A thermodynamic definition of protein domains

Protein domains are conspicuous structural units in globular proteins, and their identification has been a topic of intense biochemical interest dating back to the earliest crystal structures. Numerous disparate domain identification algorithms have been proposed, all involving some combination of visual intuition and/or structure-based decomposition. Instead, we present a rigorous, thermodynamically-based approach that redefines domains as cooperative chain segments. In greater detail, most small proteins fold with high cooperativity, meaning that the equilibrium population is dominated by completely folded and completely unfolded molecules, with a negligible subpopulation of partially folded intermediates. Here, we redefine structural domains in thermodynamic terms as cooperative folding units, based on m-values, which measure the cooperativity of a protein or its substructures. In our analysis, a domain is equated to a contiguous segment of the folded protein whose m-value is largely unaffected when that segment is excised from its parent structure. Defined in this way, a domain is a self-contained cooperative unit; i.e., its cooperativity depends primarily upon intrasegment interactions, not intersegment interactions. Implementing this concept computationally, the domains in a large representative set of proteins were identified; all exhibit consistency with experimental findings. Specifically, our domain divisions correspond to the experimentally determined equilibrium folding intermediates in a set of nine proteins. The approach was also proofed against a representative set of 71 additional proteins, again with confirmatory results. Our reframed interpretation of a protein domain transforms an indeterminate structural phenomenon into a quantifiable molecular property grounded in solution thermodynamics.     

Unfolding free energy of a two-domain transmembrane sugar transport protein

Understanding how an amino acid sequence folds into a functional, three-dimensional structure has proved to be a formidable challenge in biological research, especially for transmembrane proteins with multiple alpha helical domains. Mechanistic folding studies on helical membrane proteins have been limited to unusually stable, single domain proteins such as bacteriorhodopsin. Here, we extend such work to flexible, multidomain proteins and one of the most widespread membrane transporter families, the major facilitator superfamily, thus showing that more complex membrane proteins can be successfully refolded to recover native substrate binding. We determine the unfolding free energy of the two-domain, Escherichia coli galactose transporter, GalP; a bacterial homologue of human glucose transporters. GalP is reversibly unfolded by urea. Urea causes loss of substrate binding and a significant reduction in alpha helical content. Full recovery of helical structure and substrate binding occurs in dodecylmaltoside micelles, and the unfolding free energy can be determined. A linear dependence of this free energy on urea concentration allows the free energy of unfolding in the absence of urea to be determined as +2.5 kcal·mol(-1). Urea has often been found to be a poor denaturant for transmembrane helical structures. We attribute the denaturation of GalP helices by urea to the dynamic nature of the transporter structure allowing denaturant access via the substrate binding pocket, as well as to helical structure that extends beyond the membrane. This study gives insight into the final, critical folding step involving recovery of ligand binding for a multidomain membrane transporter.     

Local and long-range stability in tandemly arrayed tetratricopeptide repeats

The tetratricopeptide repeat (TPR) is a 34-aa alpha-helical motif that occurs in tandem arrays in a variety of different proteins. In natural proteins, the number of TPR motifs ranges from 3 to 16 or more. These arrays function as molecular scaffolds and frequently mediate protein-protein interactions. We have shown that correctly folded TPR domain proteins, exhibiting the typical helix-turn-helix fold, can be designed by arraying tandem repeats of an idealized TPR consensus motif. To date, three designed proteins, CTPR1, CTPR2, and CTPR3 (consensus TPR number of repeats) have been characterized. Their high-resolution crystal structures show that the designed proteins indeed adopt the typical TPR fold, which is specified by the correct positioning of key residues. Here, we present a study of the thermodynamic properties and folding kinetics of this set of designed proteins. Chemical denaturation, monitored by CD and fluorescence, was used to assess the folding and global stability of each protein. NMR-detected amide proton exchange was used to investigate the stability of each construct at a residue-specific level. The results of these studies reveal a stable core, which defines the intrinsic stability of an individual TPR motif. The results also show the relationship between the number of tandem repeats and the overall stability and folding of the protein.     

Folding domain B of protein A on a dynamically partitioned free energy landscape

The B domain of staphylococcal protein A (BdpA) is a small helical protein that has been studied intensively in kinetics experiments and detailed computer simulations that include explicit water. The simulations indicate that BdpA needs to reorganize in crossing the transition barrier to facilitate folding its C-terminal helix (H3) onto the nucleus formed from helices H1 and H2. This process suggests frustration between two partially ordered forms of the protein, but recent φ value measurements indicate that the transition structure is relatively constant over a broad range of temperatures. Here we develop a simplistic model to investigate the folding transition in which properties of the free energy landscape can be quantitatively compared with experimental data. The model is a continuation of the Muñoz–Eaton model to include the intermittency of contacts between structured parts of the protein, and the results compare variations in the landscape with denaturant and temperature to φ value measurements and chevron plots of the kinetic rates. The topography of the model landscape (in particular, the feature of frustration) is consistent with detailed simulations even though variations in the φ values are close to measured values. The transition barrier is smaller than indicated by the chevron data, but it agrees in order of magnitude with a similar α-carbon type of model. Discrepancies with the chevron plots are investigated from the point of view of solvent effects, and an approach is suggested to account for solvent participation in the model.     

Fast-folding alpha-helices as reversible strain absorbers in the muscle protein myomesin

The highly oriented filamentous protein network of muscle constantly experiences significant mechanical load during muscle operation. The dimeric protein myomesin has been identified as an important M-band component supporting the mechanical integrity of the entire sarcomere. Recent structural studies have revealed a long α-helical linker between the C-terminal immunoglobulin (Ig) domains My12 and My13 of myomesin. In this paper, we have used single-molecule force spectroscopy in combination with molecular dynamics simulations to characterize the mechanics of the myomesin dimer comprising immunoglobulin domains My12–My13. We find that at forces of approximately 30 pN the α-helical linker reversibly elongates allowing the molecule to extend by more than the folded extension of a full domain. High-resolution measurements directly reveal the equilibrium folding/unfolding kinetics of the individual helix. We show that α-helix unfolding mechanically protects the molecule homodimerization from dissociation at physiologically relevant forces. As fast and reversible molecular springs the myomesin α-helical linkers are an essential component for the structural integrity of the M band.     

