to identify extant fold switchers (Matthews correlation coefficient of .71). Although this classifier had a high false‐negative rate (7/17), its false‐positive rate was very low (2/136), suggesting that it can be used to predict a subset of extant fold switchers from a multitude of available genomic sequences.

Predictable fold switching by the SARS-CoV-2 protein ORF9b

Extant fold-switching proteins remodel their secondary structures and change their functions in response to environmental stimuli. These shapeshifting proteins regulate biological processes and are associated with a number of diseases, including tuberculosis, cancer, Alzheimer's, and autoimmune disorders. Thus, predictive methods are needed to identify more fold-switching proteins, especially since all naturally occurring instances have been discovered by chance. In response to this need, two high-throughput predictive methods have recently been developed. Here we test them on ORF9b, a newly discovered fold switcher and potential therapeutic target from the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Promisingly, both methods correctly indicate that ORF9b switches folds. We then tested the same two methods on ORF9b1, the ORF9b homolog from SARS-CoV-1. Again, both methods predict that ORF9b1 switches folds, a finding consistent with experimental binding studies. Together, these results (a) demonstrate that protein fold switching can be predicted using high-throughput computational approaches and (b) suggest that fold switching might be a general characteristic of ORF9b homologs.

"Protein" no longer means what it used to

Every biologist knows that the word protein describes a group of macromolecules essential to sustain life on Earth. As biologists, we are invariably trained under a protein paradigm established since the early twentieth century. However, in recent years, the term protein unveiled itself as an euphemism to describe the overwhelming heterogeneity of these compounds. Most of our current studies are targeted on carefully selected subsets of proteins, but we tend to think and write about these as representative of the whole population. Here we discuss how seeking for universal definitions and general rules in any arbitrarily segmented study would be misleading about the conclusions. Of course, it is not our purpose to discourage the use of the word protein. Instead, we suggest to embrace the extended universe of proteins to reach a deeper understanding of their full potential, realizing that the term encompasses a group of molecules very heterogeneous in terms of size, shape, chemistry and functions, i.e. the term protein no longer means what it used to.

Thoughts on the Protein's Native State

The presence of metamorphism in the protein's native state is not yet fully understood. To shed light on this issue, we present an assessment, in terms of the amide hydrogen exchange protection factor, that aims to determine the possible existence of structural fluctuations in the native-state consistent with both the upper-bound marginal stability of proteins and the presence of metamorphism. The preliminary results enable us to conclude that the native-state metamorphism is, indeed, more probable than previously thought.

Metamorphic Protein Folding Encodes Multiple Anti-Candida Mechanisms in XCL1

Candida species cause serious infections requiring prolonged and sometimes toxic therapy. Antimicrobial proteins, such as chemokines, hold great interest as potential additions to the small number of available antifungal drugs. Metamorphic proteins reversibly switch between multiple different folded structures. XCL1 is a metamorphic, antimicrobial chemokine that interconverts between the conserved chemokine fold (an α–β monomer) and an alternate fold (an all-β dimer). Previous work has shown that human XCL1 kills C. albicans but has not assessed whether one or both XCL1 folds perform this activity. Here, we use structurally locked engineered XCL1 variants and Candida killing assays, adenylate kinase release assays, and propidium iodide uptake assays to demonstrate that both XCL1 folds kill Candida, but they do so via different mechanisms. Our results suggest that the alternate fold kills via membrane disruption, consistent with previous work, and the chemokine fold does not. XCL1 fold-switching thus provides a mechanism to regulate the XCL1 mode of antifungal killing, which could protect surrounding tissue from damage associated with fungal membrane disruption and could allow XCL1 to overcome candidal resistance by switching folds. This work provides inspiration for the future design of switchable, multifunctional antifungal therapeutics.

Metamorphic proteins: the Janus proteins of structural biology

The structural paradigm that the sequence of a protein encodes for a unique three-dimensional native fold does not acknowledge the intrinsic plasticity encapsulated in conformational free energy landscapes. Metamorphic proteins are a recently discovered class of biomolecules that illustrate this plasticity by folding into at least two distinct native state structures of comparable stability in the absence of ligands or cofactors to facilitate fold-switching. The expanding list of metamorphic proteins clearly shows that these proteins are not mere aberrations in protein evolution, but may have actually been a consequence of distinctive patterns in selection pressure such as those found in virus–host co-evolution. In this review, we describe the structure–function relationships observed in well-studied metamorphic protein systems, with specific focus on how functional residues are sequestered or exposed in the two folds of the protein. We also discuss the implications of metamorphosis for protein evolution and the efforts that are underway to predict metamorphic systems from sequence properties alone.

