Evidence for the principle of minimal frustration in the evolution of protein folding landscapes

Deciphering Structural Traits for Thermal and Kinetic Stability across Protein Family Evolution through Ancestral Sequence Reconstruction

Natural proteins are frequently marginally stable, and an increase in environmental temperature can easily lead to unfolding. As a result, protein engineering to improve protein stability is an area of intensive research. Nonetheless, since there is usually a high degree of structural homology between proteins from thermophilic organisms and their mesophilic counterparts, the identification of structural determinants for thermoadaptation is challenging. Moreover, in many cases, it has become clear that the success of stabilization strategies is often dependent on the evolutionary history of a protein family. In the last few years, the use of ancestral sequence reconstruction (ASR) as a tool for elucidation of the evolutionary history of functional traits of a protein family has gained strength. Here, we used ASR to trace the evolutionary pathways between mesophilic and thermophilic kinases that participate in the biosynthetic pathway of vitamin B1 in bacteria. By combining biophysics approaches, X-ray crystallography, and molecular dynamics simulations, we found that the thermal stability of these enzymes correlates with their kinetic stability, where the highest thermal/kinetic stability is given by an increase in small hydrophobic amino acids that allow a higher number of interatomic hydrophobic contacts, making this type of interaction the main support for stability in this protein architecture. The results highlight the potential benefits of using ASR to explore the evolutionary history of protein sequence and structure to identify traits responsible for the kinetic and thermal stability of any protein architecture.

Thr-to-Ala Mutation Leads to a Larger Aromatic Pair and Reduced Packing Density in α1,α3-Helices during Thioredoxin Cold Adaptation

This study investigates the impact of aromatic-aromatic interactions on the cold adaptation of thioredoxin (Trx), a small redox protein with a conserved Trx-fold structure. Two Trx orthologs, one from the psychrophilic Arctic bacterium Sphingomonas sp. (SpTrx) and the other from the mesophilic Escherichia coli (EcTrx), display distinct aromatic interactions in their α1,α3-helices. SpTrx features a larger Trp11-Phe69 pair, while EcTrx employs a smaller Phe12-Tyr70 pair along with an additional Asp9-Thr66 hydrogen bond. Smaller aromatic residues in SpTrx (Phe-Phe or Phe-Tyr pair) lead to decreased thermal and thermodynamic stabilities, increased conformational flexibility, and reduced enzyme activity. In contrast, EcTrx's thermal stability is primarily influenced by the larger Trp residue, especially in the more hydrophobic Trp-Phe pair compared to the Trp-Tyr pair. Both SpTrx and EcTrx exhibit a strengthening of the Asp-Thr hydrogen bond by a Phe-Tyr pair and a weakening by a Trp-Phe pair. Additionally, the Asp8-Thr65 hydrogen bond in SpTrx contributes to the destabilization of the Phe-Phe pair. Molecular dynamics simulations of SpTrx indicate that a smaller aromatic pair or the Asp-Thr hydrogen bond in the α1,α3-helices further destabilizes the α2-helix across the central β-sheet. Our results suggest that the Thr-to-Ala mutation destabilizes the α1,α3-helices, resulting in a larger aromatic pair and reduced packing density in psychrophilic Trxs during cold adaptation. These findings enhance our understanding of Trx's adaptation to colder temperatures.

Structural conservation in the glutathione binding in Sphingomonas sp. glutaredoxin Grx3 and variations for cold adaptation

Glutaredoxin 3 (Grx3), a redox protein with a thioredoxin-fold structure, maintains structural integrity and glutathione (GSH) binding capabilities across varying habitat temperatures. The cis-Pro loop, essential for GSH binding, relies on the Arg-Asp salt bridge (α2-α3) and Gln-His hydrogen bond (β3-β4) for its conformation. In some psychrophilic Grx3 variants, Arg in α2 is replaced with Tyr, and His in β4 is replaced with Phe. This study examines the roles of these bonds in Grx3's structure, function, and cold adaptation, using SpGrx3 from the Arctic bacterium Sphingomonas sp. Despite its cold habitat, SpGrx3 maintains the Arg51-Asp69 salt bridge and Gln56-His63 hydrogen bond. The R51Y substitution disrupts the α2-α3 salt bridge, while the H63F and H63Y substitutions hinder the salt bridge through cation-π interactions with Arg51, involving Phe63/Tyr63, thereby enhancing flexibility. Conversely, mutations that disrupt the hydrogen bond (Q56A, H63A, and H63F) reduce thermal stability. In the psychrophilic Grx3 configuration A48T/R51Y/H63F, a Thr48-Gln56 hydrogen bond stabilizes the cis-Pro loop, enhancing flexibility by disrupting both bonds. Furthermore, all mutants exhibit reduced α-helical content and catalytic efficiency. In summary, the highly conserved Arg51-Asp69 salt bridge and Gln56-His63 hydrogen bond are crucial for stabilizing the cis-Pro loop and catalytic activity in SpGrx3. His63 is favored as it avoids cation-π interactions with Arg51, unlike Phe63/Tyr63. Psychrophilic Grx3 variants have adapted to cold environments by reducing GSH binding and increasing structural flexibility. These findings deepen our understanding of the structural conservation in Grx3 for GSH binding and the critical alterations required for cold adaptation.

