Structure and dynamics of de novo proteins from a designed superfamily of 4-helix bundles

Design of complicated all-α protein structures

A wide range of de novo protein structure designs have been achieved, but the complexity of naturally occurring protein structures is still far beyond these designs. Here, to expand the diversity and complexity of de novo designed protein structures, we sought to develop a method for designing 'difficult-to-describe' α-helical protein structures composed of irregularly aligned α-helices like globins. Backbone structure libraries consisting of a myriad of α-helical structures with five or six helices were generated by combining 18 helix-loop-helix motifs and canonical α-helices, and five distinct topologies were selected for de novo design. The designs were found to be monomeric with high thermal stability in solution and fold into the target topologies with atomic accuracy. This study demonstrated that complicated α-helical proteins are created using typical building blocks. The method we developed will enable us to explore the universe of protein structures for designing novel functional proteins.

Rigidifying a De Novo Enzyme Increases Activity and Induces a Negative Activation Heat Capacity

Conformational sampling profoundly impacts the overall activity and temperature dependence of enzymes. Peroxidases have emerged as versatile platforms for high-value biocatalysis owing to their broad palette of potential biotransformations. Here, we explore the role of conformational sampling in mediating activity in the de novo peroxidase C45. We demonstrate that 2,2,2-triflouoroethanol (TFE) affects the equilibrium of enzyme conformational states, tending toward a more globally rigid structure. This is correlated with increases in both stability and activity. Notably, these effects are concomitant with the emergence of curvature in the temperature-activity profile, trading off activity gains at ambient temperature with losses at high temperatures. We apply macromolecular rate theory (MMRT) to understand enzyme temperature dependence data. These data point to an increase in protein rigidity associated with a difference in the distribution of protein dynamics between the ground and transition states. We compare the thermodynamics of the de novo enzyme activity to those of a natural peroxidase, horseradish peroxidase. We find that the native enzyme resembles the rigidified de novo enzyme in terms of the thermodynamics of enzyme catalysis and the putative distribution of protein dynamics between the ground and transition states. The addition of TFE apparently causes C45 to behave more like the natural enzyme. Our data suggest robust, generic strategies for improving biocatalytic activity by manipulating protein rigidity; for functional de novo protein catalysts in particular, this can provide more enzyme-like catalysts without further rational engineering, computational redesign, or directed evolution.

Chimeric Claudins: A New Tool to Study Tight Junction Structure and Function

The tight junction (TJ) is a structure composed of multiple proteins, both cytosolic and membranal, responsible for cell–cell adhesion in polarized endothelium and epithelium. The TJ is intimately connected to the cytoskeleton and plays a role in development and homeostasis. Among the TJ’s membrane proteins, claudins (CLDNs) are key to establishing blood–tissue barriers that protect organismal physiology. Recently, several crystal structures have been reported for detergent extracted recombinant CLDNs. These structural advances lack direct evidence to support quaternary structure of CLDNs. In this article, we have employed protein-engineering principles to create detergent-independent chimeric CLDNs, a combination of a 4-helix bundle soluble monomeric protein (PDB ID: 2jua) and the apical—50% of human CLDN1, the extracellular domain that is responsible for cell–cell adhesion. Maltose-binding protein-fused chimeric CLDNs (MBP-CCs) used in this study are soluble proteins that retain structural and functional aspects of native CLDNs. Here, we report the biophysical characterization of the structure and function of MBP-CCs. MBP-fused epithelial cadherin (MBP-eCAD) is used as a control and point of comparison of a well-characterized cell-adhesion molecule. Our synthetic strategy may benefit other families of 4-α-helix membrane proteins, including tetraspanins, connexins, pannexins, innexins, and more.

De novo proteins from random sequences through in vitro evolution

Natural proteins are the result of billions of years of evolution. The earliest predecessors of today's proteins are believed to have emerged from random polypeptides. While we have no means to determine how this process exactly happened, there is great interest in understanding how it reasonably could have happened. We are reviewing how researchers have utilized in vitro selection and molecular evolution methods to investigate plausible scenarios for the emergence of early functional proteins. The studies range from analyzing general properties and structural features of unevolved random polypeptides to isolating de novo proteins with specific functions from synthetic randomized sequence libraries or generating novel proteins by combining evolution with rational design. While the results are exciting, more work is needed to fully unravel the mechanisms that seeded protein-dominated biology.