Inducible fold-switching as a mechanism to fibrillate pro-apoptotic BCL-2 proteins

Neurodegenerative diseases often are associated with cellular dysregulation that results in premature cell death or apoptosis. A common example is the accumulation of amyloid plaques that promotes the excessive expression of p38 mitogen-activated protein kinase. The increased abundance of this enzyme leads to mass phosphorylation and activation of a protein from the B-cell lymphoma 2 (BCL-2) family, BAX. BAX is the central regulatory protein for mitochondrial outer membrane permeabilization (MOMP), a poration process that commits cells to apoptosis by releasing death-propagating factors from the mitochondria. Recent reports identify a naturally occurring peptide, Humanin (HN), that could block amyloid-beta-associated neuronal apoptosis by interacting with BCL-2 proteins. We recently showed humanin interaction leads to the amyloid-like fibrillation of BAX and a second BCL-2 family member, BID. We proposed this as a novel anti-apoptotic mechanism that inhibits pro-apoptotic BCL-2 proteins from initiating MOMP by sequestering them into fibrils, a heretofore unprecedented phenomenon that involves refolding globular BCL-2 proteins rapidly into fibrils where they undergo significant alpha-helix to beta-sheet fold-switching. Here we seek to further characterize the fibrillation and fold-switch in conditions that are known to induce amyloid fibrillation.

Dynamical spectroscopy and microscopy of proteins in cells

With a strong understanding of how proteins fold in hand, it is now possible to ask how in-cell environments modulate their folding, binding and function. Studies accessing fast (ns to s) in-cell dynamics have accelerated over the past few years through a combination of in-cell NMR spectroscopy and time-resolved fluorescence microscopies. Here, we discuss this recent work and the emerging picture of protein surfaces as not just hydrophilic coats interfacing the solvent to the protein's core and functional regions, but as critical components in cells controlling protein mobility, function and communication with post-translational modifications.

High resolution ensemble description of metamorphic and intrinsically disordered proteins using an efficient hybrid parallel tempering scheme

Mapping free energy landscapes of complex multi-funneled metamorphic proteins and weakly-funneled intrinsically disordered proteins (IDPs) remains challenging. While rare-event sampling molecular dynamics simulations can be useful, they often need to either impose restraints or reweigh the generated data to match experiments. Here, we present a parallel-tempering method that takes advantage of accelerated water dynamics and allows efficient and accurate conformational sampling across a wide variety of proteins. We demonstrate the improved sampling efficiency by benchmarking against standard model systems such as alanine di-peptide, TRP-cage and β-hairpin. The method successfully scales to large metamorphic proteins such as RFA-H and to highly disordered IDPs such as Histatin-5. Across the diverse proteins, the calculated ensemble averages match well with the NMR, SAXS and other biophysical experiments without the need to reweigh. By allowing accurate sampling across different landscapes, the method opens doors for sampling free energy landscape of complex uncharted proteins.

The C-terminal domain of transcription factor RfaH: Folding, fold switching and energy landscape

We simulate the folding and fold switching of the C-terminal domain (CTD) of the transcription factor RfaH using an all-atom physics-based model augmented with a dual-basin structure-based potential energy term. We show that this hybrid model captures the essential thermodynamic behavior of this metamorphic domain, that is, a change in the global free energy minimum from an α-helical hairpin to a 5-stranded β-barrel upon the dissociation of the CTD from the rest of the protein. Using Monte Carlo sampling techniques, we then analyze the energy landscape of the CTD in terms of progress variables for folding toward the two folds. We find that, below the folding transition, the energy landscape is characterized by a single, dominant funnel to the native β-barrel structure. The absence of a deep funnel to the α-helical hairpin state reflects a negligible population of this fold for the isolated CTD. We observe, however, a higher α-helix structure content in the unfolded state compared to results from a similar but fold switch-incompetent version of our model. Moreover, in folding simulations started from an extended chain conformation we find transiently formed α-helical structure, occurring early in the process and disappearing as the chain progresses toward the thermally stable β-barrel state.

Evolution of fold switching in a metamorphic protein

Metamorphic proteins switch between different folds, defying the protein folding paradigm. It is unclear how fold switching arises during evolution. With ancestral reconstruction and nuclear magnetic resonance, we studied the evolution of the metamorphic human protein XCL1, which has two distinct folds with different functions, making it an unusual member of the chemokine family, whose members generally adopt one conserved fold. XCL1 evolved from an ancestor with the chemokine fold. Evolution of a dimer interface, changes in structural constraints and molecular strain, and alteration of intramolecular protein contacts drove the evolution of metamorphosis. Then, XCL1 likely evolved to preferentially populate the noncanonical fold before reaching its modern-day near-equal population of folds. These discoveries illuminate how one sequence has evolved to encode multiple structures, revealing principles for protein design and engineering.