Surface frustration re-patterning underlies the structural landscape and evolvability of fungal orphan candidate effectors

Pathogens secrete effector proteins to subvert host physiology and cause disease. Effectors are engaged in a molecular arms race with the host resulting in conflicting evolutionary constraints to manipulate host cells without triggering immune responses. The molecular mechanisms allowing effectors to be at the same time robust and evolvable remain largely enigmatic. Here, we show that 62 conserved structure-related families encompass the majority of fungal orphan effector candidates in the Pezizomycotina subphylum. These effectors diversified through changes in patterns of thermodynamic frustration at surface residues. The underlying mutations tended to increase the robustness of the overall effector protein structure while switching potential binding interfaces. This mechanism could explain how conserved effector families maintained biological activity over long evolutionary timespans in different host environments and provides a model for the emergence of sequence-unrelated effector families with conserved structures.

Metal-binding and circular permutation-dependent thermodynamic and kinetic stability of azurin

Native topology is known to determine the folding kinetics and the energy landscape of proteins. Furthermore, the circular permutation (CP) of proteins alters the order of the secondary structure connectivity while retaining the three-dimensional structure, making it an elegant and powerful approach to altering native topology. Previous studies elucidated the influence of CP in proteins with different folds such as Greek key β-barrel, β-sandwich, β-α-β, and all α-Greek key. CP mainly affects the protein stability and unfolding kinetics, while folding kinetics remains mostly unaltered. However, the effect of CP on metalloproteins is yet to be elaborately studied. The active site of metalloproteins poses an additional complexity in studying protein folding. Here, we investigate a CP variant (cpN42) of azurin-in both metal-free and metal-bound (holo) forms. As observed earlier in other proteins, apo-forms of wild-type (WT) and cpN42 fold with similar rates. In contrast, zinc-binding accelerates the folding of WT but decelerates the folding of cpN42. On zinc-binding, the spontaneous folding rate of WT increases by >250 times that of cpN42, which is unprecedented and the highest for any CP to date. On the other hand, zinc-binding reduces the spontaneous unfolding rate of cpN42 by ~100 times, making the WT and CP azurins unfold at similar rates. Our study demonstrates metal binding as a novel way to modulate the unfolding and folding rates of CPs compared to their WT counterparts. We hope our study increases the understanding of the effect of CP on the folding mechanism and energy landscape of metalloproteins.

Release of frustration drives corneal amyloid disaggregation by brain chaperone

TGFBI-related corneal dystrophy (CD) is characterized by the accumulation of insoluble protein deposits in the corneal tissues, eventually leading to progressive corneal opacity. Here we show that ATP-independent amyloid-β chaperone L-PGDS can effectively disaggregate corneal amyloids in surgically excised human cornea of TGFBI-CD patients and release trapped amyloid hallmark proteins. Since the mechanism of amyloid disassembly by ATP-independent chaperones is unknown, we reconstructed atomic models of the amyloids self-assembled from TGFBIp-derived peptides and their complex with L-PGDS using cryo-EM and NMR. We show that L-PGDS specifically recognizes structurally frustrated regions in the amyloids and releases those frustrations. The released free energy increases the chaperone's binding affinity to amyloids, resulting in local restructuring and breakage of amyloids to protofibrils. Our mechanistic model provides insights into the alternative source of energy utilized by ATP-independent disaggregases and highlights the possibility of using these chaperones as treatment strategies for different types of amyloid-related diseases.

Enhanced statistical sampling reveals microscopic complexity in the talin mechanosensor folding energy landscape

Statistical mechanics can describe the major conformational ensembles determining the equilibrium free-energy landscape of a folding protein. The challenge is to capture the full repertoire of low-occurrence conformations separated by high kinetic barriers that define complex landscapes. Computationally, enhanced sampling methods accelerate the exploration of molecular rare events. However, accessing the entire protein's conformational space in equilibrium experiments requires technological developments to enable extended observation times. We developed single-molecule magnetic tweezers to capture over a million individual transitions as a single talin protein unfolds and refolds under force in equilibrium. When observed at classically-probed timescales, talin folds in an apparently uncomplicated two-state manner. As the sampling time extends from minutes to days, the underlying energy landscape exhibits gradually larger signatures of complexity, involving a finite number of well-defined rare conformations. A fluctuation analysis allows us to propose plausible structures of each low-probability conformational state. The physiological relevance of each distinct conformation can be connected to the binding of the cytoskeletal protein vinculin, suggesting an extra layer of complexity in talin-mediated mechanotransduction. More generally, our experiments directly test the fundamental notion that equilibrium dynamics depend on the observation timescale.

Illuminating the "Twilight Zone": Advances in Difficult Protein Modeling

Homology modeling was long considered a method of choice in tertiary protein structure prediction. However, it used to provide models of acceptable quality only when templates with appreciable sequence identity with a target could be found. The threshold value was long assumed to be around 20-30%. Below this level, obtained sequence identity was getting dangerously close to values that can be obtained by chance, after aligning any random, unrelated sequences. In these cases, other approaches, including ab initio folding simulations or fragment assembly, were usually employed. The most recent editions of the CASP and CAMEO community-wide modeling methods assessment have brought some surprising outcomes, proving that much more clues can be inferred from protein sequence analyses than previously thought. In this chapter, we focus on recent advances in the field of difficult protein modeling, pushing the threshold deep into the "twilight zone", with particular attention devoted to improvements in applications of machine learning and model evaluation.

