Evolution of fold switching in a metamorphic protein

Conformational Plasticity in dsRNA-Binding Domains Drives Functional Divergence in RNA Recognition

The functional specificity of proteins is often attributed to their sequence and structural homology while frequently neglecting the underlying conformational dynamics occurring at different time scales that can profoundly impact biological consequences. Using 15N-CEST NMR and RDC-corrected metainference molecular dynamics simulations, here, we reveal differential substrate recognition mechanisms in two dsRNA-binding domain (dsRBD) paralogs, DRB2D1 and DRB3D1. Despite their nearly identical solution structures and conserved dsRNA interaction interfaces, DRB3D1 demonstrates structural plasticity that enables it to recognize conformationally flexible dsRNA, a feature notably absent in the more rigid DRB2D1. We present the pivotal role of intrinsic structural dynamics in driving functional divergence and provide insights into the mechanisms that govern specificity in dsRBD:dsRNA interactions. Importantly, our combined experimental and computational approach captures a cluster of intermediate conformations, complementing conventional methods to resolve the dominant ground state and sparsely populated excited states.

Unraveling structural transitions and kinetics along the fold-switching pathway of the RfaH C-terminal domain using exchange-based NMR

The bacterial transcriptional regulator RfaH comprises structurally and functionally distinct N- (NTD) and C- (CTD) terminal domains. The latter switches from a helical hairpin packed against the NTD to a five-stranded β-roll upon displacement by RNA polymerase binding. Here, we use exchange-based NMR to probe fold-switching intermediates sampled by the isolated CTD. In addition to the predominant (~76 to 77%), semistable β-roll conformation (state A), we identify four structurally and kinetically distinct states: A', B, B', and B″. State B is NMR observable with an occupancy of ~23%, exchanges slowly (τex ~ 300 ms) with the major A species, and comprises a largely unfolded ensemble with transient occupancy of helical (α5*) and β-hairpin (β1*/β2*) elements. Backbone chemical shift-based structure predictions using the program CS-ROSETTA suggest that the two transient structural elements within the B state may interact with one another to form a semicompact structure. A' (~0.35%) is an off-pathway state that exchanges rapidly (τex ~ 1 ms) with state A and likely entails a minor localized conformational change in the β1/β2 loop. State B' (~0.3%) exchanges rapidly (τex ~ 1.2 ms) with state B and exhibits downfield 15N backbone shifts (relative to B) in the α5* region indicative of reduced helicity. Finally state B″ (~0.05%) exchanges rapidly (τex ~ 0.8 to 1 ms) with either B' (linear model) or B (branched model), displays significant differences in absolute 15N chemical shift from states B and B', and likely represents a further intermediate with increased helicity along the fold-switching pathway.

Precise modulation of protein refolding by rationally designed covalent organic frameworks

Precisely regulating protein conformation (folding) for biomanufacturing and biomedicine is of great significance but remains challenging. In this work, we innovate a covalent organic framework (COF)-directed protein refolding strategy to modulate protein conformation by rationally designed covalent organic frameworks with adapted pore structures and customizable microenvironments. The conformation of denatured protein can be efficiently recovered through a simple one-step approach using covalent organic framework treatment in aqueous or buffer solutions. This strategy demonstrates high generality that can be applied to various proteins (for example, lysozyme, glucose oxidase, trypsin, nattokinase, and papain) and diverse covalent organic frameworks. An in-depth investigation of the refolding mechanism reveals that pore size and microenvironments such as hydrophobicity, π-π conjugation, and hydrogen bonding are critical to regulating protein conformation. Furthermore, we use this covalent organic framework platform to build up solid-phase columns for continuous protein recovery and achieved a ~ 100% refolding yield and excellent recycling performance (30 cycles), enabling an integrated process for the extracting and refolding denatured proteins (such as the harvest of protein in inclusion bodies). This study creates a highly efficient and customizable covalent organic framework platform for precisely regulating proteins refolding and enhancing their performance, opening up a new avenue for advanced protein manufacturing.

Statistical Thermodynamics of the Protein Ensemble: Mediating Function and Evolution

The growing appreciation of native state conformational fluctuations mediating protein function calls for critical reevaluation of protein evolution and adaptation. If proteins are ensembles, does nature select solely for ground state structure, or are conformational equilibria between functional states also conserved? If so, what is the mechanism and how can it be measured? Addressing these fundamental questions, we review our investigation into the role of local unfolding fluctuations in the native state ensembles of proteins. We describe the functional importance of these ubiquitous fluctuations, as revealed through studies of adenylate kinase. We then summarize elucidation of thermodynamic organizing principles, which culminate in a quantitative probe for evolutionary conservation of protein energetics. Finally, we show that these principles are predictive of sequence compatibility for multiple folds, providing a unique thermodynamic perspective on metamorphic proteins. These research areas demonstrate that the locally unfolded ensemble is an emerging, important mechanism of protein evolution.

Green tea polyphenol EGCG acts differentially on end-stage amyloid polymorphs of α-synuclein formed in different polyol osmolytes

Synucleinopathies are heterogenous group of disorders characterized by α-synuclein amyloid aggregates in the nervous system. Different synucleinopathy clinical subtypes are encoded by structurally diverse α-synuclein amyloid polymorphs referred to as 'strains'. The underlying structural differences between polymorphs can potentially hamper the drug design against synucleinopathies. Polyphenolic compounds like EGCG have shown promise in inhibiting and remodeling of α-synuclein amyloid aggregates, but their effects on different polymorphs are not well-studied. The cellular environment is one factor contributing to the heterogeneity in the amyloid landscape. Herein, we generated diverse polymorphs of α-synuclein by fine-tuning its aggregation using different polyol osmolytes, varying in their physicochemical properties. These osmolytes act as globular protein stabilizers and conformational modulators of intrinsically disordered proteins. While the buffer control α-synuclein aggregates were evenly dispersed, the polyol-induced aggregate solutions contained a heterogeneous mixture of co-existing polymorphs, as evidenced by AFM and TEM measurements. The polyol-induced aggregated solutions consisted of a mixture of both fibrillar and nonfibrillar cross-β-rich species. Using various spectroscopic tools, we observed differences in the structures of osmolyte-induced polymorphic aggregates. We incubated these aggregates with EGCG and observed its disparate action over polymorphs wherein the treated species were either disintegrated or structurally altered. Contrary to previous reports, all EGCG-treated polymorphs were β-sheet-rich and seeding-competent. Our findings are relevant in assessing the efficacy of polyphenolic compounds on diverse aggregate strains encoding different proteinopathy variants. The formation of β-sheet-rich species in our study also engenders a more critical examination of EGCG's mode of action on diverse classes of amyloids.