Single molecule force spectroscopy reveals the context dependent folding pathway of the C-terminal fragment of Top7

Top7 is a de novo designed protein with atomic level accuracy and shows a folded structure not found in nature. Previous studies showed that the folding of Top7 is not cooperative and involves various folding intermediate states. In addition, various fragments of Top7 were found to fold on their own in isolation. These features displayed by Top7 are distinct from those of naturally occurring proteins of a similar size and suggest a rough folding energy landscape. However, it remains unknown if and how the intra-polypeptide chain interactions among the neighboring sequences of Top7 affect the folding of these Top7 fragments. Here we used single-molecule optical tweezers to investigate the folding–unfolding pathways of full length Top7 as well as its C-terminal fragment (CFr) in different sequence environments. Our results showed that the mechanical folding of Top7 involves an intermediate state that likely involves non-native interactions/structure. More importantly, we found that the folding of CFr is entirely dependent upon its sequence context in which it is located. When in isolation, CFr indeed folds into a cooperative structure showing near-equilibrium unfolding–folding transitions at ∼6.5 pN in OT experiments. However, CFr loses its autonomous cooperative folding ability and displays a folding pathway that is dependent on its interactions with its neighboring sequence/structure. This context-dependent folding dynamics and pathway of CFr are distinct from those of naturally occurring proteins and highlight the critical importance of intra-chain interactions in shaping the overall energy landscape and the folding pathway of Top7. These new insights may have important implications on the de novo design of proteins.

Optical tweezers experiments reveal that the folding of the C-terminal fragment of Top7 (cFr) is context-dependent. Depending on its neighboring sequence, cFr shows very different folding pathways and folding kinetics.

Functional and Regulatory Roles of Fold-Switching Proteins

Fold-switching proteins respond to cellular stimuli by remodeling their secondary structures and changing their functions. Whereas several previous reviews have focused on various structural, physical-chemical, and evolutionary aspects of this newly emerging class of proteins, this minireview focuses on how fold switching modulates protein function and regulates biological processes. It first compares and contrasts fold switchers with other known types of proteins. Second, it presents examples of how various proteins can change their functions through fold switching. Third, it demonstrates that fold switchers can regulate biological processes by discussing two proteins, RfaH and KaiB, whose dramatic secondary structure remodeling events directly affect gene expression and a circadian clock, respectively. Finally, this minireview discusses how the field of protein fold switching might advance.

Exploring the sequence fitness landscape of a bridge between protein folds

Most foldable protein sequences adopt only a single native fold. Recent protein design studies have, however, created protein sequences which fold into different structures apon changes of environment, or single point mutation, the best characterized example being the switch between the folds of the GA and GB binding domains of streptococcal protein G. To obtain further insight into the design of sequences which can switch folds, we have used a computational model for the fitness landscape of a single fold, built from the observed sequence variation of protein homologues. We have recently shown that such coevolutionary models can be used to design novel foldable sequences. By appropriately combining two of these models to describe the joint fitness landscape of GA and GB, we are able to describe the propensity of a given sequence for each of the two folds. We have successfully tested the combined model against the known series of designed GA/GB hybrids. Using Monte Carlo simulations on this landscape, we are able to identify pathways of mutations connecting the two folds. In the absence of a requirement for domain stability, the most frequent paths go via sequences in which neither domain is stably folded, reminiscent of the propensity for certain intrinsically disordered proteins to fold into different structures according to context. Even if the folded state is required to be stable, we find that there is nonetheless still a wide range of sequences which are close to the transition region and therefore likely fold switches, consistent with recent estimates that fold switching may be more widespread than had been thought.

While most proteins self-assemble (or “fold”) to a unique three-dimensional structure, a few have been identified that can fold into two distinct structures. These so-called “metamorphic” proteins that can switch folds have attracted a lot of recent interest, and it has been suggested that they may be much more widespread than currently appreciated. We have developed a computational model that captures the propensity of a given protein sequence to fold into either one of two specific structures (GA and GB), in order to investigate which sequences are able to fold to both GA and GB (“switch sequences”), versus just one of them. Our model predicts that there is a large number of switch sequences that could fold into both structures, but also that the most likely such sequences are those for which the folded structures have low stability, in agreement with available experimental data. This also suggests that intrinsically disordered proteins which can fold into different structures on binding may provide an evolutionary path in sequence space between protein folds.

