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

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.

A contact-based analysis of local energetic frustration dynamics identifies key residues enabling RfaH fold-switch

Fold-switching enables metamorphic proteins to reversibly interconvert between two highly dissimilar native states to regulate their protein functions. While about 100 proteins have been identified to undergo fold-switching, unveiling the key residues behind this mechanism for each protein remains challenging. Reasoning that fold-switching in proteins is driven by dynamic changes in local energetic frustration, we combined fold-switching simulations generated using simplified structure-based models with frustration analysis to identify key residues involved in this process based on the change in the density of minimally frustrated contacts during refolding. Using this approach to analyze the fold-switch of the bacterial transcription factor RfaH, we identified 20 residues that significantly change their frustration during its fold-switch, some of which have been experimentally and computationally reported in previous works. Our approach, which we developed as an additional module for the FrustratometeR package, highlights the role of local frustration dynamics in protein fold-switching and offers a robust tool to enhance our understanding of other proteins with significant conformational shifts.

An integrative approach to protein sequence design through multiobjective optimization

With recent methodological advances in the field of computational protein design, in particular those based on deep learning, there is an increasing need for frameworks that allow for coherent, direct integration of different models and objective functions into the generative design process. Here we demonstrate how evolutionary multiobjective optimization techniques can be adapted to provide such an approach. With the established Non-dominated Sorting Genetic Algorithm II (NSGA-II) as the optimization framework, we use AlphaFold2 and ProteinMPNN confidence metrics to define the objective space, and a mutation operator composed of ESM-1v and ProteinMPNN to rank and then redesign the least favorable positions. Using the two-state design problem of the foldswitching protein RfaH as an in-depth case study, and PapD and calmodulin as examples of higher-dimensional design problems, we show that the evolutionary multiobjective optimization approach leads to significant reduction in the bias and variance in RfaH native sequence recovery, compared to a direct application of ProteinMPNN. We suggest that this improvement is due to three factors: (i) the use of an informative mutation operator that accelerates the sequence space exploration, (ii) the parallel, iterative design process inherent to the genetic algorithm that improves upon the ProteinMPNN autoregressive sequence decoding scheme, and (iii) the explicit approximation of the Pareto front that leads to optimal design candidates representing diverse tradeoff conditions. We anticipate this approach to be readily adaptable to different models and broadly relevant for protein design tasks with complex specifications.

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.

An integrative approach to protein sequence design through multiobjective optimization

With recent methodological advances in the field of computational protein design, in particular those based on deep learning, there is an increasing need for frameworks that allow for coherent, direct integration of different models and objective functions into the generative design process. Here we demonstrate how evolutionary multiobjective optimization techniques can be adapted to provide such an approach. With the established Non-dominated Sorting Genetic Algorithm II (NSGA-II) as the optimization framework, we use AlphaFold2 and ProteinMPNN confidence metrics to define the objective space, and a mutation operator composed of ESM-1v and ProteinMPNN to rank and then redesign the least favorable positions. Using the multistate design problem of the foldswitching protein RfaH as an in-depth case study, we show that the evolutionary multiobjective optimization approach leads to significant reduction in the bias and variance in RfaH native sequence recovery, compared to a direct application of ProteinMPNN. We suggest that this improvement is due to three factors: (i) the use of an informative mutation operator that accelerates the sequence space exploration, (ii) the parallel, iterative design process inherent to the genetic algorithm that improves upon the ProteinMPNN autoregressive sequence decoding scheme, and (iii) the explicit approximation of the Pareto front that leads to optimal design candidates representing diverse tradeoff conditions. We anticipate this approach to be readily adaptable to different models and broadly relevant for protein design tasks with complex specifications.

Computing Free Energies of Fold-Switching Proteins Using MELD x MD

Some proteins are conformational switches, able to transition between relatively different conformations. To understand what drives them requires computing the free-energy difference ΔGAB between their stable states, A and B. Molecular dynamics (MD) simulations alone are often slow because they require a reaction coordinate and must sample many transitions in between. Here, we show that modeling employing limited data (MELD) x MD on known endstates A and B is accurate and efficient because it does not require passing over barriers or knowing reaction coordinates. We validate this method on two problems: (1) it gives correct relative populations of α and β conformers for small designed chameleon sequences of protein G; and (2) it correctly predicts the conformations of the C-terminal domain (CTD) of RfaH. Free-energy methods like MELD x MD can often resolve structures that confuse machine-learning (ML) methods.

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.

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.