Enthalpy driven temperature-sensitive conformational changes in a metamorphic protein involved in the cyanobacterial circadian clock

Metamorphic proteins switch reversibly between distinctly different folds often with different functions under physiological conditions. Here, the kinetics and thermodynamics of the fold-switching at different temperatures in a metamorphic protein, KaiB, involved in cyanobacterial circadian clock, reveal that enthalpy-driven the fold-switching to form fold-switched KaiB (fsKaiB) and the fsKaiB and ground-state KaiB (gsKaiB) are more dominantly at lower and higher temperatures, respectively. Thermodynamic analysis indicates that conformational and solvent entropy have opposing effects on KaiB's fold-switching. The folding kinetic reveals that as KaiB folds, it preferentially folds into gsKaiB and then switches fold to fsKaiB. Temperature-sensitive protein fold-switching can be further extended into applications, such as new temperature-sensitive molecular switcher and biosensors development.

AlphaFold2's training set powers its predictions of some fold-switched conformations

AlphaFold2 (AF2), a deep-learning-based model that predicts protein structures from their amino acid sequences, has recently been used to predict multiple protein conformations. In some cases, AF2 has successfully predicted both dominant and alternative conformations of fold-switching proteins, which remodel their secondary and/or tertiary structures in response to cellular stimuli. Whether AF2 has learned enough protein folding principles to reliably predict alternative conformations outside of its training set is unclear. Previous work suggests that AF2 predicted these alternative conformations by memorizing them during training. Here, we use CFold-an implementation of the AF2 network trained on a more limited subset of experimentally determined protein structures-to directly test how well the AF2 architecture predicts alternative conformations of fold switchers outside of its training set. We tested CFold on eight fold switchers from six protein families. These proteins-whose secondary structures switch between α-helix and β-sheet and/or whose hydrogen bonding networks are reconfigured dramatically-had not been tested previously, and only one of their alternative conformations was in CFold's training set. Successful CFold predictions would indicate that the AF2 architecture can predict disparate alternative conformations of fold-switched conformations outside of its training set, while unsuccessful predictions would suggest that AF2 predictions of these alternative conformations likely arise from association with structures learned during training. Despite sampling 1300-4300 structures/protein with various sequence sampling techniques, CFold predicted only one alternative structure outside of its training set accurately and with high confidence while also generating experimentally inconsistent structures with higher confidence. Though these results indicate that AF2's current success in predicting alternative conformations of fold switchers stems largely from its training data, results from a sequence pruning technique suggest developments that could lead to a more reliable generative model in the future.

Impact of N-Terminal Domain Conformation and Domain Interactions on RfaH Fold Switching

RfaH is a two-domain metamorphic protein involved in transcription regulation and translation initiation. To carry out its dual functions, RfaH relies on two coupled structural changes: Domain dissociation and fold switching. In the free state, the C-terminal domain (CTD) of RfaH adopts an all-α fold and is tightly associated with the N-terminal domain (NTD). Upon binding to RNA polymerase (RNAP), the domains dissociate and the CTD transforms into an all-β fold while the NTD remains largely, but not entirely, unchanged. We test the idea that a change in the conformation of an extended β-hairpin (β3-β4) located on the NTD, helps trigger domain dissociation. To this end, we use homology modeling to construct a structure, H1, which is similar to free RfaH but with a remodeled β3-β4 hairpin. We then use an all-atom physics-based model enhanced with a dual basin structure-based potential to simulate domain separation driven by the thermal unfolding of the CTD with NTD in a fixed, folded conformation. We apply our model to both free RfaH and H1. For H1 we find, in line with our hypothesis, that the CTD exhibits lower stability and the domains dissociate at a lower temperature T, as compared to free RfaH. We do not, however, observe complete refolding to the all-β state in these simulations, suggesting that a change in β3-β4 orientation aids in, but is not sufficient for, domain dissociation. In addition, we study the reverse fold switch in which RfaH returns from a domain-open all-β state to its domain-closed all-α state. We observe a T-dependent transition rate; fold switching is slow at low T, where the CTD tends to be kinetically trapped in its all-β state, and at high-T, where the all-α state becomes unstable. Consequently, our simulations suggest an optimal T at which fold switching is most rapid. At this T, the stabilities of both folds are reduced. Overall, our study suggests that both inter-domain interactions and conformational changes within NTD may be important for the proper functioning of RfaH.

From duplication to fusion: Expanding Dayhoff's model of protein evolution

Dayhoff's hypothesis suggests that complex proteins emerged from simpler peptides or domains, which duplicated and fused to create more complex proteins and novel functions. These processes expanded and diversified the protein repertoire within organisms. Extensive studies and reviews over the past two decades have highlighted the impact of gene duplication on protein evolution. However, the role of fusion in this evolutionary narrative remains less understood. This perspective seeks to address this gap by emphasizing the role of fusion in evolution. Fusion is critical in determining the evolutionary fate of duplicated protomers, either preserving their ancestral function or evolving entirely new functions. It complements mutations, insertions, and deletions as evolutionary steps to enhance protein evolvability by expanding the capacity of the protein to explore new structural and functional space.

The multifaceted role of XCL1 in health and disease

The chemokine XC motif chemokine ligand 1 (XCL1) is an unusually specialized member of a conserved family of around 50 small, secreted proteins that are best known for their ability to stimulate the directional migration of cells. All chemokines adopt a very similar folded structure that binds a specific G protein-coupled receptor (GPCR), and most chemokines bind extracellular matrix glycosaminoglycans, often in a dimeric or oligomeric form. Owing in part to the lack of a disulfide bond that is conserved in all other chemokines, XCL1 interconverts between two distinct structures with distinct functions. One XCL1 fold resembles the structure of all other chemokines (chemokine fold), while the other does not (alternate fold). The chemokine fold of XCL1 displays high affinity for the GPCR XCR1, while the alternative fold binds GAGs and exhibits antimicrobial activity. Although the canonical role of XCL1 as a CD8+ dendritic cell chemoattractant was defined more than a decade ago, the misconception that XCL1 is a lymphocyte-specific chemoattractant still prevails in the recent literature. This review aims to highlight the structure-guided functions of XCL1 and reclarify its immunological role. In addition, the implications of this metamorphic chemokine in vaccine development and emerging functions in the nervous system will be explored.