Probing the origin of prion protein misfolding via reconstruction of ancestral proteins

Prion diseases are fatal neurodegenerative diseases caused by pathogenic misfolding of the prion protein, PrP. They are transmissible between hosts, and sometimes between different species, as with transmission of bovine spongiform encephalopathy to humans. Although PrP is found in a wide range of vertebrates, prion diseases are seen only in certain mammals, suggesting that infectious misfolding was a recent evolutionary development. To explore when PrP acquired the ability to misfold infectiously, we reconstructed the sequences of ancestral versions of PrP from the last common primate, primate-rodent, artiodactyl, placental, bird, and amniote. Recombinant ancestral PrPs were then tested for their ability to form β-sheet aggregates, either spontaneously or when seeded with infectious prion strains from human, cervid, or rodent species. The ability to aggregate developed after the oldest ancestor (last common amniote), and aggregation capabilities diverged along evolutionary pathways consistent with modern-day susceptibilities. Ancestral bird PrP could not be seeded with modern-day prions, just as modern-day birds are resistant to prion disease. Computational modeling of structures suggested that differences in helix 2 could account for the resistance of ancestral bird PrP to seeding. Interestingly, ancestral primate PrP could be converted by all prion seeds, including both human and cervid prions, raising the possibility that species descended from an ancestral primate have retained the susceptibility to conversion by cervid prions. More generally, the results suggest that susceptibility to prion disease emerged prior to ~100 million years ago, with placental mammals possibly being generally susceptible to disease.

Residue-Frustration-Based Prediction of Protein-Protein Interactions Using Machine Learning

The study of protein-protein interactions (PPIs) is important in understanding the function of proteins. However, it is still a challenge to investigate the transient protein-protein interaction by experiments. Hence, the computational prediction for protein-protein interactions draws growing attention. Statistics-based features have been widely used in the studies of protein structure prediction and protein folding. Due to the scarcity of experimental data of PPI, it is difficult to construct a conventional statistical feature for PPI prediction, and the application of statistics-based features is very limited in this field. In this paper, we explored the application of frustration, a statistical potential, in PPI prediction. By comparing the energetic contribution of the extra stabilization energy from a given residue pair in the native protein with the statistics of the energies, we obtained the residue pair's frustration index. By calculating the number of residue pairs with a high frustration index, the highly frustrated density, a residue-frustration-based feature, was then obtained to describe the tendency of residues to be involved in PPI. Highly frustrated density, as well as structure-based features, were then used to describe protein residues and combined with the long short-term memory (LSTM) neural network to predict PPI residue pairs. Our model correctly predicted 75% dimers when only the top 2‰ residue pairs were selected in each dimer. Our model, which considers the statistics-based features, is significantly different from the models based on the chemical features of residues. We found that frustration can effectively describe the tendency of residue to be involved in PPI. Frustration-based features can replace chemical features to combine with machine learning and realize the better performance of PPI prediction. It reveals the great potential of statistical potential such as frustration in PPI prediction.

Essential roles of buried phenylalanine in the structural stability of thioredoxin from a psychrophilic Arctic bacterium Sphingomonas sp

Thioredoxin (Trx), a small redox protein, exhibits thermal stability at high temperatures regardless of its origin, including psychrophiles. Trxs have a common structure consisting of the central β-sheet flanked by an aliphatic cluster on one side and an aromatic cluster on the other side. Although the roles of aromatic amino acids in the folding and stability of proteins have been studied extensively, the contributions of aromatic residues to the stability and function of Trx, particularly Trxs from cold-adapted organisms, have not been fully elucidated. This study examined the roles of aromatic amino acids in the aromatic cluster of a Trx from the psychrophilic Arctic bacterium Sphingomonas sp. PAMC 26621 (SpTrx). The aromatic cluster of SpTrx was comprised of W11, F26, F69, and F80, in which F26 at the β2 terminus was buried inside. The substitution of tyrosine for F26 changed the SpTrx conformation substantially compared to that of F69 and F80. Further biochemical and spectroscopic investigations on F26 showed that the F26Y, F26W, and F26A mutants resulted in structural instability of SpTrx in both urea- and temperature-induced unfolding and lower insulin reduction activities. The Trx reductase (SpTR) showed lower catalytic efficiencies against F26 mutants compared to the wild-type SpTrx. These results suggest that buried F26 is essential for maintaining the active-site conformation of SpTrx as an oxidoreductase and its structural stability for interactions with SpTR at colder temperatures.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Localization of Energetic Frustration in Proteins

We present a detailed heuristic method to quantify the degree of local energetic frustration manifested by protein molecules. Current applications are realized in computational experiments where a protein structure is visualized highlighting the energetic conflicts or the concordance of the local interactions in that structure. Minimally frustrated linkages highlight the stable folding core of the molecule. Sites of high local frustration, in contrast, often indicate functionally relevant regions such as binding, active, or allosteric sites.

Tracing protein and proteome history with chronologies and networks: folding recapitulates evolution

INTRODUCTION

While the origin and evolution of proteins remain mysterious, advances in evolutionary genomics and systems biology are facilitating the historical exploration of the structure, function and organization of proteins and proteomes. Molecular chronologies are series of time events describing the history of biological systems and subsystems and the rise of biological innovations. Together with time-varying networks, these chronologies provide a window into the past.

