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

Unveiling the cold reality of metamorphic proteins

Metamorphic proteins switch reversibly between two differently folded states under a variety of environmental conditions. Their identification and prediction are gaining attention, but the fundamental physicochemical basis for fold switching remains poorly understood. In this Perspective article, we address this problem by surveying the landscape of well-characterized metamorphic proteins and noting that a significant fraction of them display temperature sensitivity. We then make the case that the dependence on temperature, in particular cold-denaturation effects, is likely to be an underlying property of many metamorphic proteins regardless of their ultimate triggering mechanisms, especially those with a single domain. The argument is supported by rigorous analysis of hydrophobic effects in each well-characterized metamorphic protein pair and a description of how these parameters relate to temperature. The conclusion discusses the relevance of these insights to a better understanding of prediction, evolution, and de novo design strategies for metamorphic proteins.

Evolving concepts of the protein universe

The protein universe is the collection of all proteins on earth from all organisms both extant and extinct. Classical studies on protein folding suggested that proteins exist as a unique three-dimensional conformation that is dictated by the genetic code and is critical for function. In this perspective, we discuss ideas and developments that emerged over the past three decades regarding the protein structure-function paradigm. It is now clear that ordered (active/functional) and disordered/denatured (and hence inactive/non-functional) represent a continuum of states rather than binary states. Some proteins can switch folds without sequence change. Others exist as conformational ensembles lacking defined structure yet play critical roles in many biological processes, including forming membrane-less organelles driven by liquid-liquid phase separation. Numerous diverse proteins harbor segments with the potential to form amyloid fibrils, many of which are functional, and some possess prion-like properties enabling conformation-based transfer of heritable information. Taken together, these developments reveal the remarkable complexity of the protein universe.

AFsample2 predicts multiple conformations and ensembles with AlphaFold2

Understanding protein dynamics and conformational states is crucial for insights into biological processes and disease mechanisms, which can aid drug development. Recently, several methods have been devised to broaden the conformational predictions made by AlphaFold2 (AF2). We introduce AFsample2, a method using random MSA column masking to reduce co-evolutionary signals, enhancing structural diversity in AF2-generated models. AFsample2 effectively predicts alternative states for various proteins, producing high-quality end states and diverse conformational ensembles. In the OC23 dataset, alternate state models improved (ΔTM>0.05) in 9 out of 23 cases without affecting preferred state generation. Similar results were seen in 16 membrane protein transporters, with 11 out of 16 targets showing improvement. TM-score improvements to experimental end states were substantial, sometimes exceeding 50%, improving from 0.58 to 0.98. Additionally, AFsample2 increased the diversity of intermediate conformations by 70% compared to standard AF2, producing highly confident models potentially representing intermediate states. For four targets, predicted intermediate states were structurally similar to known structural homologs in the PDB, suggesting that they are true intermediate states. These findings indicate that AFsample2 can used to provide structural insights into proteins with multiple states, as well as potential paths between the states.

Photocontrolling the Enantioselectivity of a Phosphotriesterase via Incorporation of a Light-Responsive Unnatural Amino Acid

The external control of catalytic activity and substrate specificity of enzymes by light has aroused great interest in the fields of biocatalysis and pharmacology. Going beyond, we have attempted to photocontrol enzyme stereoselectivity on the example of phosphotriesterase (PTE), which is capable of hydrolyzing a wide variety of racemic organophosphorus substrates where one of two enantiomers is often highly toxic. To pursue this goal, the photocaged unnatural amino acid o-nitrobenzyl-l-tyrosine (ONBY) was incorporated by genetic code expansion at the large subsite of the active center, together with additional mutations at the small subsite. The stereoselectivities of the resulting PTE variants were tested with the achiral control substrate paraoxon and four different racemic substrates, which contained a p-nitrophenol leaving group in combination with either methyl-phenyl, ethyl-phenyl, methyl-cyclohexyl, or ethyl-cyclohexyl substituents. Comparison of the enantioselectivities (k cat/K M for Sp divided by k cat/K M for Rp) before and after decaging of ONBY using irradiation revealed the desired photoinduced inversion of enantioselectivity for three of the variants: PTE_I106A-H257ONBY exhibited a 43-fold stereoselectivity switch for the methyl-phenyl substrate, PTE_I106A-F132A-H257ONBY a 184-fold stereoselectivity switch for the methyl-cyclohexyl substrate, and PTE_I106A-F132A-S308A-H257ONBY a 52-fold and a 57-fold stereoselectivity switch for the methyl-cyclohexyl and the ethyl-cyclohexyl substrates. A computational analysis including molecular dynamics simulations and docking showed that a complicated interplay between steric constraints and specific enzyme-substrate interactions is responsible for the observed effects. Our findings significantly broaden the scope of possibilities for the spatiotemporal control of enantioselective transformations using light in biocatalytic systems.