Metamorphic Proteins to Achieve Conformationally Selective Material Surface Binding

The controlled binding of proteins on nanoparticle surfaces remains a grand challenge required for many applications ranging from biomedical to energy storage. The difficulty in achieving this ability arises from the different functional groups of the biomolecule that can adsorb on the nanoparticle surface. While most proteins can only adopt a single structure, metamorphic proteins can access at least two different conformations, which presents intriguing opportunities to exploit such structural variations for binding to nanoparticles. Such effects are examined using calmodulin, a sensing messenger protein, that can adopt two conformations based on Ca2+ binding. The affinity of the apo and holo forms of the protein for Au is examined using a highly integrated set of experimental and computation studies, which demonstrated significantly enhanced binding for the holo protein as compared to the apo. Such effects are proposed to arise from changes in the protein structure, which lead to substantially varied biomolecular surfaces that facilitate both Au adsorption and protein-protein assembly once adsorbed. Such studies provide critical information for protein structural design to control nanoparticle adsorption for wide-ranging applications.

Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction

In recent years, advances in artificial intelligence (AI) have transformed structural biology, particularly protein structure prediction. Though AI-based methods, such as AlphaFold (AF), often predict single conformations of proteins with high accuracy and confidence, predictions of alternative folds are often inaccurate, low-confidence, or simply not predicted at all. Here, we review three blind spots that alternative conformations reveal about AF-based protein structure prediction. First, proteins that assume conformations distinct from their training-set homologs can be mispredicted. Second, AF overrelies on its training set to predict alternative conformations. Third, degeneracies in pairwise representations can lead to high-confidence predictions inconsistent with experiment. These weaknesses suggest approaches to predict alternative folds more reliably.

Evolutionary insights into the stereoselectivity of imine reductases based on ancestral sequence reconstruction

The stereoselectivity of enzymes plays a central role in asymmetric biocatalytic reactions, but there remains a dearth of evolution-driven biochemistry studies investigating the evolutionary trajectory of this vital property. Imine reductases (IREDs) are one such enzyme that possesses excellent stereoselectivity, and stereocomplementary members are pervasive in the family. However, the regulatory mechanism behind stereocomplementarity remains cryptic. Herein, we reconstruct a panel of active ancestral IREDs and trace the evolution of stereoselectivity from ancestors to extant IREDs. Combined with coevolution analysis, we reveal six historical mutations capable of recapitulating stereoselectivity evolution. An investigation of the mechanism with X-ray crystallography shows that they collectively reshape the substrate-binding pocket to regulate stereoselectivity inversion. In addition, we construct an empirical fitness landscape and discover that epistasis is prevalent in stereoselectivity evolution. Our findings emphasize the power of ASR in circumventing the time-consuming large-scale mutagenesis library screening for identifying mutations that change functions and support a Darwinian premise from a molecular perspective that the evolution of biological functions is a stepwise process.

Molecular basis for chemokine recognition and activation of XCR1

The X-C motif chemokine receptor XCR1, which selectively binds to the chemokine XCL1, is highly expressed in conventional dendritic cells subtype 1 (cDC1s) and crucial for their activation. Modulating XCR1 signaling in cDC1s could offer novel opportunities in cancer immunotherapy and vaccine development by enhancing the antigen presentation function of cDC1s. To investigate the molecular mechanism of XCL-induced XCR1 signaling, we determined a high-resolution structure of the human XCR1 and Gi complex with an engineered form of XCL1, XCL1 CC3, by cryoelectron microscopy. Through mutagenesis and structural analysis, we elucidated the molecular details for the binding of the N-terminal segment of XCL1 CC3, which is vital for activating XCR1. The unique arrangement within the XCL1 CC3 binding site confers specificity for XCL1 in XCR1. We propose an activation mechanism for XCR1 involving structural alterations of key residues at the bottom of the XCL1 binding pocket. These detailed insights into XCL1 CC3-XCR1 interaction and XCR1 activation pave the way for developing novel XCR1-targeted therapeutics.

Nurturing the phenotype: Environmental signals and transcriptional regulation of intestinal γδ T cells

The intestinal epithelium harbours a unique lymphocyte population, the intraepithelial lymphocytes (IELs). A large fraction of IELs is represented by γδ T cells. Their role in epithelial homeostasis and immune response is well documented, but a conclusive view of their developmental pathway is still missing. In this review, we discuss the existing literature as well as recent advances regarding the tissue adaptation of γδ IELs, both for the characteristic cytotoxic subset and the newly described noncytotoxic subset. We particularly highlight the environmental cues and the transcriptional regulation that equip γδ T cells with their IEL phenotype.

Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction

In recent years, advances in artificial intelligence (AI) have transformed structural biology, particularly protein structure prediction. Though AI-based methods, such as AlphaFold (AF), often predict single conformations of proteins with high accuracy and confidence, predictions of alternative folds are often inaccurate, low-confidence, or simply not predicted at all. Here, we review three blind spots that alternative conformations reveal about AF-based protein structure prediction. First, proteins that assume conformations distinct from their training-set homologs can be mispredicted. Second, AF overrelies on its training set to predict alternative conformations. Third, degeneracies in pairwise representations can lead to high-confidence predictions inconsistent with experiment. These weaknesses suggest approaches to predict alternative folds more reliably.