Structural fluctuations and mechanical stabilities of the metamorphic protein RfaH

RfaH is a compact two-domain bacterial transcription factor that functions both as a regulator of transcription and an enhancer of translation. Underpinning the dual functional roles of RfaH is a partial but dramatic fold switch, which completely transforms the ~50-amino acid C-terminal domain (CTD) from an all-α state to an all-β state. The fold switch of the CTD occurs when RfaH binds to RNA polymerase (RNAP), however, the details of how this structural transformation is triggered is not well understood. Here we use all-atom Monte Carlo simulations to characterize structural fluctuations and mechanical stability properties of the full-length RfaH and the CTD as an isolated fragment. In agreement with experiments, we find that interdomain contacts are crucial for maintaining a stable, all-α CTD in free RfaH. To probe mechanical properties, we use pulling simulations to measure the work required to inflict local deformations at different positions along the chain. The resulting mechanical stability profile reveals that free RfaH can be divided into a "rigid" part and a "soft" part, with a boundary that nearly coincides with the boundary between the two domains. We discuss the potential role of this feature for how fold switching may be triggered by interaction with RNAP.

Drugs, host proteins and viral proteins: how their promiscuities shape antiviral design

The reciprocal nature of drug specificity and target specificity implies that the same is true for their respective promiscuities. Protein promiscuity has two broadly different types of footprint in drug design. The first is relaxed specificity of binding sites for substrates, inhibitors, effectors or cofactors. The second involves protein-protein interactions of regulatory processes such as signal transduction and transcription, and here protein intrinsic disorder plays an important role. Both viruses and host cells exploit intrinsic disorder for their survival, as do the design and discovery programs for antivirals. Drug action, strictly speaking, always relies upon promiscuous activity, with drug promiscuity enlarging its scope. Drug repurposing searches for additional promiscuity on the part of both the drug and the target in the host. Understanding the subtle nuances of these promiscuities is critical in the design of novel and more effective antivirals.

Sequence-Based Prediction of Metamorphic Behavior in Proteins

An increasing number of proteins have been demonstrated in recent years to adopt multiple three-dimensional folds with different functions. These metamorphic proteins are characterized by having two or more folds with significant differences in their secondary structure, in which each fold is stabilized by a distinct local environment. So far, ∼90 metamorphic proteins have been identified in the Protein Databank, but we and others hypothesize that a far greater number of metamorphic proteins remain undiscovered. In this work, we introduce a computational model to predict metamorphic behavior in proteins using only knowledge of the sequence. In this model, secondary structure prediction programs are used to calculate diversity indices, which are measures of uncertainty in predicted secondary structure at each position in the sequence; these are then used to assign protein sequences as likely to be metamorphic versus monomorphic (i.e., having just one fold). We constructed a reference data set to train our classification method, which includes a novel compilation of 136 likely monomorphic proteins and a set of 201 metamorphic protein structures taken from the literature. Our model is able to classify proteins as metamorphic versus monomorphic with a Matthews correlation coefficient of ∼0.36 and true positive/true negative rates of ∼65%/80%, suggesting that it is possible to predict metamorphic behavior in proteins using only sequence information.

Foldability and chameleon propensity of fold-switching protein sequences

It has been shown recently by Porter & Looger that a significant number of proteins exist that can form more than one stable fold. This note examines the sequences of these fold-switching proteins by (a) calculating their foldability scores recently introduced by the present author and (b) comparing the propensity of chameleon sequences in fold switchers and in non fold switchers. It has been found that the average foldability score of the fold switchers indicates weaker foldability. As for the propensity of chameleon sequences of length 5 to 7 it was found, somewhat surprisingly, that there is only a very small difference between the fold switchers and the non fold switchers. Furthermore, when looking at amino acid propensities, for several amino acids there was even an opposing trend in the deviation of their propensities from the overall amino acid propensities.

Carbon nanoparticles induce endoplasmic reticulum stress around blood vessels with accumulation of misfolded proteins in the developing brain of offspring

Nano-particulate air pollution threatens developing brains and is epidemiologically related to neurodegenerative diseases involving deposition of misfolded proteins. However, the mechanism underlying developmental neurotoxicity by nanoparticles remains unknown. Here, we report that maternal exposure to low doses of carbon black nanoparticle (CB-NP) induces endoplasmic reticulum (ER) stress associated with accumulation of misfolded proteins. Notably, offspring specifically showed high induction of ER stress in perivascular macrophages and reactive astrocytes only around brain blood vessels, along with accumulation of β-sheet-rich proteins regarded as misfolded proteins. Our results suggest that maternal CB-NP exposure induced ER stress in PVMs and reactive astrocytes around blood vessels in the brain of offspring in mice. The induction of ER stress accompanied by the perivascular accumulation of misfolded proteins is likely to be associated with perivascular abnormalities and neurodegeneration, and development of neurodegenerative diseases related to particulate air pollution.