A novel type of colistin resistance genes selected from random sequence space

Antibiotic resistance is a rapidly increasing medical problem that severely limits the success of antibiotic treatments, and the identification of resistance determinants is key for surveillance and control of resistance dissemination. Horizontal transfer is the dominant mechanism for spread of resistance genes between bacteria but little is known about the original emergence of resistance genes. Here, we examined experimentally if random sequences can generate novel antibiotic resistance determinants de novo. By utilizing highly diverse expression libraries encoding random sequences to select for open reading frames that confer resistance to the last-resort antibiotic colistin in Escherichia coli, six de novocolistin resistance conferring peptides (Dcr) were identified. The peptides act via direct interactions with the sensor kinase PmrB (also termed BasS in E. coli), causing an activation of the PmrAB two-component system (TCS), modification of the lipid A domain of lipopolysaccharide and subsequent colistin resistance. This kinase-activation was extended to other TCS by generation of chimeric sensor kinases. Our results demonstrate that peptides with novel activities mediated via specific peptide-protein interactions in the transmembrane domain of a sensory transducer can be selected de novo, suggesting that the origination of such peptides from non-coding regions is conceivable. In addition, we identified a novel class of resistance determinants for a key antibiotic that is used as a last resort treatment for several significant pathogens. The high-level resistance provided at low expression levels, absence of significant growth defects and the functionality of Dcr peptides across different genera suggest that this class of peptides could potentially evolve as bona fide resistance determinants in natura.

We expressed over 100 million randomly generated DNA sequences in Escherichia coli and selected 6 variants that encode peptides that provide resistance to the last-resort antibiotic colistin. We show that the selected peptides are auxiliary activators of the two-component system PmrAB, and that resistance is mediated via modifications of the cell envelope causing decreased antibiotic uptake. This is the first example where random expression libraries have been employed to select for peptides that perform an activating function by direct peptide-protein interactions in vivo, adding support to the idea that non-coding DNA can serve as a substrate for de novo gene evolution. Additionally, the described peptides expand the narrow list of colistin resistance genes and further analyses of clinical isolates will be necessary to determine if similar resistance determinants have evolved in natura.

Design of a Fe4 S4 cluster into the core of a de novo four-helix bundle

We explore the capacity of the de novo protein, S824, to incorporate a multinuclear iron-sulfur cluster within the core of a single-chain four-helix bundle. This topology has a high intrinsic designability because sequences are constrained largely by the pattern of hydrophobic and hydrophilic amino acids, thereby allowing for the extensive substitution of individual side chains. Libraries of novel proteins based on these constraints have surprising functional potential and have been shown to complement the deletion of essential genes in E. coli. Our structure-based design of four first-shell cysteine ligands, one per helix, in S824 resulted in successful incorporation of a cubane Fe₄ S₄ cluster into the protein core. A number of challenges were encountered during the design and characterization process, including nonspecific metal-induced aggregation and the presence of competing metal-cluster stoichiometries. The introduction of buried iron-sulfur clusters into the helical bundle is an initial step toward converting libraries of designed structures into functional de novo proteins with catalytic or electron-transfer functionalities.

Stanley E, H. Hecht M. Harnessing synthetic biology to enhance heterologous protein expression

The ability to express heterologous proteins in microbial hosts is crucial for many areas of research and technology. In most cases, however, successful expression and purification of the desired protein require fusion to another protein. To date, all fusion partners have been chosen from natural sequences, which evolved for other purposes, and may not be optimal fusion partners. However, the rise of synthetic biology and protein design make it possible to design and optimize fusion proteins using novel sequences that did not arise in nature. Here, we describe a series of De novo Expression Enhancer Proteins (DEEPs) that facilitate high-level expression and facile purification of heterologous proteins and peptides. To test the DEEP system, a de novo protein was fused to several target proteins covering a range of sizes and solubilities. In all cases, fusions to DEEP outperformed fusions to SUMO, a commonly used natural fusion partner. The availability of novel proteins that can be engineered for specific fusion applications could be beneficial to enhance the expression of a wide range of heterologous proteins.