AlphaFold2's training set powers its predictions of fold-switched conformations

AlphaFold2 (AF2), a deep-learning based model that predicts protein structures from their amino acid sequences, has recently been used to predict multiple protein conformations. In some cases, AF2 has successfully predicted both dominant and alternative conformations of fold-switching proteins, which remodel their secondary and tertiary structures in response to cellular stimuli. Whether AF2 has learned enough protein folding principles to reliably predict alternative conformations outside of its training set is unclear. Here, we address this question by assessing whether CFold-an implementation of the AF2 network trained on a more limited subset of experimentally determined protein structures- predicts alternative conformations of eight fold switchers from six protein families. Previous work suggests that AF2 predicted these alternative conformations by memorizing them during training. Unlike AF2, CFold's training set contains only one of these alternative conformations. Despite sampling 1300-4400 structures/protein with various sequence sampling techniques, CFold predicted only one alternative structure outside of its training set accurately and with high confidence while also generating experimentally inconsistent structures with higher confidence. Though these results indicate that AF2's current success in predicting alternative conformations of fold switchers stems largely from its training data, results from a sequence pruning technique suggest developments that could lead to a more reliable generative model in the future.

Protein Fold Usages in Ribosomes: Another Glance to the Past

The analysis of protein fold usage, similar to codon usage, offers profound insights into the evolution of biological systems and the origins of modern proteomes. While previous studies have examined fold distribution in modern genomes, our study focuses on the comparative distribution and usage of protein folds in ribosomes across bacteria, archaea, and eukaryotes. We identify the prevalence of certain 'super-ribosome folds,' such as the OB fold in bacteria and the SH3 domain in archaea and eukaryotes. The observed protein fold distribution in the ribosomes announces the future power-law distribution where only a few folds are highly prevalent, and most are rare. Additionally, we highlight the presence of three copies of proto-Rossmann folds in ribosomes across all kingdoms, showing its ancient and fundamental role in ribosomal structure and function. Our study also explores early mechanisms of molecular convergence, where different protein folds bind equivalent ribosomal RNA structures in ribosomes across different kingdoms. This comparative analysis enhances our understanding of ribosomal evolution, particularly the distinct evolutionary paths of the large and small subunits, and underscores the complex interplay between RNA and protein components in the transition from the RNA world to modern cellular life. Transcending the concept of folds also makes it possible to group a large number of ribosomal proteins into five categories of urfolds or metafolds, which could attest to their ancestral character and common origins. This work also demonstrates that the gradual acquisition of extensions by simple but ordered folds constitutes an inexorable evolutionary mechanism. This observation supports the idea that simple but structured ribosomal proteins preceded the development of their disordered extensions.

Accurate prediction of protein function using statistics-informed graph networks

Understanding protein function is pivotal in comprehending the intricate mechanisms that underlie many crucial biological activities, with far-reaching implications in the fields of medicine, biotechnology, and drug development. However, more than 200 million proteins remain uncharacterized, and computational efforts heavily rely on protein structural information to predict annotations of varying quality. Here, we present a method that utilizes statistics-informed graph networks to predict protein functions solely from its sequence. Our method inherently characterizes evolutionary signatures, allowing for a quantitative assessment of the significance of residues that carry out specific functions. PhiGnet not only demonstrates superior performance compared to alternative approaches but also narrows the sequence-function gap, even in the absence of structural information. Our findings indicate that applying deep learning to evolutionary data can highlight functional sites at the residue level, providing valuable support for interpreting both existing properties and new functionalities of proteins in research and biomedicine.

Ancestral Reconstruction and the Evolution of Protein Energy Landscapes

A protein's sequence determines its conformational energy landscape. This, in turn, determines the protein's function. Understanding the evolution of new protein functions therefore requires understanding how mutations alter the protein energy landscape. Ancestral sequence reconstruction (ASR) has proven a valuable tool for tackling this problem. In ASR, one phylogenetically infers the sequences of ancient proteins, allowing characterization of their properties. When coupled to biophysical, biochemical, and functional characterization, ASR can reveal how historical mutations altered the energy landscape of ancient proteins, allowing the evolution of enzyme activity, altered conformations, binding specificity, oligomerization, and many other protein features. In this article, we review how ASR studies have been used to dissect the evolution of energy landscapes. We also discuss ASR studies that reveal how energy landscapes have shaped protein evolution. Finally, we propose that thinking about evolution from the perspective of an energy landscape can improve how we approach and interpret ASR studies.

Metamorphic proteins and how to find them

In the last two decades, our existing notion that most foldable proteins have a unique native state has been challenged by the discovery of metamorphic proteins, which reversibly interconvert between multiple, sometimes highly dissimilar, native states. As the number of known metamorphic proteins increases, several computational and experimental strategies have emerged for gaining insights about their refolding processes and identifying unknown metamorphic proteins amongst the known proteome. In this review, we describe the current advances in biophysically and functionally ascertaining the structural interconversions of metamorphic proteins and how coevolution can be harnessed to identify novel metamorphic proteins from sequence information. We also discuss the challenges and ongoing efforts in using artificial intelligence-based protein structure prediction methods to discover metamorphic proteins and predict their corresponding three-dimensional structures.

Back in time to the Gly-rich prototype of the phosphate binding elementary function

Binding of nucleotides and their derivatives is one of the most ancient elementary functions dating back to the Origin of Life. We review here the works considering one of the key elements in binding of (di)nucleotide-containing ligands - phosphate binding. We start from a brief discussion of major participants, conditions, and events in prebiotic evolution that resulted in the Origin of Life. Tracing back to the basic functions, including metal and phosphate binding, and, potentially, formation of primitive protein-protein interactions, we focus here on the phosphate binding. Critically assessing works on the structural, functional, and evolutionary aspects of phosphate binding, we perform a simple computational experiment reconstructing its most ancient and generic sequence prototype. The profiles of the phosphate binding signatures have been derived in form of position-specific scoring matrices (PSSMs), their peculiarities depending on the type of the ligands have been analyzed, and evolutionary connections between them have been delineated. Then, the apparent prototype that gave rise to all relevant phosphate-binding signatures had also been reconstructed. We show that two major signatures of the phosphate binding that discriminate between the binding of dinucleotide- and nucleotide-containing ligands are GxGxxG and GxxGxG, respectively. It appears that the signature archetypal for dinucleotide-containing ligands is more generic, and it can frequently bind phosphate groups in nucleotide-containing ligands as well. The reconstructed prototype's key signature GxGGxG underlies the role of glycine residues in providing flexibility and interactions necessary for binding the phosphate groups. The prototype also contains other ancient amino acids, valine, and alanine, showing versatility towards evolutionary design and functional diversification.