AREAS COVERED

Here, we review molecular chronologies and networks built with modern methods of phylogeny reconstruction. We discuss how chronologies of structural domain families uncover the explosive emergence of metabolism, the late rise of translation, the co-evolution of ribosomal proteins and rRNA, and the late development of the ribosomal exit tunnel; events that coincided with a tendency to shorten folding time. Evolving networks described the early emergence of domains and a late 'big bang' of domain combinations.

EXPERT OPINION

Two processes, folding and recruitment appear central to the evolutionary progression. The former increases protein persistence. The later fosters diversity. Chronologically, protein evolution mirrors folding by combining supersecondary structures into domains, developing translation machinery to facilitate folding speed and stability, and enhancing structural complexity by establishing long-distance interactions in novel structural and architectural designs.

Quantifying Frustrations for Molecular Complexes with Noncovalent Interactions

Molecular systems bound together through noncovalent interactions are involved in a lot of life-essential processes such as molecular recognition, signal transduction, and allosteric regulation. While cooperation as an important effect discovered in these systems focuses on the behavior of system's entirety, we need also examine the behavior of individual parts. In this work, using the distortion energy as the descriptor, we quantify frustration as the energetic loss of individual parts due to the formation of nonadditive molecular complexes. The applicability of our approach has been illustrated by a few simple clusters. Our results show that the frustration effect is smaller than the cooperation effect, but same as cooperativity, it can be both positive and negative. The ultimate benefit of a system made of multiple parts is dictated by the balance between the cooperative behavior among parts and the sacrifice from its individuals. This conflicting yet complementary conceptual pair of cooperation and frustration provides us with a different perspective from the systems' viewpoint for molecular complexes. This new angle of appreciating molecular complexes can be applied in conformational changes, enzymatic catalysis, and many more.

Evolution, folding, and design of TIM barrels and related proteins

Proteins are chief actors in life that perform a myriad of exquisite functions. This diversity has been enabled through the evolution and diversification of protein folds. Analysis of sequences and structures strongly suggest that numerous protein pieces have been reused as building blocks and propagated to many modern folds. This information can be traced to understand how the protein world has diversified. In this review, we discuss the latest advances in the analysis of protein evolutionary units, and we use as a model system one of the most abundant and versatile topologies, the TIM-barrel fold, to highlight the existing common principles that interconnect protein evolution, structure, folding, function, and design.

Anomalous structural dynamics of minimally frustrated residues in cardiac troponin C triggers hypertrophic cardiomyopathy

Cardiac TnC (cTnC) is highly conserved among mammals, and genetic variants can result in disease by perturbing Ca2+-regulation of myocardial contraction. Here, we report the molecular basis of a human mutation in cTnC's αD-helix (TNNC1-p.C84Y) that impacts conformational dynamics of the D/E central-linker and sampling of discrete states in the N-domain, favoring the "primed" state associated with Ca2+ binding. We demonstrate cTnC's αD-helix normally functions as a central hub that controls minimally frustrated interactions, maintaining evolutionarily conserved rigidity of the N-domain. αD-helix perturbation remotely alters conformational dynamics of the N-domain, compromising its structural rigidity. Transgenic mice carrying this cTnC mutation exhibit altered dynamics of sarcomere function and hypertrophic cardiomyopathy. Together, our data suggest that disruption of evolutionary conserved molecular frustration networks by a myofilament protein mutation may ultimately compromise contractile performance and trigger hypertrophic cardiomyopathy.

Thermal destabilization mechanism of cytochrome c' from psychrophilic Shewanella violacea

Cytochrome c' is a nitric oxide (NO)-binding heme protein found in Gram negative bacteria. The thermal stability of psychrophilic Shewanella violacea cytochrome c' (SVCP) is lower than those of its homologues from other 2 psychrophilic Shewanella species, indicating that thermal destabilization mechanism for low-temperature adaptation accumulates in SVCP. In order to understand this mechanism at the amino acid level, here the stability and function of SVCP variants, modeled using the 2 homologues, were examined. The variants exhibited increased stability, and they bound NO similar to the wild type. The vulnerability as to the SVCP stability could be attributed to less hydrogen bond at the subunit interface, more flexible loop structure, and less salt bridge on the protein surface, which appear to be its destabilization mechanism. This study provides an example for controlling stability without spoiling function in psychrophilic proteins.

Local Interactions That Contribute Minimal Frustration Determine Foldability

Earlier experiments suggest that the evolutionary information (conservation and coevolution) encoded in protein sequences is necessary and sufficient to specify the fold of a protein family. However, there is no computational work to quantify the effect of such evolutionary information on the folding process. Here we explore the role of early folding steps for sequences designed using coevolution and conservation through a combination of computational and experimental methods. We simulated a repertoire of native and designed WW domain sequences to analyze early local contact formation and found that the N-terminal β-hairpin turn would not form correctly due to strong non-native local contacts in unfoldable sequences. Through a maximum likelihood approach, we identified five local contacts that play a critical role in folding, suggesting that a small subset of amino acid pairs can be used to solve the "needle in the haystack" problem to design foldable sequences. Thus, using the contact probability of those five local contacts that form during the early stage of folding, we built a classification model that predicts the foldability of a WW sequence with 81% accuracy. This classification model was used to redesign WW domain sequences that could not fold due to frustration and make them foldable by introducing a few mutations that led to the stabilization of these critical local contacts. The experimental analysis shows that a redesigned sequence folds and binds to polyproline peptides with a similar affinity as those observed for native WW domains. Overall, our analysis shows that evolutionary-designed sequences should not only satisfy the folding stability but also ensure a minimally frustrated folding landscape.