A Strategy for Combinatorial Cavity Design in De Novo Proteins

Protein sequence space is vast; nature uses only an infinitesimal fraction of possible sequences to sustain life. Are there solutions to biological problems other than those provided by nature? Can we create artificial proteins that sustain life? To investigate these questions, we have created combinatorial collections, or libraries, of novel sequences with no homology to those found in living organisms. Previously designed libraries contained numerous functional proteins. However, they often formed dynamic, rather than well-ordered structures, which complicated structural and mechanistic characterization. To address this challenge, we describe the development of new libraries based on the de novo protein S-824, a 4-helix bundle with a very stable 3-dimensional structure. Distinct from previous libraries, we targeted variability to a specific region of the protein, seeking to create potential functional sites. By characterizing variant proteins from this library, we demonstrate that the S-824 scaffold tolerates diverse amino acid substitutions in a putative cavity, including buried polar residues suitable for catalysis. We designed and created a DNA library encoding 1.7 × 10⁶ unique protein sequences. This new library of stable de novo α-helical proteins is well suited for screens and selections for a range of functional activities in vitro and in vivo.

Review of lactose-driven auto-induction expression of isotope-labelled proteins

NMR is an important method in the structural and functional characterization of proteins, but such experiments typically require isotopic labelling because of the low natural abundance of the nuclei of interest. Isotope-labelled protein for NMR experiments is typically obtained from IPTG-inducible bacterial expression systems in a minimal media that contains labelled carbon or nitrogen sources. Optimization of expression conditions is crucial yet challenging; large amounts of labelled protein are desired, yet protein yields are lower in minimal media, while the labelled precursors are expensive. Faced with these challenges there is a growing body of literature that apply innovative methods of induction to optimize the yield of isotope-labelled protein. A promising technique is lactose-driven auto-induction as it mitigates user intervention and can lead to higher protein yields. This review assesses the current advances and limitations surrounding the ability of researchers to isotope label proteins using auto-induction, and it identifies key components for optimization.

Unevolved De Novo Proteins Have Innate Tendencies to Bind Transition Metals

Life as we know it would not exist without the ability of protein sequences to bind metal ions. Transition metals, in particular, play essential roles in a wide range of structural and catalytic functions. The ubiquitous occurrence of metalloproteins in all organisms leads one to ask whether metal binding is an evolved trait that occurred only rarely in ancestral sequences, or alternatively, whether it is an innate property of amino acid sequences, occurring frequently in unevolved sequence space. To address this question, we studied 52 proteins from a combinatorial library of novel sequences designed to fold into 4-helix bundles. Although these sequences were neither designed nor evolved to bind metals, the majority of them have innate tendencies to bind the transition metals copper, cobalt, and zinc with high nanomolar to low-micromolar affinity.

Hierarchical design of artificial proteins and complexes toward synthetic structural biology

In multiscale structural biology, synthetic approaches are important to demonstrate biophysical principles and mechanisms underlying the structure, function, and action of bio-nanomachines. A central goal of "synthetic structural biology" is the design and construction of artificial proteins and protein complexes as desired. In this paper, I review recent remarkable progress of an array of approaches for hierarchical design of artificial proteins and complexes that signpost the path forward toward synthetic structural biology as an emerging interdisciplinary field. Topics covered include combinatorial and protein-engineering approaches for directed evolution of artificial binding proteins and membrane proteins, binary code strategy for structural and functional de novo proteins, protein nanobuilding block strategy for constructing nano-architectures, protein-metal-organic frameworks for 3D protein complex crystals, and rational and computational approaches for design/creation of artificial proteins and complexes, novel protein folds, ideal/optimized protein structures, novel binding proteins for targeted therapeutics, and self-assembling nanomaterials. Protein designers and engineers look toward a bright future in synthetic structural biology for the next generation of biophysics and biotechnology.