An enzyme-based biosensor for monitoring and engineering protein stability in vivo

Protein stability affects the physiological functions of proteins and is also a desirable trait in many protein engineering tasks, yet improving protein stability is challenging because of limitations in methods for directly monitoring protein stability in cells. Here, we report an in vivo stability biosensor wherein a protein of interest (POI) is inserted into a microbial enzyme (CysG^A) that catalyzes the formation of endogenous fluorescent compounds, thereby coupling POI stability to simple fluorescence readouts. We demonstrate the utility of the biosensor in directed evolution to obtain stabilized, less aggregation-prone variants of two POIs (including nonamyloidogenic variants of human islet amyloid polypeptide). Beyond engineering applications, we exploited our biosensor in deep mutational scanning for experimental delineation of the stability-related contributions of all residues throughout the catalytic domain of a histone H3K4 methyltransferase, thereby revealing its scientifically informative stability landscape. Thus, our highly accessible method for in vivo monitoring of the stability of diverse proteins will facilitate both basic research and applied protein engineering efforts.

Protein stability affects myriad aspects of biochemical and biological research and often appears as a challenge for the application of protein technologies. Most natural proteins are only marginally stable, having free energy values for unfolding as low as 5 to 10 kcal/mol, a level comparable to the energy needed to break only a few hydrogen bonds (1). Although these marginal stabilities enable proteins to be flexible and thereby support their diverse functions, there is a need for at least a minimal stability threshold to support adequately high enough protein folding efficiency for cell survival (2). Evolutionarily, this apparent tension has established a tight balance between increased functionality through accumulation of mutations and the ability to maintain an adequate level of stability (2). Because this balance is delicate, environmental and cellular disturbances—for example, elevated temperature or a limited pool of ligands—can often tip the balance and turn an active protein into a nonfunctional or misfolded, aggregated state (3).It is increasingly appreciated that protein instability is often a major causative factor in human diseases (4). For example, destabilized mutations of the cellular tumor antigen p53 (5) or antioxidative superoxide dismutase 1 (SOD1) (6) are known to cause multiple human diseases. Misfolding or aggregation of specific proteins is also the hallmark of many neurodegenerative diseases, such as amyloid β peptide in Alzheimer''s disease (7), α-synuclein in Parkinson’s disease (8), and polyglutamine in Huntington’s disease (9). Moreover, protein instability is very often a limiting factor in the development of protein technologies including biocatalysts, therapeutic proteins, and de novo protein design. Consider, for example, that natural enzymes cannot usually be directly deployed as biocatalysts; these tools must remain active under continuous stresses like high temperature, high ionic strength, and extreme pH during the industrial process (10) and must retain activity for days or even weeks in some cell-free applications (11). Similarly, therapeutic proteins often suffer from short half-lives in the human body and/or have a highly restricted shelf life (12). Finally, protein design based on the thermodynamic principles is often constrained by poor stability of the target: for example, 34% of the originally designed monomeric fluorescence-activating β-barrel structures were found to be insoluble, 37% were not expressed, and 7% were found to be toxic when expressed (13).Regardless of widespread academic and industrial interest in stabilizing proteins, tools available for improving protein stability remain quite limited. Although computational stability design can be used to predict stabilizing mutations, its accuracy still needs to be substantially improved due to inadequacies in the quality of experimental results in public databases, in the accuracy of functional annotation information, and in the overall performance of the stability predicting algorithms themselves (14). Directed evolution represents another approach to obtain stabilized proteins, but a profound bottleneck for this approach is to establish high-throughput selection or screening strategies to rapidly monitor protein stability in vivo. The current widely used library-based display technologies rely on functional assays, which are by nature only indirect readouts of the stability of an analyte protein (15).By contrast, protein stability biosensors offer a way to directly monitor protein stability in vivo (16–18). Although they have been successfully deployed in various protein stability evolution applications, the available technologies are not universal solutions (i.e., suitable for all proteins). As an example, our recent attempts to distinguish and evolve the in vivo stability of two members of the histone H3 lysine 4 (H3K4) methyltransferase family failed when using several well-established biosensors, including a green fluorescent protein (GFP)-based biosensor (16), an aminoglycoside 3″-adenylyltransferase–based biosensor (17), and a chloramphenicol acetyltransferase–based biosensor (18) (SI Appendix, Fig. S1). These failures in our own work highlight the need to expand the toolbox of high-throughput selection and screening strategies for the directed evolution of protein stability and served as the fundamental motivation for our work.Here, we developed an enzyme-based fluorescent biosensor to monitor and evolve protein stability in vivo. Our strategy is based on insertion of a protein of interest (POI) between two halves of the Escherichia coli uroporphyrinogen-III methyltransferase CysG^A protein (19), which catalyzes the formation of endogenous red fluorescent compounds. Linking protein folding to the activity of CysG^A allows accurate and sensitive measurement of POI stability and solubility. Our biosensor does not require exogenous substrates or any prior structural knowledge or biophysical information about the POI, therefore engendering its use as a general screen for directed evolution of protein stability. We successfully applied our biosensor to identify stabilizing mutations of muscle acylphosphatase and nonamyloidogenic mutants of the human islet amyloid peptide. Combining this biosensor with deep mutational scanning, we systematically profiled the site-specific mutational tolerance and stability of MLL3_SET, the catalytic domain of the H3K4 methyltransferase MLL3 (a member of the mixed lineage leukemia [MLL] family), therefore experimentally characterizing its stability landscape. At a fundamental level, the ability to dissect the molecular basis of protein stability allows the profile of residues that dictate stability to be generated and the stabilization hotspots in proteins to be mapped. Our study demonstrates the utility of our biosensor as a highly accessible, rapid, flexible, and robust tool for monitoring, evolving, and dissecting protein stability in vivo, allowing the improvement in the ability to engineer customized protein and a greater understanding of the relationship between sequence and stability.     

Funneled energy landscape unifies principles of protein binding and evolution

Most proteins have evolved to spontaneously fold into native structure and specifically bind with their partners for the purpose of fulfilling biological functions. According to Darwin, protein sequences evolve through random mutations, and only the fittest survives. The understanding of how the evolutionary selection sculpts the interaction patterns for both biomolecular folding and binding is still challenging. In this study, we incorporated the constraint of functional binding into the selection fitness based on the principle of minimal frustration for the underlying biomolecular interactions. Thermodynamic stability and kinetic accessibility were derived and quantified from a global funneled energy landscape that satisfies the requirements of both the folding into the stable structure and binding with the specific partner. The evolution proceeds via a bowl-like evolution energy landscape in the sequence space with a closed-ring attractor at the bottom. The sequence space is increasingly reduced until this ring attractor is reached. The molecular-interaction patterns responsible for folding and binding are identified from the evolved sequences, respectively. The residual positions participating in the interactions responsible for folding are highly conserved and maintain the hydrophobic core under additional evolutionary constraints of functional binding. The positions responsible for binding constitute a distributed network via coupling conservations that determine the specificity of binding with the partner. This work unifies the principles of protein binding and evolution under minimal frustration and sheds light on the evolutionary design of proteins for functions.