Linking molecular evolution to molecular grafting

Molecular grafting is a strategy for the engineering of molecular scaffolds into new functional agents, such as next-generation therapeutics. Despite its wide use, studies so far have focused almost exclusively on demonstrating its utility rather than understanding the factors that lead to either poor or successful grafting outcomes. Here, we examine protein evolution and identify parallels between the natural process of protein functional diversification and the artificial process of molecular grafting. We discuss features of natural proteins that are correlated to innovability-the capacity to acquire new functions-and describe their implications to molecular grafting scaffolds. Disulfide-rich peptides are used as exemplars because they are particularly promising scaffolds onto which new functions can be grafted. This article provides a perspective on why some scaffolds are more suitable for grafting than others, identifying opportunities on how molecular grafting might be improved.

Evolution of frustrated and stabilising contacts in reconstructed ancient proteins

Energetic properties of a protein are a major determinant of its evolutionary fitness. Using a reconstruction algorithm, dating the reconstructed proteins and calculating the interaction network between their amino acids through a coevolutionary approach, we studied how the interactions that stabilise 890 proteins, belonging to five families, evolved for billions of years. In particular, we focused our attention on the network of most strongly attractive contacts and on that of poorly optimised, frustrated contacts. Our results support the idea that the cluster of most attractive interactions extends its size along evolutionary time, but from the data, we cannot conclude that protein stability or that the degree of frustration tends always to decrease.

SWOTein: a structure-based approach to predict stability Strengths and Weaknesses of prOTEINs

MOTIVATION

Although structured proteins adopt their lowest free energy conformation in physiological conditions, the individual residues are generally not in their lowest free energy conformation. Residues that are stability weaknesses are often involved in functional regions, whereas stability strengths ensure local structural stability. The detection of strengths and weaknesses provides key information to guide protein engineering experiments aiming to modulate folding and various functional processes.

RESULTS

We developed the SWOTein predictor which identifies strong and weak residues in proteins on the basis of three types of statistical energy functions describing local interactions along the chain, hydrophobic forces and tertiary interactions. The large-scale analysis of the different types of strengths and weaknesses demonstrated their complementarity and the enhancement of the information they provide. Moreover, a good average correlation was observed between predicted and experimental strengths and weaknesses obtained from native hydrogen exchange data. SWOTein application to three test cases further showed its suitability to predict and interpret strong and weak residues in the context of folding, conformational changes and protein-protein binding. In summary, SWOTein is both fast and accurate and can be applied at small and large scale to analyze and modulate folding and molecular recognition processes.

AVAILABILITY

The SWOTein webserver provides the list of predicted strengths and weaknesses and a protein structure visualization tool that facilitates the interpretation of the predictions. It is freely available for academic use at http://babylone.ulb.ac.be/SWOTein/.

Protein folding stability and binding interactions through the lens of evolution: a dynamical perspective

While the function of a protein depends heavily on its ability to fold into a correct 3D structure, billions of years of evolution have tailored proteins from highly stable objects to flexible molecules as they adapted to environmental changes. Nature maintains the fine balance of protein folding and stability while still evolving towards new function through generations of fine-tuning necessary interactions with other proteins and small molecules. Here we focus on recent computational and experimental studies that shed light onto how evolution molds protein folding and the functional landscape from a conformational dynamics' perspective. Particularly, we explore the importance of dynamic allostery throughout protein evolution and discuss how the protein anisotropic network can give rise to allosteric and epistatic interactions.

Three Recently Diverging Duplicated Methyltransferases Exhibit Substrate-Dependent Regioselectivity Essential for Xantholipin Biosynthesis

Polycyclic xanthones are characterized by highly oxygenated, angular hexacyclic frameworks and exhibit diverse biological activities. Although many of them have been isolated and chemically synthesized, the detailed biosynthetic machinery awaits discovery. Recently, xanthone construction in the xantholipin (1) pathway was shown to involve cryptic demethoxylation. This suggested a rationale for the existence of three O-methyltransferase (OMT) genes in the gene cluster, although there are only two O-methyl groups in the structure of 1. Here, in vivo and in vitro analysis have been used to show that the three paralogous OMTs, XanM1-M3, introduce individual methyl groups at specific points in the biosynthetic pathway. Each OMT can to some extent take over the role of the other OMTs, although they exhibit highly substrate-dependent regiospecificity. In addition, phylogenetic analysis suggests their evolution from a common ancestor. Four putative ancestral proteins were constructed, and one of them performed all the functions of XanM1-M3, while the others possessed more limited catalytic functions. The results suggest that a promiscuous common ancestor may have been able to catalyze all three reactions prior to gene duplication and functional divergence. The characterization of XanM1-M3 expands the enzyme inventory for polycyclic xanthone biosynthesis and suggests novel directed evolution approaches to diversifying natural product pathways.

Frustration and inhomogeneous environments in relaxation of open chains with Ising-type interactions

Frustration can contribute to very slow relaxation times in large open chains, as in spin glasses and in biopolymers. However, frustration may not be sufficient to produce broken ergodicity in finite systems. Here we employ a system-plus-reservoir approach to investigate how strongly inhomogeneous environments and frustration compete in the relaxation of finite open chains. We find a sufficient condition for our inhomogeneous environments to break ergodicity. We use the microscopic model to derive a Markovian quantum master equation for a generic chain with ultrastrong intrachain couplings. We show that this microscopic model avoids a spurious broken ergodicity we find in the phenomenological model. We work out an explicit example of broken ergodicity due to the inhomogeneous environment of an unfrustrated spin chain as far as simulating a recent experiment on protein denaturation (where environment inhomogeneity is especially relevant). We finally show that an inhomogeneous environment can mitigate the effects of frustration-induced degeneracies.