Seesaw protein: Design of a protein that adopts interconvertible alternative functional conformations and its dynamics

According to classical Anfinsen's dogma, a protein folds into a single unique conformation with minimal Gibbs energy under physiological conditions. However, certain proteins may fold into two or more conformations from single amino acid sequences. Here, we designed a protein that adopts interconvertible alternative functional conformations, termed "seesaw" protein (SSP). An SSP was engineered by fusing GFP lacking the C-terminal β-strand and dihydrofolate reductase (DHFR) lacking the N-terminal β-strand with an overlapping linker, which can be competitively incorporated into either the GFP or the DHFR moiety. In vivo and biochemical analyses, including atomic force microscopy (AFM) imaging, demonstrated that the SSP adopts two alternative conformations, which can be biased by point mutations and ligand binding. The drastic conformational change upon the ligand binding was directly visualized by high-speed AFM. Furthermore, the balance of the seesaw can be reversibly changed depending on buffer conditions. In summary, our design strategy for SSP provides a unique direction for creating artificial proteins with on-off behaviors.

Conformational dynamics and multi-modal interaction of Paxillin with the Focal Adhesion Targeting Domain

Paxillin (PXN) and focal adhesion kinase (FAK) are two major components of the focal adhesion complex, a multiprotein structure linking the intracellular cytoskeleton to the cell exterior. PXN interacts directly with the C-terminal targeting domain of FAK (FAT) via its intrinsically disordered N-terminal domain. This interaction is necessary and sufficient for localizing FAK to focal adhesions. Furthermore, PXN serves as a platform for recruiting other proteins that together control the dynamic changes needed for cell migration and survival. Here, we show that the PXN disordered region undergoes large-scale conformational restriction upon binding to FAT, forming a 48-kDa multi-modal complex consisting of four major interconverting states. Although the complex is flexible, each state has unique sets of contacts involving disordered regions that are both highly represented in ensembles and conserved. Moreover, conserved intramolecular contacts from glutamine-rich regions in PXN contribute to high entropy and thus stability of the FAT bound complex. As PXN is a hub protein, the results provide a structural basis for understanding how perturbations that lead to cellular network rewiring, such as ligand binding and phosphorylation, may lead to shifts in the multi-state equilibrium and phenotypic switching.

Temperature-dependent fold-switching mechanism of the circadian clock protein KaiB

The oscillator of the cyanobacterial circadian clock relies on the ability of the KaiB protein to switch reversibly between a stable ground-state fold (gsKaiB) and an unstable fold-switched fold (fsKaiB). Rare fold-switching events by KaiB provide a critical delay in the negative feedback loop of this posttranslational oscillator. In this study, we experimentally and computationally investigate the temperature dependence of fold switching and its mechanism. We demonstrate that the stability of gsKaiB increases with temperature compared to fsKaiB and that the Q10 value for the gsKaiB → fsKaiB transition is nearly three times smaller than that for the reverse transition in a construct optimized for NMR studies. Simulations and native-state hydrogen-deuterium exchange NMR experiments suggest that fold switching can involve both partially and completely unfolded intermediates. The simulations predict that the transition state for fold switching coincides with isomerization of conserved prolines in the most rapidly exchanging region, and we confirm experimentally that proline isomerization is a rate-limiting step for fold switching. We explore the implications of our results for temperature compensation, a hallmark of circadian clocks, through a kinetic model.