Proteins in nature have a high degree of thermodynamic and kinetic specificities different from random heteropolymers of amino acids (1–3). Except for intrinsically disordered proteins, naturally occurring proteins are believed to evolve to spontaneously fold into stable native structure and specifically bind with partners for fulfilling the biological functions (4–6). Directed evolution, which mimics natural evolution via rounds of mutagenesis and selections in the laboratory, has also successfully obtained desired protein functions (7–11). According to Darwin, protein sequences evolve through random mutations for the fitness (12). The evolutionary constraint to fold into a particular, stable three-dimensional structure has been considered as the fitness to greatly restrict the sequence space of protein evolution (13–18). However, the biological functions of the proteins are often performed through binding with their partners. The evolutionary selection ultimately operates on the functions other than the structures.A protein’s biological function, such as binding/recognition, conformation dynamics, and activity, can be described by its thermodynamics and kinetics, which are determined by the underlying interactions between the residues. The principle of minimal frustration has been fruitful in illustrating how the global pattern of interactions determines thermodynamic stability and kinetic accessibility of protein folding and binding (3, 19–25). The principle requires that energetic conflicts are minimized in folded native states, so that a sequence can spontaneously fold. Because of the functional necessity, naturally occurring sequences are actually in the tradeoff for coding the capacity to simultaneously satisfy stable folding and functional binding. From the view of localized frustration (23–27), naturally occurring proteins maintain a conserved network of minimally frustrated interactions at the hydrophobic core. In contrast, highly frustrated interactions tend to be clustered on the surface, often near binding sites that become less frustrated upon binding. A natural question is how the evolution sculpts the interaction patterns that conflict with the overall folding of minimal frustration but are specific for protein binding.Extensive statistical analysis of the evolutionary information has shown that native structures of protein folding and binding can be reliably predicted from the global pattern of interactions between amino acids extracted from homologous native sequences (NSs) (28–34). This indicates that thermodynamic and kinetic specificities of protein folding and binding are encoded as the evolutionary footprints on the NSs. In this sense, thermodynamic and kinetic specificities should be not only the evolutionary outcomes but also the selection pressures on protein evolution. The proposed selection fitness quantified by the folding requirement of the thermodynamic stability and the kinetic accessibility has successfully evolved sequences and structures of small domains with strong protein characteristics, including the hydrophobic core, high designability, and fast folding (35). The principle of minimal frustration as a rule to quantify the selection fitness has provided the physical mechanism and mathematical formations for the theoretical and computational studies of protein-folding evolution.Different from our previous study, which concentrated on the evolution of individual domain folding (35), here, we incorporated the constraint of functional binding into the selection fitness under the principle of minimal frustration. Thermodynamic stability and kinetic accessibility were derived and quantified from the global funneled energy landscape, which satisfies the requirements of both folding into the stable structure and binding with the specific partner. The evolution under the selection fitness of optimizing both folding and binding requirements is realized through a bowl-like energy landscape with a closed-ring attractor at the bottom. The sequence space is increasingly reduced until this ring attractor is reached. The interaction patterns respectively responsible for the folding and binding are extracted from the evolved sequences. The residual positions participating in the interactions responsible for folding are highly conserved and maintain the hydrophobic core under additional evolutionary constraints of functional binding. The positions responsible for binding constitute a distributed network via coupling conservations of the residual positions. This distributed network with coupling conservations determines the specificity of the binding with the partner, and the interactions involving the positions of the network can be influenced and adjusted depending on the binding partner. This work unifies the principles of protein binding and evolution and provides an evolution strategy to generate evolved sequences similar to naturally occurring sequences.     

Computing protein stabilities from their chain lengths

New amino acid sequences of proteins are being learned at a rapid rate, thanks to modern genomics. The native structures and functions of those proteins can often be inferred using bioinformatics methods. We show here that it is also possible to infer the stabilities and thermal folding properties of proteins, given only simple genomics information: the chain length and the numbers of charged side chains. In particular, our model predicts ΔH(T), ΔS(T), ΔC_p, and ΔF(T) —the folding enthalpy, entropy, heat capacity, and free energy—as functions of temperature T; the denaturant m values in guanidine and urea; the pH-temperature-salt phase diagrams, and the energy of confinement F(s) of the protein inside a cavity of radius s. All combinations of these phase equilibria can also then be computed from that information. As one illustration, we compute the pH and salt conditions that would denature a protein inside a small confined cavity. Because the model is analytical, it is computationally efficient enough that it could be used to automatically annotate whole proteomes with protein stability information.     

Role of structural determinants in folding of the sandwich-like protein Pseudomonas aeruginosa azurin

An invariant substructure that forms two interlocked pairs of neighboring beta-strands occurs in essentially all known sandwich-like proteins. Eight conserved positions in these strands were recently shown to act as structural determinants. To test whether the residues at these invariant positions are conserved for mechanistic (i.e., part of folding nucleus) or energetic (i.e., governing native-state stability) reasons, we characterized the folding behavior of eight point-mutated variants of the sandwich-like protein Pseudomonas aeruginosa apo-azurin. We find a simple relationship among the conserved positions: half of the residues form native-like interactions in the folding transition state, whereas the others do not participate in the folding nucleus but govern high native-state stability. Thus, evolutionary preservation of these specific positions gives both mechanistic and energetic advantages to members of the sandwich-like protein family.     