A Non-natural Protein Rescues Cells Deleted for a Key Enzyme in Central Metabolism

An important goal of synthetic biology is to create novel proteins that provide life-sustaining functions in living organisms. Recent attempts to produce novel proteins have focused largely on rational design involving significant computational efforts. In contrast, nature does not design sequences a priori. Instead, nature relies on Darwinian evolution to select biologically functional sequences from nondesigned sequence space. To mimic natural selection in the laboratory, we combed through libraries of novel sequences and selected proteins that rescue E. coli cells deleted for conditionally essential genes. One such gene, gltA, encodes citrate synthase, the enzyme responsible for metabolic entry into the citric acid cycle. The de novo protein SynGltA was isolated as a rescuer of ΔgltA. However, SynGltA is not an enzyme. Instead, SynGltA allows cells to recover from a defect in central carbon and energy metabolism by altering the regulation of an alternative metabolic pathway. Specifically, SynGltA dramatically enhances the expression of prpC, a gene encoding methylcitrate synthase in the propionate degradation pathway. This endogenous protein has promiscuous catalytic activity, which when overexpressed, compensates for the deletion of citrate synthase. While the molecular details responsible for this overexpression have not been elucidated, the results clearly demonstrate that non-natural proteins-unrelated to sequences in nature-can provide life-sustaining functions by altering gene regulation in natural organisms.

Predicting protein dynamics from structural ensembles

The biological properties of proteins are uniquely determined by their structure and dynamics. A protein in solution populates a structural ensemble of metastable configurations around the global fold. From overall rotation to local fluctuations, the dynamics of proteins can cover several orders of magnitude in time scales. We propose a simulation-free coarse-grained approach which utilizes knowledge of the important metastable folded states of the protein to predict the protein dynamics. This approach is based upon the Langevin Equation for Protein Dynamics (LE4PD), a Langevin formalism in the coordinates of the protein backbone. The linear modes of this Langevin formalism organize the fluctuations of the protein, so that more extended dynamical cooperativity relates to increasing energy barriers to mode diffusion. The accuracy of the LE4PD is verified by analyzing the predicted dynamics across a set of seven different proteins for which both relaxation data and NMR solution structures are available. Using experimental NMR conformers as the input structural ensembles, LE4PD predicts quantitatively accurate results, with correlation coefficient ρ = 0.93 to NMR backbone relaxation measurements for the seven proteins. The NMR solution structure derived ensemble and predicted dynamical relaxation is compared with molecular dynamics simulation-derived structural ensembles and LE4PD predictions and is consistent in the time scale of the simulations. The use of the experimental NMR conformers frees the approach from computationally demanding simulations.

A de novo protein confers copper resistance in Escherichia coli

To survive environmental challenges, biological systems rely on proteins that were selected by evolution to function in particular cellular and conditional settings. With the advent of protein design and synthetic biology, it is now possible to construct novel proteins that are not biased by eons of selection in natural hosts. The availability of these sequences prompts us to ask whether natural biological organisms can use naïve-non-biological-proteins to enhance fitness in stressful environments. To address this question, we transformed a library of DNA sequences encoding ∼1.5 × 10(6) binary patterned de novo proteins into E. coli, and selected for sequences that enable growth in concentrations of copper that would otherwise be toxic. Several novel sequences were discovered, and one of them, called Construct K (ConK), was studied in detail. Cells expressing ConK accumulate approximately 50% less copper than control cells. The function of ConK does not involve an oxidase, nor does it require two of the best characterized copper efflux systems. However, the ability of ConK to rescue cells from toxic concentrations of copper does require an active proton motive force. Further selections for growth in higher concentrations of copper led to the laboratory evolution of variants of ConK with enhanced levels of activity in vivo. These studies demonstrate that novel proteins, unbiased by evolutionary history in the natural world, can enhance the fitness of biological systems.

SYNOPSIS

Living systems evolve to adapt to potentially lethal environmental changes. This normally involves repurposing existing genetic information (i.e. sequences that were selected by billions of years of evolution). Here we show that a completely de novo protein, not derived from nature, can enable E. coli cells to grow in otherwise toxic concentrations of copper, demonstrating that living systems also have the capacity to incorporate and protopurpose entirely novel genetic information.