Unveiling the activation dynamics of a fold-switch bacterial glycosyltransferase by 19F NMR

Fold-switch pathways remodel the secondary structure topology of proteins in response to the cellular environment. It is a major challenge to understand the dynamics of these folding processes. Here, we conducted an in-depth analysis of the α-helix–to–β-strand and β-strand–to–α-helix transitions and domain motions displayed by the essential mannosyltransferase PimA from mycobacteria. Using ¹⁹F NMR, we identified four functionally relevant states of PimA that coexist in dynamic equilibria on millisecond-to-second timescales in solution. We discovered that fold-switching is a slow process, on the order of seconds, whereas domain motions occur simultaneously but are substantially faster, on the order of milliseconds. Strikingly, the addition of substrate accelerated the fold-switching dynamics of PimA. We propose a model in which the fold-switching dynamics constitute a mechanism for PimA activation.

Structure of the Hydrophobic Core Determines the 3D Protein Structure-Verification by Single Mutation Proteins

Four de novo proteins differing in single mutation positions, with a chain length of 56 amino acids, represent diverse 3D structures: monomeric 3α and 4β + α folds. The reason for this diversity is seen in the different structure of the hydrophobic core as a result of synergy leading to the generation of a system in which the polypeptide chain as a whole participates. On the basis of the fuzzy oil drop model, where the structure of the hydrophobic core is expressed by means of the hydrophobic distribution function in the form of a 3D Gaussian distribution, it has been shown that the composition of the hydrophobic core in these two structural forms is different. In addition, the use of a model to determine the structure of the early intermediate in the folding process allows to indicate differences in the polypeptide chain geometry, which, combined with the construction of a common hydrophobic nucleus as an effect of specific synergy, may indicate the reason for the diversity of the folding process of the polypeptide chain. The results indicate the need to take into account the presence of an external force field originating from the water environment and that its active impact on the formation of a hydrophobic core whose participation in the stabilization of the tertiary structure is fundamental.

Length-Dependent Structural Transformations of Huntingtin PolyQ Domain Upon Binding to 2D-Nanomaterials

There is a strong negative correlation between the polyglutamine (polyQ) domain length (Q-length) in the intrinsically disordered Huntingtin protein (Htt) exon-1 and the age of onset of Huntington's disease (HD). PolyQ of Q-length longer than 40 has the propensity of forming very compact aggregate structures, leading to HD at full penetrance. Recent advances in nanobiotechnology provided a new platform for the development of novel diagnosis and therapeutics. Here, we explore the possibility of utilizing 2D-nanomaterials to inhibit the formation of supercompact polyQ structures through the so-called “folding-upon-binding” where the protein structure is dependent on the binding substrate. Using molecular dynamics simulations, we characterize two polyQ peptides with Q-length of 22 (Q22, normal length) and 46 (Q46, typical length causing HD) binding to both graphene and molybdenum disulfide (MoS₂) nanosheets, which have been applied as antibacterial or anticancer agents. Upon binding, Q22 unfolds and elongates on both grapheme and MoS₂ surfaces, regardless of its initial conformation, with graphene showing slightly stronger effect. In contrast, initially collapsed Q46 remains mostly collapsed within our simulation time on both nanosheets even though they do provide some “stretching” to Q46 as well. Further analyses indicate that the hydrophobic nature of graphene/MoS₂ promotes the stretching of polyQ on nanosheets. However, there is strong competition with the intra-polyQ interactions (mainly internal hydrogen bonds) leading to the disparate folding/binding behaviors of Q22 and Q46. Our results present distinct Q-length specific behavior of the polyQ domain upon binding to two types of 2D-nanomaterials which holds clinical relevance for Huntington's disease.

Are RNA networks scale-free?

A network is scale-free if its connectivity density function is proportional to a power-law distribution. It has been suggested that scale-free networks may provide an explanation for the robustness observed in certain physical and biological phenomena, since the presence of a few highly connected hub nodes and a large number of small-degree nodes may provide alternate paths between any two nodes on average—such robustness has been suggested in studies of metabolic networks, gene interaction networks and protein folding. A theoretical justification for why many networks appear to be scale-free has been provided by Barabási and Albert, who argue that expanding networks, in which new nodes are preferentially attached to highly connected nodes, tend to be scale-free. In this paper, we provide the first efficient algorithm to compute the connectivity density function for the ensemble of all homopolymer secondary structures of a user-specified length—a highly nontrivial result, since the exponential size of such networks precludes their enumeration. Since existent power-law fitting software, such as powerlaw, cannot be used to determine a power-law fit for our exponentially large RNA connectivity data, we also implement efficient code to compute the maximum likelihood estimate for the power-law scaling factor and associated Kolmogorov–Smirnov p value. Hypothesis tests strongly indicate that homopolymer RNA secondary structure networks are not scale-free; moreover, this appears to be the case for real (non-homopolymer) RNA networks.