Designed protein reveals structural determinants of extreme kinetic stability

The design of stable, functional proteins is difficult. Improved design requires a deeper knowledge of the molecular basis for design outcomes and properties. We previously used a bioinformatics and energy function method to design a symmetric superfold protein composed of repeating structural elements with multivalent carbohydrate-binding function, called ThreeFoil. This and similar methods have produced a notably high yield of stable proteins. Using a battery of experimental and computational analyses we show that despite its small size and lack of disulfide bonds, ThreeFoil has remarkably high kinetic stability and its folding is specifically chaperoned by carbohydrate binding. It is also extremely stable against thermal and chemical denaturation and proteolytic degradation. We demonstrate that the kinetic stability can be predicted and modeled using absolute contact order (ACO) and long-range order (LRO), as well as coarse-grained simulations; the stability arises from a topology that includes many long-range contacts which create a large and highly cooperative energy barrier for unfolding and folding. Extensive data from proteomic screens and other experiments reveal that a high ACO/LRO is a general feature of proteins with strong resistances to denaturation and degradation. These results provide tractable approaches for predicting resistance and designing proteins with sufficient topological complexity and long-range interactions to accommodate destabilizing functional features as well as withstand chemical and proteolytic challenge.The design of proteins with a desired stable fold and function is a much sought after goal. Although impressive recent successes have been reported in designing both natural and novel protein functions and/or structures (1–6), design remains difficult, often requiring multiple rounds of iterative improvements (7–10). In depth biophysical characterization of protein design outcomes and an understanding of their molecular basis have been limited, and these are critical for improving future designs. Combining designed function with structure is particularly difficult, in part because functional sites tend to be sources of thermodynamic instability (11, 12) and folding frustration (13–15). We investigate how an approach that considers both structure and function from the outset may be used to overcome such obstacles. Furthermore, we demonstrate how kinetic and related stabilities against denaturation can be rationally designed.A promising emerging paradigm for protein design is the repetition of modular structural elements (1, 2, 5–7, 14, 16–20). This approach can simplify the design process and build on aspects of the evolution of natural repetition in proteins, as well as incorporate the inherent multivalent binding functionality of such structures (1, 21). Internal structural symmetry, resulting from the repetition of smaller elements of structure, is very common in natural proteins, with ∼20% of all protein folds (22) and the majority of the most populated globular protein folds (superfolds) (21) containing internal structural symmetry. Recent design successes, for helical proteins (5, 6), repeat proteins (18, 20, 23) and symmetric superfolds (1, 2, 7, 16, 17, 19, 24–26) recommend the simplification of the design process by using repetitive/symmetric folds as a particularly effective strategy.The β-trefoil superfold is an interesting test case for design by repetition as bioinformatics analysis has revealed multiple and recent instances of the evolution of distinct proteins with this symmetric fold (1). The fold consists of three repeats, each containing four β-strands, and is adopted by numerous superfamilies with highly diverse binding functions (27). Our design of a completely symmetric β-trefoil, ThreeFoil (Fig. 1), used a hypothetical multivalent carbohydrate binding template and mutated 40 of the 141 residues (1). The mutations were based on a combination of consensus design using a limited set of close homologs (to preserve function), and energy scoring using Rosetta (28). The design was successful on the first attempt, producing a soluble, well folded, and functional monomer with very high resistance to structural fluctuations as indicated by high resistance to thermal denaturation and limited amide H/D exchange (1).Open in a separate windowFig. 1.Design of ThreeFoil. (A) ThreeFoil (PDB: 3PG0) illustrating its three identical peptide subdomains (red, green, blue). (B) ThreeFoil’s secondary structure: turn (purple), β-strand/bridge (yellow), and 3/10-helix (magenta) and ligand binding residues indicated by colored circles and insertions shown in red. (C) Comparison of ThreeFoil with the independently designed Symfoil (PDB: 3O4D, 15% sequence identity), shown along (Left) and across (Right) the axis of symmetry. Backbones are colored by RMSD between the two structures (blue to white, 0–5 Å), with insertions in the loops of ThreeFoil relative to Symfoil colored red. ThreeFoil’s bound sodium shown in gray, and bis-Tris, which binds in the conserved carbohydrate binding sites, shown in cyan.Here, we use a battery of biophysical and computational methods to perform an in depth analysis of Threefoil, which shows that it has remarkably slow unfolding and folding kinetics compared with natural and designed proteins due to an unusually high transition state energy barrier. Such kinetic stability against unfolding has been studied little to date. Furthermore, Threefoil is extremely resistant to chemical denaturation and proteolytic degradation. Analyses using Absolute Contact Order (ACO) (29) and Long-Range Order (LRO) (30) as well as Gō model folding simulations (31–33) show that ThreeFoil’s resistance can be explained by the high cooperativity of its folded structure, which includes many long-range interactions. Simulations also show that nonnative interactions or folding frustration arising from protein symmetry (34) do not create long-lived traps during folding or account for the high barrier. They also explain how ligand binding can chaperone folding, which can be an added advantage of designing the fold and function together. Notably, additional analyses using whole proteome screening and other experiments show that proteins with similar resistances as ThreeFoil generally have high ACO/LRO values. Thus, the design method used for ThreeFoil and the strategy of designing folds with many long-range contacts may be useful for designing functional proteins with high resistance to denaturation and degradation, as may be needed for challenging biotechnology applications.     

Structural insights into how vacuolar sorting receptors recognize the sorting determinants of seed storage proteins

In Arabidopsis, vacuolar sorting receptor isoform 1 (VSR1) sorts 12S globulins to the protein storage vacuoles during seed development. Vacuolar sorting is mediated by specific protein–protein interactions between VSR1 and the vacuolar sorting determinant located at the C terminus (ctVSD) on the cargo proteins. Here, we determined the crystal structure of the protease-associated domain of VSR1 (VSR1-PA) in complex with the C-terminal pentapeptide (₄₆₈RVAAA₄₇₂) of cruciferin 1, an isoform of 12S globulins. The ₄₆₈RVA₄₇₀ motif forms a parallel β-sheet with the switch III residues (₁₂₇TMD₁₂₉) of VSR1-PA, and the ₄₇₁AA₄₇₂ motif docks to a cradle formed by the cargo-binding loop (₉₅RGDCYF₁₀₀), making a hydrophobic interaction with Tyr99. The C-terminal carboxyl group of the ctVSD is recognized by forming salt bridges with Arg95. The C-terminal sequences of cruciferin 1 and vicilin-like storage protein 22 were sufficient to redirect the secretory red fluorescent protein (spRFP) to the vacuoles in Arabidopsis protoplasts. Adding a proline residue to the C terminus of the ctVSD and R95M substitution of VSR1 disrupted receptor–cargo interactions in vitro and led to increased secretion of spRFP in Arabidopsis protoplasts. How VSR1-PA recognizes ctVSDs of other storage proteins was modeled. The last three residues of ctVSD prefer hydrophobic residues because they form a hydrophobic cluster with Tyr99 of VSR1-PA. Due to charge–charge interactions, conserved acidic residues, Asp129 and Glu132, around the cargo-binding site should prefer basic residues over acidic ones in the ctVSD. The structural insights gained may be useful in targeting recombinant proteins to the protein storage vacuoles in seeds.