Exploring the structural acrobatics of fold-switching proteins using simplified structure-based models

Metamorphic proteins are a paradigm of the protein folding process, by encoding two or more native states, highly dissimilar in terms of their secondary, tertiary, and even quaternary structure, on a single amino acid sequence. Moreover, these proteins structurally interconvert between these native states in a reversible manner at biologically relevant timescales as a result of different environmental cues. The large-scale rearrangements experienced by these proteins, and their sometimes high mass interacting partners that trigger their metamorphosis, makes the computational and experimental study of their structural interconversion challenging. Here, we present our efforts in studying the refolding landscapes of two quintessential metamorphic proteins, RfaH and KaiB, using simplified dual-basin structure-based models (SBMs), rigorously footed on the energy landscape theory of protein folding and the principle of minimal frustration. By using coarse-grained models in which the native contacts and bonded interactions extracted from the available experimental structures of the two native states of RfaH and KaiB are merged into a single Hamiltonian, dual-basin SBM models can be generated and savvily calibrated to explore their fold-switch in a reversible manner in molecular dynamics simulations. We also describe how some of the insights offered by these simulations have driven the design of experiments and the validation of the conformational ensembles and refolding routes observed using this simple and computationally efficient models.

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.

Coevolution-derived native and non-native contacts determine the emergence of a novel fold in a universally conserved family of transcription factors

The NusG protein family is structurally and functionally conserved in all domains of life. Its members directly bind RNA polymerases and regulate transcription processivity and termination. RfaH, a divergent sub-family in its evolutionary history, is known for displaying distinct features than those in NusG proteins, which allows them to regulate the expression of virulence factors in enterobacteria in a DNA sequence-dependent manner. A striking feature is its structural interconversion between an active fold, which is the canonical NusG three-dimensional structure, and an autoinhibited fold, which is distinctively novel. How this novel fold is encoded within RfaH sequence to encode a metamorphic protein remains elusive. In this work, we used publicly available genomic RfaH protein sequences to construct a complete multiple sequence alignment, which was further augmented with metagenomic sequences and curated by predicting their secondary structure propensities using JPred. Coevolving pairs of residues were calculated from these sequences using plmDCA and GREMLIN, which allowed us to detect the enrichment of key metamorphic contacts after sequence filtering. Finally, we combined our coevolutionary predictions with molecular dynamics to demonstrate that these interactions are sufficient to predict the structures of both native folds, where coevolutionary-derived non-native contacts may play a key role in achieving the compact RfaH novel fold. All in all, emergent coevolutionary signals found within RfaH sequences encode the autoinhibited and active folds of this protein, shedding light on the key interactions responsible for the action of this metamorphic protein.

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.

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.

The N-terminal domain of RfaH plays an active role in protein fold-switching

The bacterial elongation factor RfaH promotes the expression of virulence factors by specifically binding to RNA polymerases (RNAP) paused at a DNA signal. This behavior is unlike that of its paralog NusG, the major representative of the protein family to which RfaH belongs. Both proteins have an N-terminal domain (NTD) bearing an RNAP binding site, yet NusG C-terminal domain (CTD) is folded as a β-barrel while RfaH CTD is forming an α-hairpin blocking such site. Upon recognition of the specific DNA exposed by RNAP, RfaH is activated via interdomain dissociation and complete CTD structural rearrangement into a β-barrel structurally identical to NusG CTD. Although RfaH transformation has been extensively characterized computationally, little attention has been given to the role of the NTD in the fold-switching process, as its structure remains unchanged. Here, we used Associative Water-mediated Structure and Energy Model (AWSEM) molecular dynamics to characterize the transformation of RfaH, spotlighting the sequence-dependent effects of NTD on CTD fold stabilization. Umbrella sampling simulations guided by native contacts recapitulate the thermodynamic equilibrium experimentally observed for RfaH and its isolated CTD. Temperature refolding simulations of full-length RfaH show a high success towards α-folded CTD, whereas the NTD interferes with βCTD folding, becoming trapped in a β-barrel intermediate. Meanwhile, NusG CTD refolding is unaffected by the presence of RfaH NTD, showing that these NTD-CTD interactions are encoded in RfaH sequence. Altogether, these results suggest that the NTD of RfaH favors the α-folded RfaH by specifically orienting the αCTD upon interdomain binding and by favoring β-barrel rupture into an intermediate from which fold-switching proceeds.

Proteins commonly adopt a single three-dimensional structure that is required for biological function. Nevertheless, proteins are not isolated in the cell, and the presence of binding partners can give rise to alternate structural configurations. Metamorphic proteins represent an extreme case of the latter, by folding into at least two well-defined configurations that are both structurally and functionally different. For RfaH, a virulence factor in enterobacteria, two distinct folds are found: an autoinhibited state in which its two protein domains strongly interact, and an active state in which these domains dissociate due to a specific DNA signal on RNA polymerases. This activation is accompanied by the refolding of the C-terminal domain (CTD) from an α-helical structure to a β-barrel. Our work employs computational simulations to explore the role of the N-terminal domain (NTD) in regulating the metamorphic behavior of RfaH, determining that this domain has a major part in orienting and binding to the CTD in its α-helical fold, and in stabilizing an intermediate state instead of the fully folded β-barrel. These results suggest that the NTD not only participates in stabilizing the autoinhibited state, but also aids in fold-switching back to it after active RfaH is released from RNA polymerase.