A protein constructed de novo enables cell growth by altering gene regulation

Recent advances in protein design rely on rational and computational approaches to create novel sequences that fold and function. In contrast, natural systems selected functional proteins without any design a priori. In an attempt to mimic nature, we used large libraries of novel sequences and selected for functional proteins that rescue Escherichia coli cells in which a conditionally essential gene has been deleted. In this way, the de novo protein SynSerB3 was selected as a rescuer of cells in which serB, which encodes phosphoserine phosphatase, an enzyme essential for serine biosynthesis, was deleted. However, SynSerB3 does not rescue the deleted activity by catalyzing hydrolysis of phosphoserine. Instead, SynSerB3 up-regulates hisB, a gene encoding histidinol phosphate phosphatase. This endogenous E. coli phosphatase has promiscuous activity that, when overexpressed, compensates for the deletion of phosphoserine phosphatase. Thus, the de novo protein SynSerB3 rescues the deletion of serB by altering the natural regulation of the His operon.

De Novo Proteins with Life-Sustaining Functions Are Structurally Dynamic

Designing and producing novel proteins that fold into stable structures and provide essential biological functions are key goals in synthetic biology. In initial steps toward achieving these goals, we constructed a combinatorial library of de novo proteins designed to fold into 4-helix bundles. As described previously, screening this library for sequences that function in vivo to rescue conditionally lethal mutants of Escherichia coli (auxotrophs) yielded several de novo sequences, termed SynRescue proteins, which rescued four different E. coli auxotrophs. In an effort to understand the structural requirements necessary for auxotroph rescue, we investigated the biophysical properties of the SynRescue proteins, using both computational and experimental approaches. Results from circular dichroism, size-exclusion chromatography, and NMR demonstrate that the SynRescue proteins are α-helical and relatively stable. Surprisingly, however, they do not form well-ordered structures. Instead, they form dynamic structures that fluctuate between monomeric and dimeric states. These findings show that a well-ordered structure is not a prerequisite for life-sustaining functions, and suggests that dynamic structures may have been important in the early evolution of protein function.

Hierarchical cascades of instability govern the mechanics of coiled coils: helix unfolding precedes coil unzipping

Coiled coils are a fundamental emergent motif in proteins found in structural biomaterials, consisting of α-helical secondary structures wrapped in a supercoil. A fundamental question regarding the thermal and mechanical stability of coiled coils in extreme environments is the sequence of events leading to the disassembly of individual oligomers from the universal coiled-coil motifs. To shed light on this phenomenon, here we report atomistic simulations of a trimeric coiled coil in an explicit water solvent and investigate the mechanisms underlying helix unfolding and coil unzipping in the assembly. We employ advanced sampling techniques involving steered molecular dynamics and metadynamics simulations to obtain the free-energy landscapes of single-strand unfolding and unzipping in a three-stranded assembly. Our comparative analysis of the free-energy landscapes of instability pathways shows that coil unzipping is a sequential process involving multiple intermediates. At each intermediate state, one heptad repeat of the coiled coil first unfolds and then unzips due to the loss of contacts with the hydrophobic core. This observation suggests that helix unfolding facilitates the initiation of coiled-coil disassembly, which is confirmed by our 2D metadynamics simulations showing that unzipping of one strand requires less energy in the unfolded state compared with the folded state. Our results explain recent experimental findings and lay the groundwork for studying the hierarchical molecular mechanisms that underpin the thermomechanical stability/instability of coiled coils and similar protein assemblies.

Computational de novo design of a four-helix bundle protein--DND_4HB

The de novo design of proteins is a rigorous test of our understanding of the key determinants of protein structure. The helix bundle is an interesting de novo design model system due to the diverse topologies that can be generated from a few simple α-helices. Previously, noncomputational studies demonstrated that connecting amphipathic helices together with short loops can sometimes generate helix bundle proteins, regardless of the bundle's exact sequence. However, using such methods, the precise positions of helices and side chains cannot be predetermined. Since protein function depends on exact positioning of residues, we examined if sequence design tools in the program Rosetta could be used to design a four-helix bundle with a predetermined structure. Helix position was specified using a folding procedure that constrained the design model to a defined topology, and iterative rounds of rotamer-based sequence design and backbone refinement were used to identify a low energy sequence for characterization. The designed protein, DND_4HB, unfolds cooperatively (Tm >90°C) and a NMR solution structure shows that it adopts the target helical bundle topology. Helices 2, 3, and 4 agree very closely with the design model (backbone RMSD = 1.11 Å) and >90% of the core side chain χ1 and χ2 angles are correctly predicted. Helix 1 lies in the target groove against the other helices, but is displaced 3 Å along the bundle axis. This result highlights the potential of computational design to create bundles with atomic-level precision, but also points at remaining challenges for achieving specific positioning between amphipathic helices.