Non-conservation of folding rates in the thioredoxin family reveals degradation of ancestral unassisted-folding

Evolution involves not only adaptation, but also the degradation of superfluous features. Many examples of degradation at the morphological level are known (vestigial organs, for instance). However, the impact of degradation on molecular evolution has been rarely addressed. Thioredoxins serve as general oxidoreductases in all cells. Here, we report extensive mutational analyses on the folding of modern and resurrected ancestral bacterial thioredoxins. Contrary to claims from recent literature, in vitro folding rates in the thioredoxin family are not evolutionarily conserved, but span at least a ∼100-fold range. Furthermore, modern thioredoxin folding is often substantially slower than ancestral thioredoxin folding. Unassisted folding, as probed in vitro, thus emerges as an ancestral vestigial feature that underwent degradation, plausibly upon the evolutionary emergence of efficient cellular folding assistance. More generally, our results provide evidence that degradation of ancestral features shapes, not only morphological evolution, but also the evolution of individual proteins.

Energy Landscapes of Deoxyxylo- and Xylo-Nucleic Acid Octamers

Artificial analogues of the natural nucleic acids have attracted interest as a diverse class of information storage molecules capable of self-replication. In this study, we use the computational potential energy landscape framework to investigate the structural and dynamical properties of xylo- and deoxyxylo-nucleic acids (XyNA and dXyNA), which are derived from their respective RNA and DNA analogues by inversion of a single chiral center in the sugar moiety of the nucleotides. For an octameric XyNA sequence and the analogue dXyNA, we observe facile conformational transitions between a left-handed helix, which is the free energy global minimum, and a ladder-type structure with approximately zero helicity. The competing ensembles are better separated in the dXyNA, making it a more suitable candidate for a molecular switch, whereas the XyNA exhibits additional flexibility. Both energy landscapes exhibit greater frustration than we observe in RNA or DNA, in agreement with the higher degree of optimization expected from the principle of minimal frustration in evolved biomolecules.

Protein adaptation to high hydrostatic pressure: Computational analysis of the structural proteome

Hydrostatic pressure has a vital role in the biological adaptation of the piezophiles, organisms that live under high hydrostatic pressure. However, the mechanisms by which piezophiles are able to adapt their proteins to high hydrostatic pressure is not well understood. One proposed hypothesis is that the volume changes of unfolding (ΔVTot ) for proteins from piezophiles is distinct from those of nonpiezophilic organisms. Since ΔVTot defines pressure dependence of stability, we performed a comprehensive computational analysis of this property for proteins from piezophilic and nonpiezophilic organisms. In addition, we experimentally measured the ΔVTot of acylphosphatases and thioredoxins belonging to piezophilic and nonpiezophilic organisms. Based on this analysis we concluded that there is no difference in ΔVTot for proteins from piezophilic and nonpiezophilic organisms. Finally, we put forward the hypothesis that increased concentrations of osmolytes can provide a systemic increase in pressure stability of proteins from piezophilic organisms and provide experimental thermodynamic evidence in support of this hypothesis.

Protein structure optimization using improved simulated annealing algorithm on a three-dimensional AB off-lattice model

This paper proposed an improved simulated annealing (ISA) algorithm for protein structure optimization based on a three-dimensional AB off-lattice model. In the algorithm, we provided a general formula used for producing initial solution, and designed a multivariable disturbance term, relating to the parameters of simulated annealing and a tuned constant, to generate neighborhood solution. To avoid missing optimal solution, storage operation was performed in searching process. We applied the algorithm to test artificial protein sequences from literature and constructed a benchmark dataset consisting of 10 real protein sequences from the Protein Data Bank (PDB). Otherwise, we generated C_α space-filling model to represent protein folding conformation. The results indicate our algorithm outperforms the five methods before in searching lower energies of artificial protein sequences. In the testing on real proteins, our method can achieve the energy conformations with C_α-RMSD less than 3.0 Å from the PDB structures. Moreover, C_α space-filling model may simulate dynamic change of protein folding conformation at atomic level.

Integrated Computational Approaches and Tools forAllosteric Drug Discovery

Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.

The unfolding transition state of ubiquitin with charged residues has higher energy than that with hydrophobic residues

The native-state structure and folding pathways of a protein are encoded in its amino acid sequence.

Energetic dependencies dictate folding mechanism in a complex protein

Large proteins composed of multiple domains are abundant in all proteomes, but their folding and structural dynamics remain poorly understood. Using single-molecule force spectroscopy, we have defined how stabilizing interfaces among the domains of elongation factor G (EF-G) shape its folding pathway. Contrary to the expectation that multidomain proteins fold sequentially as they emerge from the ribosome, we find that folding cannot be completed until the full protein has been synthesized. This posttranslational folding mechanism results in a propensity for misfolding. It is dictated by an energetic coupling among domains that enables conformational flexibility crucial for EF-G function. EF-G thus provides an example of how distinct biological ends—robust folding and functionally important flexibility—come into conflict during protein biogenesis.