During seed development, storage proteins are deposited in a specialized organelle called the protein storage vacuole (PSV) and are mobilized to provide sources of carbon, nitrogen, and sulfur during germination (1). Seed storage proteins are synthesized as secretory proteins that are translocated into the endoplasmic reticulum (ER). How these proteins are transported to the PSV is not fully understood. In the receptor-mediated sorting pathway, storage proteins are sorted to the vacuoles via sequence-specific interactions with transmembrane sorting receptors (2). According to the latest model, sorting receptors could pick up the cargo proteins as early as in the ER and transport them through the Golgi apparatus to the trans-Golgi network (TGN), which then matures into the prevacuolar compartment (PVC) and PSV (2). Alternatively, storage proteins are concentrated and aggregated at the periphery of the cis-Golgi, where the dense vesicles (DVs) are formed (3, 4). DVs later bud off and fuse with the PVC, which matures into the PSV. Receptor–cargo interaction could play a role in the aggregation of storage proteins. For example, removal of the C-terminal hydrophobic (AFVY) residues of phaseolin, a storage protein of French bean (Phaseolus vulgaris), abolished aggregation of phaseolin and missorted it to the extracellular space (5).There are two families of sorting receptors, namely vacuolar sorting receptors (VSRs) and receptor-homology-transmembrane-RING-H2 (RMR) proteins (6–8). There are seven homologs of VSR and six homologs of RMR in the Arabidopsis thaliana genome. Unlike lysosomal sorting in animal cells that recognizes the posttranslational modification of mannose-6-phosphate (9), vacuolar sorting in yeast and plant cells is mediated by specific protein–protein interactions between the sorting receptors and the cargo proteins (6, 10–19). These sorting receptors recognize sequence-specific information, or vacuolar sorting determinants (VSDs), on the cargo proteins (20, 21). There are two types of VSD, the sequence-specific VSD (ssVSD) and the C-terminal VSD (ctVSD) (22–24). VSRs can recognize both ssVSDs and ctVSDs (6, 15, 25), while RMRs can only recognize ctVSDs (26, 27). ssVSD, often found in acidic hydrolases targeting lytic vacuoles, contains an NPIR motif with the consensus sequence of (N/L)-(P/I/L)-(I/P)-(R/N/S) (28). Mutations in the NPIR motif disrupt receptor–cargo interactions and lead to missorting of cargo proteins (18, 21, 29, 30). Unlike ssVSD that is located at internal sequence positions, ctVSD is only found at the C terminus of cargo proteins. No consensus sequence has been identified for ctVSD, but it is usually rich in hydrophobic residues (20). For example, the AFVY motif at the C terminus of phaseolin was found to be essential for targeting seed proteins to the PSV (31).VSRs are type I transmembrane proteins that contain a protease-associated (PA) domain, a central domain, and three epidermal growth factor (EGF) repeats in the luminal N-terminal region, followed by a single transmembrane domain (TMD) and a C-terminal cytoplasmic tail (Fig. 1A) (6, 12, 32). The PA domain and central domain are involved in sequence-specific interactions with ssVSDs (21, 33). We have previously determined the crystal structure of the PA domain of vacuolar sorting receptor isoform 1 (VSR1-PA) in complex with the ssVSD of barley aleurain (21) and showed that the PA domain is responsible for recognizing the sequences preceding the NPIR motif. Cargo binding induces the C-terminal tail to undergo a swivel motion that could relocate the central domain to cooperate with the PA domain for ssVSD recognition (21). The EGF repeats have unclear functions, but they might regulate the cargo binding by calcium-dependent conformational change of the PA and central domains (33, 34).Open in a separate windowFig. 1.Crystal structure of VSR1-PA in complex with the C-terminal pentapeptide (₄₆₈RVAAA₄₇₂) of CRU1. (A) Domain organization of VSRs. VSR1-NT consists of a protease-associated domain, a central domain, and three EGF repeats. sp, signal peptide. (B) Pull-down assay. E. coli–expressed VSR1-PA was incubated with NHS-resins coupled with the C-terminal peptide sequence of CRU1 (YRVAAA) or with glycine. A tyrosine residue was added to the N terminus of the peptide to facilitate the quantification of peptide concentration using A₂₈₀. After extensive washing to ensure VSR1-PA was not present in the last wash fractions (W), VSR1-PA bound (B) to the resins was analyzed by immunoblot with a VSR1-PA antibody. (C) Cartoon representation of the crystal structure of VSR1-PA in complex with the CRU1 C-terminal sequence, ₄₆₈RVAAA₄₇₂ (yellow). Switch I, II, and III regions and the cargo-binding loop are color-coded green, magenta, salmon, and cyan, respectively. The complex structure determined at pH 6.5 is shown. (D) A close-up view of the detailed receptor–cargo interactions. ₄₆₈RVA₄₇₀ of CRU1 forms a parallel β-sheet with ₁₂₈TMD₁₂₉ of switch III. The last two residues of CRU1, ₄₇₁AA₄₇₂, dock into a cradle formed by the conserved residues in the cargo-binding loop, ₉₅RGDCYF₁₀₀. The backbone conformation of the bound cargo is maintained by a number of backbone–backbone hydrogen bonds (dotted lines). The C-terminal carboxyl group of CRU1 forms salt bridges with Arg95 in the cargo-binding loop. Intermolecular hydrogen bonds and salt bridges are summarized (Right). (E) VSR1-PA undergoes conformational changes upon binding of ₄₆₈RVAAA₄₇₂. In the apo form of VSR1-PA (light blue), the cargo-binding site is occupied by switch III residues, where Glu133 forms salt bridges with Arg95. Cargo binding displaces the switch III residues away. N-terminal residues 20 to 24 that form strand β-1N in the apo form became disordered, making room for Asn46 in the switch II region to move toward and make a hydrogen bond with Met128 of switch III. Switch I residues (25 to 27) straighten up to form an antiparallel β-sheet with β-2. (F) Sequence of VSR1-PA, pumpkin PV72, pea BP-80, and soybean and French bean VSRs were aligned using the program MUSCLE (57). Secondary structure elements of the bound and apo forms of VSR1-PA are indicated above and below the alignment, respectively. Dotted lines indicate residues that are disordered in the crystal structures. Residues are numbered according to the VSR1-PA sequence.The role of VSRs in sorting seed storage proteins has been supported by genetic studies in Arabidopsis. In a pioneer study, Shimada and coworkers showed that the vsr1 knockout mutant missorted the seed storage proteins 12S globulin and 2S albumin to the extracellular space in Arabidopsis seeds (15). Zouhar and coworkers further showed that vsr1vsr3 and vsr1vsr4 double mutants reduced the amount of the mature form of 12S globulin in the PSV, suggesting that VSR1, VSR3, and VSR4 are the sorting receptors for 12S globulin (35). Moreover, tagging the C-terminal 24 residues of β-conglycinin to the C terminus of a secretory green fluorescent protein (GFP) was sufficient to target the fluorescent protein to the PSV in Arabidopsis seeds, while the fluorescent protein was missorted to the extracellular space in the vsr1 mutant (19). Since VSR1 can bind to the C-terminal sequence of both cruciferin 1 (CRU1), an isoform of 12S globulin, and β-conglycinin (15, 19), it is likely that VSR1 recognizes the sorting determinants in these sequences and sorts them to the PSV in seeds.The molecular mechanism of how VSRs recognize the sorting determinants of cargo proteins remains elusive. In this study, we report the crystal structure of the PA domain of VSR1 in complex with the C-terminal pentapeptide (₄₆₈RVAAA₄₇₂) of CRU1. Structural insights into receptor–cargo interaction were supported by mutagenesis and functional studies, which showed that a specific recognition between the VSR and ctVSD is essential for vacuolar sorting.     