Engineering protein assemblies with allosteric control via monomer fold-switching

The macromolecular machines of life use allosteric control to self-assemble, dissociate and change shape in response to signals. Despite enormous interest, the design of nanoscale allosteric assemblies has proven tremendously challenging. Here we present a proof of concept of allosteric assembly in which an engineered fold switch on the protein monomer triggers or blocks assembly. Our design is based on the hyper-stable, naturally monomeric protein CI2, a paradigm of simple two-state folding, and the toroidal arrangement with 6-fold symmetry that it only adopts in crystalline form. We engineer CI2 to enable a switch between the native and an alternate, latent fold that self-assembles onto hexagonal toroidal particles by exposing a favorable inter-monomer interface. The assembly is controlled on demand via the competing effects of temperature and a designed short peptide. These findings unveil a remarkable potential for structural metamorphosis in proteins and demonstrate key principles for engineering protein-based nanomachinery.

The design of protein assemblies is a major thrust for biomolecular engineering and nanobiotechnology. Here the authors demonstrate a general mechanism for designing allosteric macromolecular assemblies and showcase a proof of concept for engineered allosteric protein assembly.

Probing transient excited states of the bacterial cell division regulator MinE by relaxation dispersion NMR spectroscopy

Bacterial MinD and MinE form a standing oscillatory wave which positions the cell division inhibitor MinC, that binds MinD, everywhere on the membrane except at the midpoint of the cell, ensuring midcell positioning of the cytokinetic septum. During this process MinE undergoes fold switching as it interacts with different partners. We explore the exchange dynamics between major and excited states of the MinE dimer in 3 forms using ¹⁵N relaxation dispersion NMR: the full-length protein (6-stranded β-sheet sandwiched between 4 helices) representing the resting state; a 10-residue N-terminal deletion (Δ10) mimicking the membrane-binding competent state where the N-terminal helix is detached to interact with membrane; and N-terminal deletions of either 30 (Δ30) or 10 residues with an I24N mutation (Δ10/I24N), in which the β1-strands at the dimer interface are extruded and available to bind MinD, leaving behind a 4-stranded β-sheet. Full-length MinE samples 2 "excited" states: The first is similar to a full-length/Δ10 heterodimer; the second, also sampled by Δ10, is either similar to or well along the pathway toward the 4-stranded β-sheet form. Both Δ30 and Δ10/I24N sample 2 excited species: The first may involve destabilization of the β3- and β3'-strands at the dimer interface; changes in the second are more extensive, involving further disruption of secondary structure, possibly representing an ensemble of states on the pathway toward restoration of the resting state. The quantitative information on MinE conformational dynamics involving these excited states is crucial for understanding the oscillation pattern self-organization by MinD-MinE interaction dynamics on the membrane.

Turncoat Polypeptides: We Adapt to Our Environment

A common interpretation of Anfinsen's hypothesis states that one amino acid sequence should fold into a single, native, ordered state, or a highly similar set thereof, coinciding with the global minimum in the folding-energy landscape, which, in turn, is responsible for the function of the protein. However, this classical view is challenged by many proteins and peptide sequences, which can adopt exchangeable, significantly dissimilar conformations that even fulfill different biological roles. The similarities and differences of concepts related to these proteins, mainly chameleon sequences, metamorphic proteins, and switch peptides, which are all denoted herein "turncoat" polypeptides, are reviewed. As well as adding a twist to the conventional view of protein folding, the lack of structural definition adds clear versatility to the activity of proteins and can be used as a tool for protein design and further application in biotechnology and biomedicine.

Conformational heterogeneity in apo and drug-bound structures of Toxoplasma gondii prolyl-tRNA synthetase

Prolyl-tRNA synthetase (PRS) is a member of the aminoacyl-tRNA synthetase family that drives protein translation in cells. The apicomplexan PRSs are validated targets of febrifugine (FF) and its halogenated derivative halofuginone (HF). PRSs are of great interest for drug development against Plasmodium falciparum and Toxoplasma gondii. In this study, structures of apo and FF-bound T. gondii (TgPRS) are revealed and the dynamic nature of the conformational changes that occur upon FF binding is unraveled. In addition, this study highlights significant conformational plasticity within two different crystal structures of apo PRSs but not within drug-bound PRSs. The apo PRSs exist in multi-conformational states and manifest pseudo-dimeric structures. In contrast, when FF is bound the PRS dimer adopts a highly symmetrical architecture. It is shown that TgPRS does not display extant fold switching, in contrast to P. falciparum PRS, despite having over 65% sequence identity. Finally, structure-comparison analyses suggest the utility of r.m.s.d. per residue (r.m.s.d.^/res) as a robust tool to detect structural alterations even when the r.m.s.d. is low. Apo TgPRS reveals FF/HF-induced rigidity and this work has implications for drug-design studies that rely on the apo structures of target proteins.