Large proteins with multiple domains are thought to fold cotranslationally to minimize interdomain misfolding. Once folded, domains interact with each other through the formation of extensive interfaces that are important for protein stability and function. However, multidomain protein folding and the energetics of domain interactions remain poorly understood. In elongation factor G (EF-G), a highly conserved protein composed of 5 domains, the 2 N-terminal domains form a stably structured unit cotranslationally. Using single-molecule optical tweezers, we have defined the steps leading to fully folded EF-G. We find that the central domain III of EF-G is highly dynamic and does not fold upon emerging from the ribosome. Surprisingly, a large interface with the N-terminal domains does not contribute to the stability of domain III. Instead, it requires interactions with its folded C-terminal neighbors to be stably structured. Because of the directionality of protein synthesis, this energetic dependency of domain III on its C-terminal neighbors disrupts cotranslational folding and imposes a posttranslational mechanism on the folding of the C-terminal part of EF-G. As a consequence, unfolded domains accumulate during synthesis, leading to the extensive population of misfolded species that interfere with productive folding. Domain III flexibility enables large-scale conformational transitions that are part of the EF-G functional cycle during ribosome translocation. Our results suggest that energetic tuning of domain stabilities, which is likely crucial for EF-G function, complicates the folding of this large multidomain protein.

Sibe: a computation tool to apply protein sequence statistics to predict folding and design in silico

BACKGROUND

Evolutionary information contained in the amino acid sequences of proteins specifies the biological function and fold, but exactly what information contained in the protein sequence drives both of these processes? Considerable progress has been made to answer this fundamental question, but it remains challenging to explore the potential space of cooperative interactions between amino acids. Statistical analysis plays a significant role in studying such interactions and its use has expanded in recent years to studies ranging from coevolution-guided rational protein design to protein folding in silico.

RESULTS

Here we describe a computational tool named Sibe for use in studies of protein sequence, folding, and design using evolutionary coupling between amino acids as a driving factor. In this study, Sibe is used to identify positionally conserved couplings between pairwise amino acids and aid rational protein design. In this process, pairwise couplings are filtered according to the relative entropy computed from the positional conservations and grouped into several 'blocks', which could contribute to driving protein folding and design. A human β2-adrenergic receptor (β2AR) was used to demonstrate that those 'blocks' contribute the rational design for specifying functional residues. Sibe also provides folding modules based on both the positionally conserved couplings and well-established statistical potentials for simulating protein folding in silico and predicting tertiary structure. Our results show that statistically inferences of basic evolutionary principles, such as conservations and coupled-mutations, can be used to rapidly design a diverse set of proteins and study protein folding.

CONCLUSIONS

The developed software Sibe provides a computational tool for systematical analysis from protein primary to its tertiary structure using the evolutionary couplings as a driving factor. Sibe, written in C++, accounts for compatibility with the 'big data' era in biological science, and it primarily focuses on protein sequence analysis, but it is also applicable to extend to other modeling and predictions of experimental measurements.

Protein at liquid solid interfaces: Toward a new paradigm to change the approach to design hybrid protein/solid-state materials

This review gives an overview of protein adsorption at solid/liquid interface. Compared to the other ones, we have focus on three main questions with the point of view of the protein. The first question is related to the kinetic and especially the using of Langmuir model to describe the protein adsorption. The second question is about the concept of hard and soft protein. In this part, we report the protein structural modification induced by adsorption regarding their intrinsic structure. This allows formulating of a new concept to classify the protein to predict their behavior at solid/liquid interface. The last question is related to the protein corona. We give an overview about the soft/hard corona and attempt to make correlation with the concept of hard/soft protein.

Functional analyses of ancestral thioredoxins provide insights into their evolutionary history

Thioredoxin (Trx) is a conserved, cytosolic reductase in all known organisms. The enzyme receives two electrons from NADPH via thioredoxin reductase (TrxR) and passes them on to multiple cellular reductases via disulfide exchange. Despite the ubiquity of thioredoxins in all taxa, little is known about the functions of resurrected ancestral thioredoxins in the context of a modern mesophilic organism. Here, we report on functional in vitro and in vivo analyses of seven resurrected Precambrian thioredoxins, dating back 1–4 billion years, in the Escherichia coli cytoplasm. Using synthetic gene constructs for recombinant expression of the ancestral enzymes, along with thermodynamic and kinetic assays, we show that all ancestral thioredoxins, as today's thioredoxins, exhibit strongly reducing redox potentials, suggesting that thioredoxins served as catalysts of cellular reduction reactions from the beginning of evolution, even before the oxygen catastrophe. A detailed, quantitative characterization of their interactions with the electron donor TrxR from Escherichia coli and the electron acceptor methionine sulfoxide reductase, also from E. coli, strongly hinted that thioredoxins and thioredoxin reductases co-evolved and that the promiscuity of thioredoxins toward downstream electron acceptors was maintained during evolution. In summary, our findings suggest that thioredoxins evolved high specificity for their sole electron donor TrxR while maintaining promiscuity to their multiple electron acceptors.

Superfunneled Energy Landscape of Protein Evolution Unifies the Principles of Protein Evolution, Folding, and Design

Evolution is essential for shaping the biological functions. Darwin proposed the selection as the driving force for evolution upon mutations. While mutations are clear, the quantification of the selection force is still challenging. In this study, we identified and quantified both thermodynamic stability and kinetic accessibility as the selection forces for protein evolution. The protein evolution can be viewed and quantified as a trajectory moving along a superfunneled energy landscape with a line attractor at the bottom. The resulting evolved sequences and structures show strong protein characteristics including the hydrophobic core, high designability, and fast folding. The evolution principle uncovered here is validated on real proteins and sheds light on the protein design.