Molecular chaperone function of Mia40 triggers consecutive induced folding steps of the substrate in mitochondrial protein import

Several proteins of the mitochondrial intermembrane space are targeted by internal targeting signals. A class of such proteins with α-helical hairpin structure bridged by two intramolecular disulfides is trapped by a Mia40-dependent oxidative process. Here, we describe the oxidative folding mechanism underpinning this process by an exhaustive structural characterization of the protein in all stages and as a complex with Mia40. Two consecutive induced folding steps are at the basis of the protein-trapping process. In the first one, Mia40 functions as a molecular chaperone assisting α-helical folding of the internal targeting signal of the substrate. Subsequently, in a Mia40-independent manner, folding of the second substrate helix is induced by the folded targeting signal functioning as a folding scaffold. The Mia40-induced folding pathway provides a proof of principle for the general concept that internal targeting signals may operate as a folding nucleus upon compartment-specific activation.     

Experimental support for the evolution of symmetric protein architecture from a simple peptide motif

The majority of protein architectures exhibit elements of structural symmetry, and "gene duplication and fusion" is the evolutionary mechanism generally hypothesized to be responsible for their emergence from simple peptide motifs. Despite the central importance of the gene duplication and fusion hypothesis, experimental support for a plausible evolutionary pathway for a specific protein architecture has yet to be effectively demonstrated. To address this question, a unique "top-down symmetric deconstruction" strategy was utilized to successfully identify a simple peptide motif capable of recapitulating, via gene duplication and fusion processes, a symmetric protein architecture (the threefold symmetric β-trefoil fold). The folding properties of intermediary forms in this deconstruction agree precisely with a previously proposed "conserved architecture" model for symmetric protein evolution. Furthermore, a route through foldable sequence-space between the simple peptide motif and extant protein fold is demonstrated. These results provide compelling experimental support for a plausible evolutionary pathway of symmetric protein architecture via gene duplication and fusion processes.     

On the role of frustration in the energy landscapes of allosteric proteins

Natural protein domains must be sufficiently stable to fold but often need to be locally unstable to function. Overall, strong energetic conflicts are minimized in native states satisfying the principle of minimal frustration. Local violations of this principle open up possibilities to form the complex multifunnel energy landscapes needed for large-scale conformational changes. We survey the local frustration patterns of allosteric domains and show that the regions that reconfigure are often enriched in patches of highly frustrated interactions, consistent both with the idea that these locally frustrated regions may act as specific hinges or that proteins may "crack" in these locations. On the other hand, the symmetry of multimeric protein assemblies allows near degeneracy by reconfiguring while maintaining minimally frustrated interactions. We also anecdotally examine some specific examples of complex conformational changes and speculate on the role of frustration in the kinetics of allosteric change.     

Calcium levels in the Golgi complex regulate clustering and apical sorting of GPI-APs in polarized epithelial cells

Glycosylphosphatidylinositol-anchored proteins (GPI-APs) are lipid-associated luminal secretory cargoes selectively sorted to the apical surface of the epithelia where they reside and play diverse vital functions. Cholesterol-dependent clustering of GPI-APs in the Golgi is the key step driving their apical sorting and their further plasma membrane organization and activity; however, the specific machinery involved in this Golgi event is still poorly understood. In this study, we show that the formation of GPI-AP homoclusters (made of single GPI-AP species) in the Golgi relies directly on the levels of calcium within cisternae. We further demonstrate that the TGN calcium/manganese pump, SPCA1, which regulates the calcium concentration within the Golgi, and Cab45, a calcium-binding luminal Golgi resident protein, are essential for the formation of GPI-AP homoclusters in the Golgi and for their subsequent apical sorting. Down-regulation of SPCA1 or Cab45 in polarized epithelial cells impairs the oligomerization of GPI-APs in the Golgi complex and leads to their missorting to the basolateral surface. Overall, our data reveal an unexpected role for calcium in the mechanism of GPI-AP apical sorting in polarized epithelial cells and identify the molecular machinery involved in the clustering of GPI-APs in the Golgi.

Glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are localized on the apical surface of most epithelia, where they exert their physiological functions, which are regulated by their spatiotemporal compartmentalization.In polarized epithelial cells, the organization of GPI-APs at the apical surface is driven by the mechanism of apical sorting, which relies on the formation of GPI-AP homoclusters in the Golgi apparatus (1, 2). GPI-AP homoclusters (containing a single GPI-AP species) form uniquely in the Golgi apparatus of fully polarized cells (and not in nonpolarized cells) in a cholesterol-dependent manner (1, 3, 4). Once formed, GPI-AP homoclusters become insensitive to cholesterol depletion, suggesting that protein–protein interactions stabilize them (1, 2). At the apical membrane, newly arrived homoclusters coalesce into heteroclusters (containing at least two different GPI-AP species) that are sensitive to cholesterol depletion (1). Of importance, in the absence of homoclustering in the Golgi (e.g., in nonpolarized epithelial cells), GPI-APs remain in the form of monomers and dimers and do not cluster at the cell surface (1, 5). Thus, the organization of GPI-APs at the apical plasma membrane of polarized cells strictly depends on clustering mechanisms in the Golgi apparatus allowing their apical sorting. This is different from what was shown in fibroblasts where clustering of GPI-APs occurs from monomer condensation at the plasma membrane, indicating that distinct mechanisms regulate GPI-AP clustering in polarized epithelial cells and fibroblasts (1, 6, 7). Furthermore, in polarized epithelial cells, the spatial organization of clusters also appears to regulate the biological activity of the proteins (1) so that GPI-APs are fully functional only when properly sorted to the apical surface and less active in the case of missorting to the basolateral domain (1, 8, 9). Understanding the mechanism of GPI-AP apical sorting in the Golgi apparatus is therefore crucial to decipher their organization at the plasma membrane and the regulation of their activity. The determinants for protein apical sorting have been difficult to uncover compared to the ones for basolateral sorting (10–14). Besides a role of cholesterol, the molecular factors regulating the clustering-based mechanism of GPI-AP sorting in polarized epithelial cells are unknown. Here, we analyzed the possible role of the actin cytoskeleton and of calcium levels in the Golgi. The actin cytoskeleton is not only critical for the maintenance of the Golgi structure and its mechanical properties but also provides the structural support favoring carrier biogenesis (15–18). The Golgi exit of various cargoes is altered in cells treated with drugs either depolymerizing or stabilizing actin filaments (19, 20), and the post-Golgi trafficking is affected either by the knockdown of the expression of some actin-binding proteins, which regulate actin dynamics, or by the overexpression of their mutants (12, 21–23), all together revealing the critical role of actin dynamics for protein trafficking. Only few studies have shown the involvement of actin remodeling proteins in polarized trafficking, mostly in selectively mediating the apical and basolateral trafficking of transmembrane proteins [refs. 24–26; and reviewed in ref. 27]; thus, it remains unclear whether actin filaments play a role in protein sorting in polarized cells.On the other hand, the Golgi apparatus exhibits high calcium levels that have been revealed to be essential for protein processing and the sorting of some secreted soluble proteins in nonpolarized cells (28–31). Moreover, a functional interplay between the actin cytoskeleton and Golgi calcium in modulating protein sorting in nonpolarized cells has been shown (22).In this study, we report that in epithelial cells, actin perturbation does not impair GPI-AP clustering capacity in the Golgi and therefore their apical sorting. In contrast, we found that the Golgi organization of GPI-APs is drastically perturbed upon calcium depletion and that the amount of calcium in the Golgi cisternae is critical for the formation of GPI-AP homoclusters. We further show that the TGN calcium/manganese pump, SPCA1 (secretory pathway Ca(2+)-ATPase pump type 1), which controls the Golgi calcium concentration (32), and Cab45, a calcium-binding luminal Golgi resident protein previously described to be involved in the sorting of a subset of soluble cargoes (33, 34), are essential for the formation of GPI-APs homoclusters in the Golgi and for their subsequent apical sorting. Indeed, down-regulation of SPCA1 or Cab45 expression impairs the oligomerization of GPI-APs in the Golgi complex and leads to their missorting to the basolateral surface but does not affect apical or basolateral transmembrane proteins. Overall, our data reveal an unexpected role for calcium in the mechanism of GPI-AP apical sorting in polarized epithelial cells and identify the molecular machinery involved in the clustering of GPI-APs in the Golgi.     

Full distance-resolved folding energy landscape of one single protein molecule

Kinetic bulk and single molecule folding experiments characterize barrier properties but the shape of folding landscapes between barrier top and native state is difficult to access. Here, we directly extract the full free energy landscape of a single molecule of the GCN4 leucine zipper using dual beam optical tweezers. To this end, we use deconvolution force spectroscopy to follow an individual molecule’s trajectory with high temporal and spatial resolution. We find a heterogeneous energy landscape of the GCN4 leucine zipper domain. The energy profile is divided into two stable C-terminal heptad repeats and two less stable repeats at the N-terminus. Energies and transition barrier positions were confirmed by single molecule kinetic analysis. We anticipate that deconvolution sampling is a powerful tool for the model-free investigation of protein energy landscapes.     

From the Cover: In-cell thermodynamics and a new role for protein surfaces

There is abundant, physiologically relevant knowledge about protein cores; they are hydrophobic, exquisitely well packed, and nearly all hydrogen bonds are satisfied. An equivalent understanding of protein surfaces has remained elusive because proteins are almost exclusively studied in vitro in simple aqueous solutions. Here, we establish the essential physiological roles played by protein surfaces by measuring the equilibrium thermodynamics and kinetics of protein folding in the complex environment of living Escherichia coli cells, and under physiologically relevant in vitro conditions. Fluorine NMR data on the 7-kDa globular N-terminal SH3 domain of Drosophila signal transduction protein drk (SH3) show that charge–charge interactions are fundamental to protein stability and folding kinetics in cells. Our results contradict predictions from accepted theories of macromolecular crowding and show that cosolutes commonly used to mimic the cellular interior do not yield physiologically relevant information. As such, we provide the foundation for a complete picture of protein chemistry in cells.Classic theories about the effects of complex environments consider only hard-core repulsions (volume exclusion) and so predict entropy-driven protein stabilization (1–3). Here, we use the 7-kDa globular N-terminal SH3 domain of Drosophila signal transduction protein drk (SH3) as a model to test this idea in living cells. SH3 exists in a dynamic equilibrium between the folded state and the unfolded ensemble (4). This two-state behavior (5) is ideal for NMR-based studies of folding. Fluorine labeling (6) of its sole tryptophan leads to only two ¹⁹F resonances (7): one from the folded state, the other from the unfolded ensemble (Fig. 1A). The area under each resonance is proportional to its population, ρ_f and ρ_u, respectively. These populations are used to quantify protein stability via the modified standard state free energy of unfolding,ΔGU,T°′=−RTlnρUρF,[1]where R is the gas constant and T is the absolute temperature. Furthermore, the width at half height of each resonance is proportional to the transverse relaxation rate, which is an approximate measure of intermolecular interactions (8–10). Thus, this simple system yields both quantitative thermodynamic knowledge and information about interactions involving the folded state and the unfolded ensemble.Open in a separate windowFig. 1.Fluorine spectra acquired at 298 K, in buffer (A) and cells (B). The blue trace is from the postexperiment supernatant and shows that the red spectrum arises from protein inside cells. Stability curves (C) in buffer (black), in cells (red and green), and in 100 g/L urea (magenta). In-cell metabolite correction and analysis of uncertainties are discussed in Results and Discussion and Materials and Methods, respectively. Shaded regions are 95% confidence intervals. Error bars for buffer are smaller than the labels and represent the SD of three trials. Error bars for the in-cell data at 273, 298, and 313 K represent the SD of three trials. Stability in buffer (black) and solutions of 100 g/L BSA (blue) and lysozyme (red) at different pH values (D–F). The curve for buffer from C is reproduced in D. The net charges on SH3, BSA, and lysozyme (based on sequence) are shown. Error bars (298 K) represent the SD from three trials. Appearance of new resonances in the pH 3 BSA sample prevented extraction of thermodynamic parameters.To assess the enthalpic (ΔHU°′) and entropic (ΔSU°′) components, we measured the temperature dependence of ΔGU°′. These data were fitted to the integrated Gibbs–Helmholtz equation (11), assuming a constant heat capacity of unfolding, ΔCp,U°:ΔGU,T°′=ΔHU,Tref°′−TΔSU,Tref°′+ΔCp,U°′[T−Tref−T⁡lnTTref],[2]where T_ref is either the melting temperature, T_m (where ρ_f = ρ_u), or the temperature of maximum stability, T_s (where ΔSU°′ = 0) (11).     