High-quality combinatorial protein libraries using the binary patterning approach

Protein combinatorial libraries have become a platform technology for exploring protein sequence space for novel molecules for use in research, synthetic biology, biotechnology, and medicine. To expedite the isolation of proteins with novel/desired functions using screens and selections, high-quality approaches that generate protein libraries rich in folded and soluble structures are desirable for this goal. The binary patterning approach is a protein library design method that incorporates elements of both rational design and combinatorial diversity to specify the arrangement of polar and nonpolar amino acid residues in the context of a desired, folded tertiary structure template. An overview of the considerations necessary to design and construct binary patterned libraries of de novo and natural proteins is presented.

An evolution-based approach to De Novo protein design and case study on Mycobacterium tuberculosis

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality.

The goal of computational protein design is to create new protein sequences of desirable structure and biological function. Most protein design methods are developed to search for sequences with the lowest free-energy based on physics-based force fields following Anfinsen's thermodynamic hypothesis. A major obstacle of such approaches is the inaccuracy of the force-field design, which cannot accurately describe atomic interactions or correctly recognize protein folds. We propose a novel method which uses evolutionary information, in the form of sequence profiles from structure families, to guide the sequence design. Since sequence profiles are generally more accurate than physics-based potentials in protein fold recognition, a unique advantage lies on that it targets the design procedure to a family of protein sequence profiles to enhance the robustness of designed sequences. The method was tested on 87 proteins and the designed sequences can be folded by I-TASSER to models with an average RMSD 2.1 Å. As a case study of large-scale application, the method is extended to redesign all structurally resolved proteins in the human pathogenic bacteria, Mycobacterium tuberculosis. Five sequences varying in fold and sizes were characterized by circular dichroism and NMR spectroscopy experiments and three were shown to have ordered tertiary structure.

Conformational dynamics is more important than helical propensity for the folding of the all α-helical protein Im7

Im7 folds via an on-pathway intermediate that contains three of the four native α-helices. The missing helix, helix III, is the shortest and its failure to be formed until late in the pathway is related to frustration in the structure. Im7H3M3, a 94-residue variant of the 87-residue Im7 in which helix III is the longest of the four native helices, also folds via an intermediate. To investigate the structural basis for this we calculated the frustration in the structure of Im7H3M3 and used NMR to investigate its dynamics. We found that the native state of Im7H3M3 is highly frustrated and in equilibrium with an intermediate state that lacks helix III, similar to Im7. Model-free analysis identified residues with chemical exchange contributions to their relaxation that aligned with the residues predicted to have highly frustrated interactions, also like Im7. Finally, we determined properties of urea-denatured Im7H3M3 and identified four clusters of interacting residues that corresponded to the α-helices of the native protein. In Im7 the cluster sizes were related to the lengths of the α-helices with cluster III being the smallest but in Im7H3M3 cluster III was also the smallest, despite this region forming the longest helix in the native state. These results suggest that the conformational properties of the urea-denatured states promote formation of a three-helix intermediate in which the residues that form helix III remain non-helical. Thus it appears that features of the native structure are formed early in folding linked to collapse of the unfolded state.

Intrinsically unstructured proteins by design-electrostatic interactions can control binding, folding, and function of a helix-loop-helix heterodimer

Intrinsically disordered proteins that exist as unordered monomeric structures in aqueous solution at pH 7 but fold into four-helix bundles upon binding to recognized polypeptide targets have been designed. NMR and CD spectra of the monomeric polypeptides show the hallmarks of unordered structures, whereas in the bound state they are highly helical. Analytical ultracentrifugation data shows that the polypeptides bind to their targets to form exclusively heterodimers at neutral pH. To demonstrate the relationship between binding, folding, and function, a catalytic site for ester hydrolysis was introduced into an unordered and largely inactive monomer, but that was structured and catalytically active in the presence of a specific polypeptide target. Electrostatic interactions between surface-exposed residues inhibited the binding and folding of the monomers at pH 7. Charge-charge repulsion between ionizable amino acids was thus found to be sufficient to disrupt binding between polypeptide chains despite their inherent propensities for structure formation and may be involved in the folding and function of inherently disordered proteins in biology.