AlphaFold predictions of fold-switched conformations are driven by structure memorization

Recent work suggests that AlphaFold (AF)-a deep learning-based model that can accurately infer protein structure from sequence-may discern important features of folded protein energy landscapes, defined by the diversity and frequency of different conformations in the folded state. Here, we test the limits of its predictive power on fold-switching proteins, which assume two structures with regions of distinct secondary and/or tertiary structure. We find that (1) AF is a weak predictor of fold switching and (2) some of its successes result from memorization of training-set structures rather than learned protein energetics. Combining >280,000 models from several implementations of AF2 and AF3, a 35% success rate was achieved for fold switchers likely in AF's training sets. AF2's confidence metrics selected against models consistent with experimentally determined fold-switching structures and failed to discriminate between low and high energy conformations. Further, AF captured only one out of seven experimentally confirmed fold switchers outside of its training sets despite extensive sampling of an additional ~280,000 models. Several observations indicate that AF2 has memorized structural information during training, and AF3 misassigns coevolutionary restraints. These limitations constrain the scope of successful predictions, highlighting the need for physically based methods that readily predict multiple protein conformations.

An ancestral fold reveals the evolutionary link between RNA polymerase and ribosomal proteins

Numerous molecular machines are required to drive the central dogma of molecular biology. However, the means by which these numerous proteins emerged in the early evolutionary stage of life remains enigmatic. Many of them possess small β-barrel folds with different topologies, represented by double-psi β-barrels (DPBBs) conserved in DNA and RNA polymerases, and similar but topologically distinct six-stranded β-barrel RIFT or five-stranded β-barrel folds such as OB and SH3 in ribosomal proteins. Here, we discover that the previously reconstructed ancient DPBB sequence could also adopt a β-barrel fold named Double-Zeta β-barrel (DZBB), as a metamorphic protein. The DZBB fold is not found in any modern protein, although its structure shares similarities with RIFT and OB. Indeed, DZBB could be transformed into them through simple engineering experiments. Furthermore, the OB designs could be further converted into SH3 by circular-permutation as previously predicted. These results indicate that these β-barrels diversified quickly from a common ancestor at the beginning of the central dogma evolution.

Temperature-Dependent Fold-Switching Mechanism of the Circadian Clock Protein KaiB

The oscillator of the cyanobacterial circadian clock relies on the ability of the KaiB protein to switch reversibly between a stable ground-state fold (gsKaiB) and an unstable fold-switched fold (fsKaiB). Rare fold-switching events by KaiB provide a critical delay in the negative feedback loop of this post-translational oscillator. In this study, we experimentally and computationally investigate the temperature dependence of fold switching and its mechanism. We demonstrate that the stability of gsKaiB increases with temperature compared to fsKaiB and that the Q10 value for the gsKaiB → fsKaiB transition is nearly three times smaller than that for the reverse transition. Simulations and native-state hydrogen-deuterium exchange NMR experiments suggest that fold switching can involve both subglobally and near-globally unfolded intermediates. The simulations predict that the transition state for fold switching coincides with isomerization of conserved prolines in the most rapidly exchanging region, and we confirm experimentally that proline isomerization is a rate-limiting step for fold switching. We explore the implications of our results for temperature compensation, a hallmark of circadian clocks, through a kinetic model.

AlphaFold2 has more to learn about protein energy landscapes

Recent work suggests that AlphaFold2 (AF2)-a deep learning-based model that can accurately infer protein structure from sequence-may discern important features of folded protein energy landscapes, defined by the diversity and frequency of different conformations in the folded state. Here, we test the limits of its predictive power on fold-switching proteins, which assume two structures with regions of distinct secondary and/or tertiary structure. Using several implementations of AF2, including two published enhanced sampling approaches, we generated >280,000 models of 93 fold-switching proteins whose experimentally determined conformations were likely in AF2's training set. Combining all models, AF2 predicted fold switching with a modest success rate of ~25%, indicating that it does not readily sample both experimentally characterized conformations of most fold switchers. Further, AF2's confidence metrics selected against models consistent with experimentally determined fold-switching conformations in favor of inconsistent models. Accordingly, these confidence metrics-though suggested to evaluate protein energetics reliably-did not discriminate between low and high energy states of fold-switching proteins. We then evaluated AF2's performance on seven fold-switching proteins outside of its training set, generating >159,000 models in total. Fold switching was accurately predicted in one of seven targets with moderate confidence. Further, AF2 demonstrated no ability to predict alternative conformations of two newly discovered targets without homologs in the set of 93 fold switchers. These results indicate that AF2 has more to learn about the underlying energetics of protein ensembles and highlight the need for further developments of methods that readily predict multiple protein conformations.

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.

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.

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.

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.

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.

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.