DistAA: Database of amino acid distances in proteins and web application for statistical review of distances

Three-dimensional structure of a protein chain is determined by its amino acid interactions. One approach to the analysis of amino acid interactions refers to geometric distances of amino acid pairs in polypeptide chains. For a detailed analysis of the amino acid distances, the database with three types of amino acid distances in a set of chains was created. Web application Distances of Amino Acids has also been developed to enable scientists to explore interactions of amino acids with different properties based on distances stored in the database. Web application calculates and displays descriptive statistics and graphs of amino acid pair distances with selected properties, such as geometric distance threshold, corresponding SCOP class of proteins and secondary structure types. In addition to the analysis of pre-calculated distances stored in the database, the amino acid distances of a single protein with the specified PDB identifier can also be analyzed. The web application is available at http://andromeda.matf.bg.ac.rs/aadis_dynamic/.

A topology-based investigation of protein interaction sites using Hydrophobic Cluster Analysis

Hydrophobic clusters, as defined by Hydrophobic Cluster Analysis (HCA), are conditioned binary patterns, made of hydrophobic and non-hydrophobic positions, whose limits fit well those of regular secondary structures. They were proved to be useful for predicting secondary structures in proteins from the only information of a single amino acid sequence and have permitted to assess, in a comprehensive way, the leading role of binary patterns in secondary structure preference towards a particular state. Here, we considered the available experimental 3D structures of protein globular domains to enlarge our previously reported hydrophobic cluster database (HCDB), almost doubling the number of hydrophobic cluster species (each species being defined by a unique binary pattern) that represent the most frequent structural bricks encountered within protein globular domains. We then used this updated HCDB to show that the hydrophobic amino acids of discordant clusters, i.e. those less abundant clusters for which the observed secondary structure is in disagreement with the binary pattern preference of the species to which they belong, are more exposed to solvent and are more involved in protein interfaces than the hydrophobic amino acids of concordant clusters. As amino acid composition differs between concordant/discordant clusters, considering binary patterns may be used to gain novel insights into key features of protein globular domain cores and surfaces. It can also provide useful information on possible conformational plasticity, including disorder to order transitions.

The DNA walk and its demonstration of deterministic chaos-relevance to genomic alterations in lung cancer

MOTIVATION

Advancements in cancer genetics have facilitated the development of therapies with actionable mutations. Although mutated genes have been studied extensively, their chaotic behavior has not been appreciated. Thus, in contrast to naïve DNA, mutated DNA sequences can display characteristics of unpredictability and sensitivity to the initial conditions that may be dictated by the environment, expression patterns and presence of other genomic alterations. Employing a DNA walk as a form of 2D analysis of the nucleotide sequence, we demonstrate that chaotic behavior in the sequence of a mutated gene can be predicted.

RESULTS

Using fractal analysis for these DNA walks, we have determined the complexity and nucleotide variance of commonly observed mutated genes in non-small cell lung cancer, and their wild-type counterparts. DNA walks for wild-type genes demonstrate varying levels of chaos, with BRAF, NTRK1 and MET exhibiting greater levels of chaos than KRAS, paxillin and EGFR. Analyzing changes in chaotic properties, such as changes in periodicity and linearity, reveal that while deletion mutations indicate a notable disruption in fractal 'self-similarity', fusion mutations demonstrate bifurcations between the two genes. Our results suggest that the fractals generated by DNA walks can yield important insights into potential consequences of these mutated genes.

AVAILABILITY AND IMPLEMENTATION

Introduction to Turtle graphics in Python is an open source article on learning to develop a script for Turtle graphics in Python, freely available on the web at https://docs.python.org/2/library/turtle.html. cDNA sequences were obtained through NCBI RefSeq database, an open source database that contains information on a large array of genes, such as their nucleotide and amino acid sequences, freely available at https://www.ncbi.nlm.nih.gov/refseq/. FracLac plugin for Fractal analysis in ImageJ is an open source plugin for the ImageJ program to perform fractal analysis, free to download at https://imagej.nih.gov/ij/plugins/fraclac/FLHelp/Introduction.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Inaccurate secondary structure predictions often indicate protein fold switching