Folding helical proteins in explicit solvent using dihedral-biased tempering

Using a single-trajectory-based tempering method with a high-temperature dihedral bias, we repeatedly folded four helical proteins [α(3)D (PDB ID: 2A3D, 73 residues), α(3)W (1LQ7, 67 residues), Fap1-NR(α) (2KUB, 81 residues) and S-836 (2JUA, 102 residues)] and some of the mutants in explicit solvent within several microseconds. The lowest root-mean-square deviations of backbone atoms from the experimentally determined structures were 1.9, 1.4, 1.0, and 2.1 Å, respectively. Cluster analyses of folding trajectories showed the native conformation usually occupied the most populated cluster. The simulation protocol can be applied to large-scale simulations of other helical proteins on commonly accessible computing platforms.

Proteins from an unevolved library of de novo designed sequences bind a range of small molecules

The availability of large collections of de novo designed proteins presents new opportunities to harness novel macromolecules for synthetic biological functions. Many of these new functions will require binding to small molecules. Is the ability to bind small molecules a property that arises only in response to biological selection or computational design? Or alternatively, is small molecule binding a property of folded proteins that occurs readily amidst collections of unevolved sequences? These questions can be addressed by assessing the binding potential of de novo proteins that are designed to fold into stable structures, but are "naïve" in the sense that they (i) share no significant sequence similarity with natural proteins and (ii) were neither selected nor designed to bind small molecules. We chose three naïve proteins from a library of sequences designed to fold into 4-helix bundles and screened for binding to 10,000 compounds displayed on small molecule microarrays. Several binders were identified, and binding was characterized by a series of biophysical assays. Surprisingly, despite the similarity of the three de novo proteins to one another, they exhibit selective ligand binding. These findings demonstrate the potential of novel proteins for molecular recognition and have significant implications for a range of applications in synthetic biology.

Relative stability of de novo four-helix bundle proteins: insights from coarse grained molecular simulations

We use a recently developed coarse-grained computational model to investigate the relative stability of two different sets of de novo designed four-helix bundle proteins. Our simulations suggest a possible explanation for the experimentally observed increase in stability of the four-helix bundles with increasing sequence length. In details, we show that both short subsequences composed only by polar residues and additional nonpolar residues inserted, via different point mutations in ad hoc positions, seem to play a significant role in stabilizing the four-helix bundle conformation in the longer sequences. Finally, we propose an additional mutation that rescues a short amino acid sequence that would otherwise adopt a compact misfolded state. Our work suggests that simple computational models can be used as a complementary tool in the design process of de novo proteins.

Comparison of the frequency of functional SH3 domains with different limited sets of amino acids using mRNA display

Although modern proteins consist of 20 different amino acids, it has been proposed that primordial proteins consisted of a small set of amino acids, and additional amino acids have gradually been recruited into the genetic code. This hypothesis has recently been supported by comparative genome sequence analysis, but no direct experimental approach has been reported. Here, we utilized a novel experimental approach to test a hypothesis that native-like globular proteins might be easily simplified by a set of putative primitive amino acids with retention of its structure and function than by a set of putative new amino acids. We performed in vitro selection of a functional SH3 domain as a model from partially randomized libraries with different sets of amino acids using mRNA display. Consequently, a library rich in putative primitive amino acids included a larger number of functional SH3 sequences than a library rich in putative new amino acids. Further, the functional SH3 sequences were enriched from the primitive library slightly earlier than from a randomized library with the full set of amino acids, while the function and structure of the selected SH3 proteins with the primitive alphabet were comparable with those from the 20 amino acid alphabet. Application of this approach to various combinations of codons in protein sequences may be useful not only for clarifying the precise order of the amino acid expansion in the early stages of protein evolution but also for efficiently creating novel functional proteins in the laboratory.