Protein engineers turned evolutionists-the quest for the optimal starting point

The advent of laboratory directed evolution yielded a fruitful crosstalk between the disciplines of molecular evolution and bio-engineering. Here, we outline recent developments in both disciplines with respect to how one can identify the best starting points for directed evolution, such that highly efficient and robust tailor-made enzymes can be obtained with minimal optimization. Directed evolution studies have highlighted essential features of engineer-able enzymes: highly stable, mutationally robust enzymes with the capacity to accept a broad range of substrates. Robust, evolvable enzymes can be inferred from the natural sequence record. Broad substrate spectrum relates to conformational plasticity and can also be predicted by phylogenetic analyses and/or by computational design. Overall, an increasingly powerful toolkit is becoming available for identifying optimal starting points including network analyses of enzyme superfamilies and other bioinformatics methods.

Electrostatic control of calcineurin's intrinsically-disordered regulatory domain binding to calmodulin

Calcineurin (CaN) is a serine/threonine phosphatase that regulates a variety of physiological and pathophysiological processes in mammalian tissue. The calcineurin (CaN) regulatory domain (RD) is responsible for regulating the enzyme's phosphatase activity, and is believed to be highly-disordered when inhibiting CaN, but undergoes a disorder-to-order transition upon diffusion-limited binding with the regulatory protein calmodulin (CaM). The prevalence of polar and charged amino acids in the regulatory domain (RD) suggests electrostatic interactions are involved in mediating calmodulin (CaM) binding, yet the lack of atomistic-resolution data for the bound complex has stymied efforts to probe how the RD sequence controls its conformational ensemble and long-range attractions contribute to target protein binding. In the present study, we investigated via computational modeling the extent to which electrostatics and structural disorder facilitate CaM/CaN association kinetics. Specifically, we examined several RD constructs that contain the CaM binding region (CAMBR) to characterize the roles of electrostatics versus conformational diversity in controlling diffusion-limited association rates, via microsecond-scale molecular dynamics (MD) and Brownian dynamic (BD) simulations. Our results indicate that the RD amino acid composition and sequence length influence both the dynamic availability of conformations amenable to CaM binding, as well as long-range electrostatic interactions to steer association. These findings provide intriguing insight into the interplay between conformational diversity and electrostatically-driven protein-protein association involving CaN, which are likely to extend to wide-ranging diffusion-limited processes regulated by intrinsically-disordered proteins.

Ancient thioredoxins evolved to modern-day stability-function requirement by altering native state ensemble

Thioredoxins (THRXs)-small globular proteins that reduce other proteins-are ubiquitous in all forms of life, from Archaea to mammals. Although ancestral thioredoxins share sequential and structural similarity with the modern-day (extant) homologues, they exhibit significantly different functional activity and stability. We investigate this puzzle by comparative studies of their (ancient and modern-day THRXs') native state ensemble, as quantified by the dynamic flexibility index (DFI), a metric for the relative resilience of an amino acid to perturbations in the rest of the protein. Clustering proteins using DFI profiles strongly resemble an alternative classification scheme based on their activity and stability. The DFI profiles of the extant proteins are substantially different around the α3, α4 helices and catalytic regions. Likewise, allosteric coupling of the active site with the rest of the protein is different between ancient and extant THRXs, possibly explaining the decreased catalytic activity at low pH with evolution. At a global level, we note that the population of low-flexibility (called hinges) and high-flexibility sites increases with evolution. The heterogeneity (quantified by the variance) in DFI distribution increases with the decrease in the melting temperature typically associated with the evolution of ancient proteins to their modern-day counterparts.This article is part of a discussion meeting issue 'Allostery and molecular machines'.

Frustration, function and folding

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

Self-Referential Encoding on Modules of Anticodon Pairs-Roots of the Biological Flow System

The proposal that the genetic code was formed on the basis of (proto)tRNA Dimer-Directed Protein Synthesis is reviewed and updated. The tRNAs paired through the anticodon loops are an indication on the process. Dimers are considered mimics of the ribosomes-structures that hold tRNAs together and facilitate the transferase reaction, and of the translation process-anticodons are at the same time codons for each other. The primitive protein synthesis system gets stabilized when the product peptides are stable and apt to bind the producers therewith establishing a self-stimulating production cycle. The chronology of amino acid encoding starts with Glycine and Serine, indicating the metabolic support of the Glycine-Serine C1-assimilation pathway, which is also consistent with evidence on origins of bioenergetics mechanisms. Since it is not possible to reach for substrates simpler than C1 and compounds in the identified pathway are apt for generating the other central metabolic routes, it is considered that protein synthesis is the beginning and center of a succession of sink-effective mechanisms that drive the formation and evolution of the metabolic flow system. Plasticity and diversification of proteins construct the cellular system following the orientation given by the flow and implementing it. Nucleic acid monomers participate in bioenergetics and the polymers are conservative memory systems for the synthesis of proteins. Protoplasmic fission is the final sink-effective mechanism, part of cell reproduction, guaranteeing that proteins don't accumulate to saturation, which would trigger inhibition.