Although most proteins conform to the classical one‐structure/one‐function paradigm, an increasing number of proteins with dual structures and functions have been discovered. In response to cellular stimuli, such proteins undergo structural changes sufficiently dramatic to remodel even their secondary structures and domain organization. This “fold‐switching” capability fosters protein multi‐functionality, enabling cells to establish tight control over various biochemical processes. Accurate predictions of fold‐switching proteins could both suggest underlying mechanisms for uncharacterized biological processes and reveal potential drug targets. Recently, we developed a prediction method for fold‐switching proteins using structure‐based thermodynamic calculations and discrepancies between predicted and experimentally determined protein secondary structure (Porter and Looger, Proc Natl Acad Sci U S A 2018; 115:5968–5973). Here we seek to leverage the negative information found in these secondary structure prediction discrepancies. To do this, we quantified secondary structure prediction accuracies of 192 known fold‐switching regions (FSRs) within solved protein structures found in the Protein Data Bank (PDB). We find that the secondary structure prediction accuracies for these FSRs vary widely. Inaccurate secondary structure predictions are strongly associated with fold‐switching proteins compared to equally long segments of non‐fold‐switching proteins selected at random. These inaccurate predictions are enriched in helix‐to‐strand and strand‐to‐coil discrepancies. Finally, we find that most proteins with inaccurate secondary structure predictions are underrepresented in the PDB compared with their alternatively folded cognates, suggesting that unequal representation of fold‐switching conformers within the PDB could be an important cause of inaccurate secondary structure predictions. These results demonstrate that inconsistent secondary structure predictions can serve as a useful preliminary marker of fold switching.

Protein ensembles link genotype to phenotype

Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype-phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function.

HIV-1 Reverse Transcriptase: A Metamorphic Protein with Three Stable States

There has been a steadily increasing appreciation of the fact that the relationship between protein sequence and structure is often sufficiently ambiguous to allow a single sequence to adopt alternative, stable folds. Living organisms have been able to utilize such metamorphic proteins in remarkable and unanticipated ways. HIV-1 reverse transcriptase is among the earliest such proteins identified and remains a unique example in which a functional heterodimer contains two, alternatively folded polymerase domains. Structural characterization of the p66 precursor protein combined with NMR spectroscopic and molecular modeling studies have provided insights into the factors underlying the metamorphic transition and the subunit-specific programmed unfolding step required to expose the protease cleavage site within the ribonuclease H domain, supporting the conversion of the p66/p66' precursor into the mature p66/p51 heterodimer.

Increased sequence hydrophobicity reduces conformational specificity: A mutational case study of the Arc repressor protein

The amino-acid sequences of soluble, globular proteins must have hydrophobic residues to form a stable core, but excess sequence hydrophobicity can lead to loss of native state conformational specificity and aggregation. Previous studies of polar-to-hydrophobic mutations in the β-sheet of the Arc repressor dimer showed that a single substitution at position 11 (N11L) leads to population of an alternate dimeric fold in which the β-sheet is replaced by helix. Two additional hydrophobic mutations at positions 9 and 13 (Q9V and R13V) lead to population of a differently folded octamer along with both dimeric folds. Here we conduct a comprehensive study of the sequence determinants of this progressive loss of fold specificity. We find that the alternate dimer-fold specifically results from the N11L substitution and is not promoted by other hydrophobic substitutions in the β-sheet. We also find that three highly hydrophobic substitutions at positions 9, 11, and 13 are necessary and sufficient for oligomer formation, but the oligomer size depends on the identity of the hydrophobic residue in question. The hydrophobic substitutions increase thermal stability, illustrating how increased hydrophobicity can increase folding stability even as it degrades conformational specificity. The oligomeric variants are predicted to be aggregation-prone but may be hindered from doing so by proline residues that flank the β-sheet region. Loss of conformational specificity due to increased hydrophobicity can manifest itself at any level of structure, depending upon the specific mutations and the context in which they occur.

Structural metamorphism and polymorphism in proteins on the brink of thermodynamic stability

The classical view of the structure-function paradigm advanced by Anfinsen in the 1960s is that a protein's function is inextricably linked to its three-dimensional structure and is encrypted in its amino acid sequence. However, it is now known that a significant fraction of the proteome consists of intrinsically disordered proteins (IDPs). These proteins populate a polymorphic ensemble of conformations rather than a unique structure but are still capable of performing biological functions. At the boundary, between well-ordered and inherently disordered states are proteins that are on the brink of stability, either weakly stable ordered systems or disordered but on the verge of being stable. In such marginal states, even relatively minor changes can significantly alter the energy landscape, leading to large-scale conformational remodeling. Some proteins on the edge of stability are metamorphic, with the capacity to switch from one fold topology to another in response to an environmental trigger (e.g., pH, temperature/salt, redox). Many IDPs, on the other hand, are marginally unstable such that small perturbations (e.g., phosphorylation, ligands) tip the balance over to a range of ordered, partially ordered, or even more disordered states. In general, the structural transitions described by metamorphic fold switches and polymorphic IDPs possess a number of common features including low or diminished stability, large-scale conformational changes, critical disordered regions, latent or attenuated binding sites, and expansion of function. We suggest that these transitions are, therefore, conceptually and mechanistically analogous, representing adjacent regions in the continuum of order/disorder transitions.