Evolution of Phosphorylase Activity in an Ancestral Glycosyltransferase

The reconstruction of ancestral sequences can offer a glimpse into the fascinating process of molecular evolution by exposing the adaptive pathways that shape the proteins found in nature today. Here, we track the evolution of the carbohydrate-active enzymes responsible for the synthesis and turnover of mannogen, a critical carbohydrate reserve in Leishmania parasites. Biochemical characterization of resurrected enzymes demonstrated that mannoside phosphorylase activity emerged in an ancestral bacterial mannosyltransferase, and later disappeared in the process of horizontal gene transfer and gene duplication in Leishmania. By shuffling through plausible historical sequence space in an ancestral mannosyltransferase, we found that mannoside phosphorylase activity could be toggled on through various combinations of mutations at positions outside of the active site. Molecular dynamics simulations showed that such mutations can affect loop rigidity and shield the active site from water molecules that disrupt key interactions, allowing α-mannose 1-phosphate to adopt a catalytically productive conformation. These findings highlight the importance of subtle distal mutations in protein evolution and suggest that the vast collection of natural glycosyltransferases may be a promising source of engineering templates for the design of tailored phosphorylases.

Predicting multiple conformations via sequence clustering and AlphaFold2

AlphaFold2 (ref. 1) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein's biological function often depends on multiple conformational substates2, and disease-causing point mutations often cause population changes within these substates3,4. We demonstrate that clustering a multiple-sequence alignment by sequence similarity enables AlphaFold2 to sample alternative states of known metamorphic proteins with high confidence. Using this method, named AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protein KaiB5 and found that predictions of both conformations were distributed in clusters across the KaiB family. We used nuclear magnetic resonance spectroscopy to confirm an AF-Cluster prediction: a cyanobacteria KaiB variant is stabilized in the opposite state compared with the more widely studied variant. To test AF-Cluster's sensitivity to point mutations, we designed and experimentally verified a set of three mutations predicted to flip KaiB from Rhodobacter sphaeroides from the ground to the fold-switched state. Finally, screening for alternative states in protein families without known fold switching identified a putative alternative state for the oxidoreductase Mpt53 in Mycobacterium tuberculosis. Further development of such bioinformatic methods in tandem with experiments will probably have a considerable impact on predicting protein energy landscapes, essential for illuminating biological function.

SSDraw: Software for generating comparative protein secondary structure diagrams

The program SSDraw generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. Diagrams of homologous proteins can be registered according to an input multiple sequence alignment. Linear visualization allows the user to stack registered diagrams, facilitating comparison of secondary structure and other properties among homologous proteins. SSDraw can be used to compare secondary structures of homologous proteins with both conserved and divergent folds. It can also generate one secondary structure diagram from an input protein structure of interest. The source code can be downloaded (https://github.com/ncbi/SSDraw) and run locally for rapid structure generation, while a Google Colab notebook allows easy use.

The First Nucleic Acid Strands May Have Grown on Peptides via Primeval Reverse Translation

The central dogma of molecular biology dictates that, with only a few exceptions, information proceeds from DNA to protein through an RNA intermediate. Examining the enigmatic steps from prebiotic to biological chemistry, we take another road suggesting that primordial peptides acted as template for the self-assembly of the first nucleic acids polymers. Arguing in favour of a sort of archaic "reverse translation" from proteins to RNA, our basic premise is a Hadean Earth where key biomolecules such as amino acids, polypeptides, purines, pyrimidines, nucleosides and nucleotides were available under different prebiotically plausible conditions, including meteorites delivery, shallow ponds and hydrothermal vents scenarios. Supporting a protein-first scenario alternative to the RNA world hypothesis, we propose the primeval occurrence of short two-dimensional peptides termed "selective amino acid- and nucleotide-matching oligopeptides" (henceforward SANMAOs) that noncovalently bind at the same time the polymerized amino acids and the single nucleotides dispersed in the prebiotic milieu. In this theoretical paper, we describe the chemical features of this hypothetical oligopeptide, its biological plausibility and its virtues from an evolutionary perspective. We provide a theoretical example of SANMAO's selective pairing between amino acids and nucleosides, simulating a poly-Glycine peptide that acts as a template to build a purinic chain corresponding to the glycine's extant triplet codon GGG. Further, we discuss how SANMAO might have endorsed the formation of low-fidelity RNA's polymerized strains, well before the appearance of the accurate genetic material's transmission ensured by the current translation apparatus.

SSDraw: software for generating comparative protein secondary structure diagrams

The program SSDraw generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. Diagrams of homologous proteins can be registered according to an input multiple sequence alignment. Linear visualization allows the user to stack registered diagrams, facilitating comparison of secondary structure and other properties among homologous proteins. SSDraw can be used to compare secondary structures of homologous proteins with both conserved and divergent folds. It can also generate one secondary structure diagram from an input protein structure of interest. The source code can be downloaded (https://github.com/ethanchen1301/SSDraw) and run locally for rapid structure generation, while a Google Colab notebook allows easy use.

Impact of ancestral sequence reconstruction on mechanistic and structural enzymology

Ancestral sequence reconstruction (ASR) provides insight into the changes within a protein sequence across evolution. More specifically, it can illustrate how specific amino acid changes give rise to different phenotypes within a protein family. Over the last few decades it has established itself as a powerful technique for revealing molecular common denominators that govern enzyme function. Here, we describe the strength of ASR in unveiling catalytic mechanisms and emerging phenotypes for a range of different proteins, also highlighting biotechnological applications the methodology can provide.

Simulations of a protein fold switch reveal crowding-induced population shifts driven by disordered regions

Macromolecular crowding effects on globular proteins, which usually adopt a single stable fold, have been widely studied. However, little is known about crowding effects on fold-switching proteins, which reversibly switch between distinct folds. Here we study the mutationally driven switch between the folds of GA and GB, the two 56-amino acid binding domains of protein G, using a structure-based dual-basin model. We show that, in the absence of crowders, the fold populations PA and PB can be controlled by the strengths of contacts in the two folds, κA and κB. A population balance, PA ≈ PB, is obtained for κB/κA = 0.92. The resulting model protein is subject to crowding at different packing fractions, ϕc. We find that crowding increases the GB population and reduces the GA population, reaching PB/PA ≈ 4 at ϕc = 0.44. We analyze the ϕc-dependence of the crowding-induced GA-to-GB switch using scaled particle theory, which provides a qualitative, but not quantitative, fit of our data, suggesting effects beyond a spherical description of the folds. We show that the terminal regions of the protein chain, which are intrinsically disordered only in GA, play a dominant role in the response of the fold switch to crowding effects.