Robust folding of a de novo designed ideal protein even with most of the core mutated to valine

Protein design provides a stringent test for our understanding of protein folding. We previously described principles for designing ideal protein structures stabilized by consistent local and nonlocal interactions, based on a set of rules relating local backbone structures to tertiary packing motifs. The principles have made possible the design of protein structures having various topologies with high thermal stability. Whereas nonlocal interactions such as tight hydrophobic core packing have traditionally been considered to be crucial for protein folding and stability, the rules proposed by our previous studies suggest the importance of local backbone structures to protein folding. In this study, we investigated the robustness of folding of de novo designed proteins to the reduction of the hydrophobic core, by extensive mutation of large hydrophobic residues (Leu, Ile) to smaller ones (Val) for one of the designs. Surprisingly, even after 10 Leu and Ile residues were mutated to Val, this mutant with the core mostly filled with Val was found to not be in a molten globule state and fold into the same backbone structure as the original design, with high stability. These results indicate the importance of local backbone structures to the folding ability and high thermal stability of designed proteins and suggest a method for engineering thermally stabilized natural proteins.

The de novo design of protein structures, starting from pioneering work (1, 2), has been achieved in tandem with our understanding of how amino acid sequences determine folded structures (3–16). A breakthrough in protein design methodology was a finding of principles for encoding funnel-shaped energy landscapes into amino acid sequences (7, 10, 17, 18). Based on studies of protein folding, it had been suggested that naturally occurring proteins have evolved to have funnel-shaped energy landscapes toward their folded structures (19–23). However, complicated structures of naturally occurring proteins with nonideal features for folding—for example, kinked α-helices, bulged β-strands, long or strained loops, and buried polar groups—make it difficult to understand how the funnels are encoded in amino acid sequences. By focusing on protein structures without such nonideal features, we proposed principles for designing ideal protein structures stabilized by completely consistent local and nonlocal interactions (24), based on a set of rules relating local backbone structures to preferred tertiary motifs (7, 10). These design rules describe the relation of the lengths or torsion patterns of two secondary structure elements and the connecting loop to favorable packing geometries (SI Appendix, Fig. S1A). The design principles enable to encode strongly funneled energy landscapes into amino acid sequences, by the stabilization of folded structures (positive design) and by the destabilization of nonnative conformations (negative design) due to the restriction of folding conformational space by the rules (SI Appendix, Fig. S1C). In the design procedure, backbone structures for a target topology are generated based on a blueprint (SI Appendix, Fig. S1B), in which either the lengths or backbone torsion patterns of the secondary structures and loops are determined using the rules so that the tertiary motifs present in the target topology are favored, and then amino acid sequences stabilizing the generated backbone structures are designed. The designed amino acid sequences stabilize their folded structures both with nonlocal interactions such as hydrophobic core packing and with local interactions favoring the secondary structures and loops specified in the blueprint, which destabilize a myriad of nonnative topologies through local backbone strain captured by the rules, thereby resulting in funnel-shaped energy landscapes (SI Appendix, Fig. S1C). The principles have enabled the de novo design of ideal protein structures for various topologies with atomic-level accuracy (Fig. 1) (6, 7, 10, 13).Open in a separate windowFig. 1.In silico energy landscapes and far-UV circular dichroism (CD) spectra for 10 de novo designed ideal proteins. (A–E) Five designs by Koga et al. in 2012 (7). (F–I) Four designs by Lin et al. in 2015 (10). (J) Top7 by Kuhlman et al. in 2003 (6). (Top) Design models. (Middle) Energy landscapes obtained from Rosetta ab initio structure prediction simulations (41). Red points represent the lowest energy structures obtained in independent Monte Carlo structure prediction trajectories starting from an extended chain for each sequence; the y axis is the Rosetta all-atom energy; the x axis is the Cα root-mean-square deviation (RMSD) to the design model. Green points represent the lowest energy structures obtained in trajectories starting from the design model. (Bottom) The far-UV CD spectra during thermal denaturation with the melting temperature T_m, which is obtained by fitting to the denaturation curves shown in SI Appendix, Fig. S2.Interestingly, the de novo designs exhibit prominent characteristics in terms of thermal stability when compared with naturally occurring proteins. The circular dichroism (CD) measurements up to 170 °C conducted in this study revealed the melting temperature (T_m), which was above 100 °C for most of the designs (Fig. 1) (6, 7, 10). Therefore, the designs have great potential for use as scaffolds to engineer proteins with specific functions of interest. Indeed, miniprotein structures (∼40 residues) designed de novo according to the rules were applied as scaffolds for creating protein binders specific for influenza hemagglutinin and botulinum neurotoxin, displaying high thermal stability (>70 °C) despite the small size (25).The rules in the principles described above emphasize the importance of local backbone structures not the details of amino acid side chains to protein folding, which is also supported by studies using simple calculations with the hydrophobic-polar lattice model or the snake-cube model (26, 27). On the other hand, it is known that hydrophobic interactions are the dominant driving force for folding (28, 29) and the cores of naturally occurring proteins are tightly packed with hydrophobic amino acid residues (30, 31) like a jigsaw puzzle. Indeed, in our design principles, protein cores were designed to be tightly packed and as “fat” as possible with larger hydrophobic residues so that energy landscapes were sculpted to be deeply funneled into a target topology by lowering its energy (SI Appendix, Fig. S1C).Which factor, the local backbone structures encoded by the rules or the tight core packing with fat hydrophobic residues, contributes more to the generation of funnels in the designs? Here, we studied the contribution of hydrophobic core packing to folding ability and thermal stability by investigating the robustness of folding against the reduction of packing, using the design with the highest thermal stability among our nine de novo designs (Fig. 1, except Top7), Rsmn2x2_5_6 (10). We started to study single-residue mutants from Leu or Ile to Val that prune one carbon atom from the aliphatic side chain, which lose the tight packing like a jigsaw puzzle and decrease the hydrophobicity, and then, we combined the mutations. Consequently, we found that a mutant with 10 residue substitutions of Leu or Ile with Val still has the folding ability and high thermal stability despite its reduced and loosened hydrophobic core packing. This result suggests the importance of the local backbone structures for the folding ability and stability of the de novo designs.