Evolutionary selection of proteins with two folds

Although most globular proteins fold into a single stable structure, an increasing number have been shown to remodel their secondary and tertiary structures in response to cellular stimuli. State-of-the-art algorithms predict that these fold-switching proteins adopt only one stable structure, missing their functionally critical alternative folds. Why these algorithms predict a single fold is unclear, but all of them infer protein structure from coevolved amino acid pairs. Here, we hypothesize that coevolutionary signatures are being missed. Suspecting that single-fold variants could be masking these signatures, we developed an approach, called Alternative Contact Enhancement (ACE), to search both highly diverse protein superfamilies-composed of single-fold and fold-switching variants-and protein subfamilies with more fold-switching variants. ACE successfully revealed coevolution of amino acid pairs uniquely corresponding to both conformations of 56/56 fold-switching proteins from distinct families. Then, we used ACE-derived contacts to (1) predict two experimentally consistent conformations of a candidate protein with unsolved structure and (2) develop a blind prediction pipeline for fold-switching proteins. The discovery of widespread dual-fold coevolution indicates that fold-switching sequences have been preserved by natural selection, implying that their functionalities provide evolutionary advantage and paving the way for predictions of diverse protein structures from single sequences.

Fluid protein fold space and its implications

Fold-switching proteins, which remodel their secondary and tertiary structures in response to cellular stimuli, suggest a new view of protein fold space. For decades, experimental evidence has indicated that protein fold space is discrete: dissimilar folds are encoded by dissimilar amino acid sequences. Challenging this assumption, fold-switching proteins interconnect discrete groups of dissimilar protein folds, making protein fold space fluid. Three recent observations support the concept of fluid fold space: (1) some amino acid sequences interconvert between folds with distinct secondary structures, (2) some naturally occurring sequences have switched folds by stepwise mutation, and (3) fold switching is evolutionarily selected and likely confers advantage. These observations indicate that minor amino acid sequence modifications can transform protein structure and function. Consequently, proteomic structural and functional diversity may be expanded by alternative splicing, small nucleotide polymorphisms, post-translational modifications, and modified translation rates.

Molecular determinants of protein evolvability

The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein's initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration.

Metamorphic protein folding as evolutionary adaptation

Metamorphic proteins switch reversibly between multiple distinct, stable structures, often with different functions. It was previously hypothesized that metamorphic proteins arose as intermediates in the evolution of a new fold - rare and transient exceptions to the 'one sequence, one fold' paradigm. However, as described herein, mounting evidence suggests that metamorphic folding is an adaptive feature, preserved and optimized over evolutionary time as exemplified by the NusG family and the chemokine XCL1. Analysis of extant protein families and resurrected protein ancestors demonstrates that large regions of sequence space are compatible with metamorphic folding. As a category that enhances biological fitness, metamorphic proteins are likely to employ fold switching to perform important biological functions and may be more common than previously thought.

Crowded environments tune the fold-switching in metamorphic proteins

Metamorphic proteins such as circadian clock protein KaiB and human chemokine XCL1 play vital roles in regulating biological processes, including gene expression, circadian clock and innate immune responses, and perform distinct functions in living cell by switching different structures in response to cellular environment stimuli. However, it is unclear how complex and crowded intracellular environments affect conformational rearrangement of metamorphic proteins. Here, the kinetics and thermodynamics of two well-characterized metamorphic proteins, circadian clock protein KaiB and human chemokine XCL1, were quantified in physiologically relevant environments by using NMR spectroscopy, indicating that crowded agents shift equilibrium towards the inactive form (ground-state KaiB and Ltn10-like state XCL1) without disturbing the corresponding structures, and crowded agents have predominantly impact on the exchange rate of XCL1 that switches folds on timescales of seconds, but have slightly impact on the exchange rate of KaiB that switches folds on timescales of hours. Our data shed light on how metamorphic proteins can respond immediately to the changed crowded intracellular conditions that induced by environmental cues and then execute different functions in living cell, and it also enhances our understanding of how environments enrich the sequence-structure-function paradigm.

Identification of a covert evolutionary pathway between two protein folds

Although homologous protein sequences are expected to adopt similar structures, some amino acid substitutions can interconvert α-helices and β-sheets. Such fold switching may have occurred over evolutionary history, but supporting evidence has been limited by the: (1) abundance and diversity of sequenced genes, (2) quantity of experimentally determined protein structures, and (3) assumptions underlying the statistical methods used to infer homology. Here, we overcome these barriers by applying multiple statistical methods to a family of ~600,000 bacterial response regulator proteins. We find that their homologous DNA-binding subunits assume divergent structures: helix-turn-helix versus α-helix + β-sheet (winged helix). Phylogenetic analyses, ancestral sequence reconstruction, and AlphaFold2 models indicate that amino acid substitutions facilitated a switch from helix-turn-helix into winged helix. This structural transformation likely expanded DNA-binding specificity. Our approach uncovers an evolutionary pathway between two protein folds and provides a methodology to identify secondary structure switching in other protein families.

Thermodynamic Evolution of a Metamorphic Protein: A Theoretical-Computational Study of Human Lymphotactin

Metamorphic, or fold-switching, proteins feature different folds that are physiologically relevant. The human chemokine XCL1 (or Lymphotactin) is a metamorphic protein that features two native states, an [Formula: see text] and an all[Formula: see text] fold, which have similar stability at physiological condition. Here, extended molecular dynamics (MD) simulations, principal component analysis of atomic fluctuations and thermodynamic modeling based on both the configurational volume and free energy landscape, are used to obtain a detailed characterization of the conformational thermodynamics of human Lymphotactin and of one of its ancestors (as was previously obtained by genetic reconstruction). Comparison of our computational results with the available experimental data show that the MD-based thermodynamics can explain the experimentally observed variation of the conformational equilibrium between the two proteins. In particular, our computational data provide an interpretation of the thermodynamic evolution in this protein, revealing the relevance of the configurational entropy and of the shape of the free energy landscape within the essential space (i.e., the space defined by the generalized internal coordinates providing the largest, typically non-Gaussian, structural fluctuations).

What defines a chemokine? - The curious case of CXCL17

Chemotactic cytokines (chemokines) are a group of around 40 small proteins which share a similar protein fold and are well known for their ability to direct the migration of leukocytes to a variety of tissue locations. CXCL17 was the last member of the chemokine family to be assigned and was admitted to the family based on theoretical modelling of the CXCL17 structure and chemotactic activity for monocytes and dendritic cells. Of Interest, CXCL17 expression appears to be restricted to mucosal tissues such as the tongue, stomach and lung, suggestive of specific roles at these locations. A putative CXCL17 receptor, GPR35 was reportedly identified and mice deficient in CXCL17 were generated and characterised. More recently, however, some apparent contradictions regarding aspects of CXCL17 biology have been raised by ourselves and others. Notably, GPR35 appears to be a receptor for the serotonin metabolite 5-hydroxyindoleacetic acid rather than for CXCL17 and modelling of CXCL17 using a variety of platforms fails to identify a chemokine-like fold. In this article, we summarize the discovery of CXCL17 and discuss key papers describing the subsequent characterisation of this protein. Ultimately, we pose the question, 'What defines a chemokine?' (185 words).

Distinguishing features of fold-switching proteins

Though many folded proteins assume one stable structure that performs one function, a small-but-increasing number remodel their secondary and tertiary structures and change their functions in response to cellular stimuli. These fold-switching proteins regulate biological processes and are associated with autoimmune dysfunction, severe acute respiratory syndrome coronavirus-2 infection, and more. Despite their biological importance, it is difficult to computationally predict fold switching. With the aim of advancing computational prediction and experimental characterization of fold switchers, this review discusses several features that distinguish fold-switching proteins from their single-fold and intrinsically disordered counterparts. First, the isolated structures of fold switchers are less stable and more heterogeneous than single folders but more stable and less heterogeneous than intrinsically disordered proteins (IDPs). Second, the sequences of single fold, fold switching, and intrinsically disordered proteins can evolve at distinct rates. Third, proteins from these three classes are best predicted using different computational techniques. Finally, late-breaking results suggest that single folders, fold switchers, and IDPs have distinct patterns of residue-residue coevolution. The review closes by discussing high-throughput and medium-throughput experimental approaches that might be used to identify new fold-switching proteins.

Genetic Perturbation Alters Functional Substates in Alkaline Phosphatase

Enzymes inherently exhibit molecule-to-molecule heterogeneity in their conformational and functional states, which is considered to be a key to the evolution of new functions. Single-molecule enzyme assays enable us to directly observe such multiple functional states or functional substates. Here, we quantitatively analyzed functional substates in the wild-type and 69 single-point mutants of Escherichia coli alkaline phosphatase by employing a high-throughput single-molecule assay with a femtoliter reactor array device. Interestingly, many mutant enzymes exhibited significantly heterogeneous functional substates with various types, while the wild-type enzyme showed a highly homogeneous substate. We identified a correlation between the degree of functional substates and the level of improvement in promiscuous activities. Our work provides much comprehensive evidence that the functional substates can be easily altered by mutations, and the evolution toward a new catalytic activity may involve the modulation of the functional substates.

Design and characterization of a protein fold switching network

To better understand how amino acid sequence encodes protein structure, we engineered mutational pathways that connect three common folds (3α, β-grasp, and α/β-plait). The structures of proteins at high sequence-identity intersections in the pathways (nodes) were determined using NMR spectroscopy and analyzed for stability and function. To generate nodes, the amino acid sequence encoding a smaller fold is embedded in the structure of an ~50% larger fold and a new sequence compatible with two sets of native interactions is designed. This generates protein pairs with a 3α or β-grasp fold in the smaller form but an α/β-plait fold in the larger form. Further, embedding smaller antagonistic folds creates critical states in the larger folds such that single amino acid substitutions can switch both their fold and function. The results help explain the underlying ambiguity in the protein folding code and show that new protein structures can evolve via abrupt fold switching.

Reversible switching between two common protein folds in a designed system using only temperature

Naturally occurring metamorphic proteins have the ability to interconvert from one folded state to another through either a limited set of mutations or by way of a change in the local environment. Here, we show in a designed system that it is possible to switch reversibly between two of the most common monomeric folds employing only temperature changes. We demonstrate that a latent 3α state can be unmasked from an α/β-plait topology with a single V90T amino acid substitution, populating both forms simultaneously. The equilibrium between these two states exhibits temperature dependence, such that the 3α state is predominant (>90%) at 5 °C, while the α/β-plait fold is the major species (>90%) at 30 °C. We describe the structure and dynamics of these topologies, how mutational changes affect the temperature dependence, and the energetics and kinetics of interconversion. Additionally, we demonstrate how ligand-binding function can be tightly regulated by large amplitude changes in protein structure over a relatively narrow temperature range that is relevant to biology. The 3α/αβ switch thus represents a potentially useful approach for designing proteins that alter their fold topologies in response to environmental triggers. It may also serve as a model for computational studies of temperature-dependent protein stability and fold switching.

Evolutionary selection of proteins with two folds

Although most globular proteins fold into a single stable structure 1 , an increasing number have been shown to remodel their secondary and tertiary structures in response to cellular stimuli 2 . State-of-the-art algorithms 3-5 predict that these fold-switching proteins assume only one stable structure 6,7 , missing their functionally critical alternative folds. Why these algorithms predict a single fold is unclear, but all of them infer protein structure from coevolved amino acid pairs. Here, we hypothesize that coevolutionary signatures are being missed. Suspecting that over-represented single-fold sequences may be masking these signatures, we developed an approach to search both highly diverse protein superfamilies-composed of single-fold and fold-switching variants-and protein subfamilies with more fold-switching variants. This approach successfully revealed coevolution of amino acid pairs uniquely corresponding to both conformations of 56/58 fold-switching proteins from distinct families. Then, using a set of coevolved amino acid pairs predicted by our approach, we successfully biased AlphaFold2 5 to predict two experimentally consistent conformations of a candidate protein with unsolved structure. The discovery of widespread dual-fold coevolution indicates that fold-switching sequences have been preserved by natural selection, implying that their functionalities provide evolutionary advantage and paving the way for predictions of diverse protein structures from single sequences.

Protein dynamics: The future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem," we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function.

Physiology of chemokines in the cancer microenvironment

Chemokines are chemotactic cytokines whose canonical functions govern movement of receptor-expressing cells along chemical gradients. Chemokines are a physiological system that is finely tuned by ligand and receptor expression, ligand or receptor oligomerization, redundancy, expression of atypical receptors, and non-GPCR binding partners that cumulatively influence discrete pharmacological signaling responses and cellular functions. In cancer, chemokines play paradoxical roles in both the directed emigration of metastatic, receptor-expressing cancer cells out of the tumor as well as immigration of tumor-infiltrating immune cells that culminate in a tumor-unique immune microenvironment. In the age of precision oncology, strategies to effectively harness the power of immunotherapy requires consideration of chemokine gradients within the unique spatial topography and temporal influences with heterogeneous tumors. In this article, we review current literature on the diversity of chemokine ligands and their cellular receptors that detect and process chemotactic gradients and illustrate how differences between ligand recognition and receptor activation influence the signaling machinery that drives cellular movement into and out of the tumor microenvironment. Facets of chemokine physiology across discrete cancer immune phenotypes are contrasted to existing chemokine-centered therapies in cancer.

Metamorphic proteins under a computational microscope: Lessons from a fold-switching RfaH protein

Metamorphic proteins constitute unexpected paradigms of the protein folding problem, as their sequences encode two alternative folds, which reversibly interconvert within biologically relevant timescales to trigger different cellular responses. Once considered a rare aberration, metamorphism may be common among proteins that must respond to rapidly changing environments, exemplified by NusG-like proteins, the only transcription factors present in every domain of life. RfaH, a specialized paralog of bacterial NusG, undergoes an all-α to all-β domain switch to activate expression of virulence and conjugation genes in many animal and plant pathogens and is the quintessential example of a metamorphic protein. The dramatic nature of RfaH structural transformation and the richness of its evolutionary history makes for an excellent model for studying how metamorphic proteins switch folds. Here, we summarize the structural and functional evidence that sparked the discovery of RfaH as a metamorphic protein, the experimental and computational approaches that enabled the description of the molecular mechanism and refolding pathways of its structural interconversion, and the ongoing efforts to find signatures and general properties to ultimately describe the protein metamorphome.

Intrinsically fluorescent polyureas toward conformation-assisted metamorphosis, discoloration and intracellular drug delivery

Peptidomimetic polymers have attracted increasing interest because of the advantages of facile synthesis, high molecular tunability, resistance to degradation, and low immunogenicity. However, the presence of non-native linkages compromises their ability to form higher ordered structures and protein-inspired functions. Here we report a class of amino acid-constructed polyureas with molecular weight- and solvent-dependent helical and sheet-like conformations as well as green fluorescent protein-mimic autofluorescence with aggregation-induced emission characteristics. The copolymers self-assemble into vesicles and nanotubes and exhibit H-bonding-mediated metamorphosis and discoloration behaviors. We show that these polymeric vehicles with ultrahigh stability, superfast responsivity and conformation-assisted cell internalization efficiency could act as an “on-off” switchable nanocarrier for specific intracellular drug delivery and effective cancer theranosis in vitro and in vivo. This work provides insights into the folding and hierarchical assembly of biomacromolecules, and a new generation of bioresponsive polymers and nonconventional luminescent aliphatic materials for diverse applications.

Biomimetic materials are of interest but can often suffer from limitations caused by the non-native linkages used. Here, the authors report on the creation of amino acid constructed polyureas which can self-assemble into vesicles and nanotubes with aggregation induced fluorescence and the potential for drug delivery applications.

Mechanisms of protein evolution

How do proteins evolve? How do changes in sequence mediate changes in protein structure, and in turn in function? This question has multiple angles, ranging from biochemistry and biophysics to evolutionary biology. This review provides a brief integrated view of some key mechanistic aspects of protein evolution. First, we explain how protein evolution is primarily driven by randomly acquired genetic mutations and selection for function, and how these mutations can even give rise to completely new folds. Then, we also comment on how phenotypic protein variability, including promiscuity, transcriptional and translational errors, may also accelerate this process, possibly via "plasticity-first" mechanisms. Finally, we highlight open questions in the field of protein evolution, with respect to the emergence of more sophisticated protein systems such as protein complexes, pathways, and the emergence of pre-LUCA enzymes.

Many dissimilar NusG protein domains switch between α-helix and β-sheet folds

Folded proteins are assumed to be built upon fixed scaffolds of secondary structure, α-helices and β-sheets. Experimentally determined structures of >58,000 non-redundant proteins support this assumption, though it has recently been challenged by ~100 fold-switching proteins. Though ostensibly rare, these proteins raise the question of how many uncharacterized proteins have shapeshifting-rather than fixed-secondary structures. Here, we use a comparative sequence-based approach to predict fold switching in the universally conserved NusG transcription factor family, one member of which has a 50-residue regulatory subunit experimentally shown to switch between α-helical and β-sheet folds. Our approach predicts that 24% of sequences in this family undergo similar α-helix ⇌ β-sheet transitions. While these predictions cannot be reproduced by other state-of-the-art computational methods, they are confirmed by circular dichroism and nuclear magnetic resonance spectroscopy for 10 out of 10 sequence-diverse variants. This work suggests that fold switching may be a pervasive mechanism of transcriptional regulation in all kingdoms of life.

Design and discovery of metamorphic proteins

Metamorphic proteins are single amino acid sequences that reversibly interconvert between multiple, dramatically different native structures, often with distinct functions. Since the discovery of the first metamorphic proteins in the early 2000s, several additional metamorphic proteins have been identified, and it was suggested that up to 4% of proteins in the PDB may switch folds. Metamorphic proteins have been found to share common features such as marginal thermostability and inconsistencies in predicted secondary structures. Outstanding challenges in the field include the search for more metamorphic proteins and the design of new proteins that switch folds. Identification of novel metamorphic proteins in nature will improve therapeutic targeting of fold-switching proteins involved in human pathology and will enhance the design of protein-based therapies. Designed fold switching proteins have applications as biosensors, molecular switches, molecular machines, and self-assembling systems.