Binding of small molecules to cavity forming mutants of a de novo designed protein

A central goal of protein design is to devise novel proteins for applications in biotechnology and medicine. Many applications, including those focused on sensing and catalysis will require proteins that recognize and bind to small molecules. Here, we show that stably folded α-helical proteins isolated from a binary patterned library of designed sequences can be mutated to produce binding sites capable of binding a range of small aromatic compounds. Specifically, we mutated two phenylalanine side chains to alanine in the known structure of de novo protein S-824 to create buried cavities in the core of this four-helix bundle. The parental protein and the Phe→Ala variants were exposed to mixtures of compounds, and selective binding was assessed by saturation transfer difference NMR. The affinities of benzene and a number of its derivatives were determined by pulse field gradient spin echo NMR, and several of the compounds were shown to bind the mutated protein with micromolar dissociation constants. These studies suggest that stably folded de novo proteins from binary patterned libraries are well-suited as scaffolds for the design of binding sites.

De novo designed proteins from a library of artificial sequences function in Escherichia coli and enable cell growth

A central challenge of synthetic biology is to enable the growth of living systems using parts that are not derived from nature, but designed and synthesized in the laboratory. As an initial step toward achieving this goal, we probed the ability of a collection of >10⁶de novo designed proteins to provide biological functions necessary to sustain cell growth. Our collection of proteins was drawn from a combinatorial library of 102-residue sequences, designed by binary patterning of polar and nonpolar residues to fold into stable 4-helix bundles. We probed the capacity of proteins from this library to function in vivo by testing their abilities to rescue 27 different knockout strains of Escherichia coli, each deleted for a conditionally essential gene. Four different strains – ΔserB, ΔgltA, ΔilvA, and Δfes – were rescued by specific sequences from our library. Further experiments demonstrated that a strain simultaneously deleted for all four genes was rescued by co-expression of four novel sequences. Thus, cells deleted for ∼0.1% of the E. coli genome (and ∼1% of the genes required for growth under nutrient-poor conditions) can be sustained by sequences designed de novo.

Comparative characterization of random-sequence proteins consisting of 5, 12, and 20 kinds of amino acids

Screening of functional proteins from a random-sequence library has been used to evolve novel proteins in the field of evolutionary protein engineering. However, random-sequence proteins consisting of the 20 natural amino acids tend to aggregate, and the occurrence rate of functional proteins in a random-sequence library is low. From the viewpoint of the origin of life, it has been proposed that primordial proteins consisted of a limited set of amino acids that could have been abundantly formed early during chemical evolution. We have previously found that members of a random-sequence protein library constructed with five primitive amino acids show high solubility (Doi et al., Protein Eng Des Sel 2005;18:279-284). Although such a library is expected to be appropriate for finding functional proteins, the functionality may be limited, because they have no positively charged amino acid. Here, we constructed three libraries of 120-amino acid, random-sequence proteins using alphabets of 5, 12, and 20 amino acids by preselection using mRNA display (to eliminate sequences containing stop codons and frameshifts) and characterized and compared the structural properties of random-sequence proteins arbitrarily chosen from these libraries. We found that random-sequence proteins constructed with the 12-member alphabet (including five primitive amino acids and positively charged amino acids) have higher solubility than those constructed with the 20-member alphabet, though other biophysical properties are very similar in the two libraries. Thus, a library of moderate complexity constructed from 12 amino acids may be a more appropriate resource for functional screening than one constructed from 20 amino acids.

Sequence periodicity and secondary structure propensity in model proteins

We explore the question of whether local effects (originating from the amino acids intrinsic secondary structure propensities) or nonlocal effects (reflecting the sequence of amino acids as a whole) play a larger role in determining the fold of globular proteins. Earlier circular dichroism studies have shown that the pattern of polar, non polar amino acids (nonlocal effect) dominates over the amino acid intrinsic propensity (local effect) in determining the secondary structure of oligomeric peptides. In this article, we present a coarse grained computational model that allows us to quantitatively estimate the role of local and nonlocal factors in determining both the secondary and tertiary structure of small, globular proteins. The amino acid intrinsic secondary structure propensity is modeled by a dihedral potential term. This dihedral potential is parametrized to match with experimental measurements of secondary structure propensity. Similarly, the magnitude of the attraction between hydrophobic residues is parametrized to match the experimental transfer free energies of hydrophobic amino acids. Under these parametrization conditions, we systematically explore the degree of frustration a given polar, non polar pattern can tolerate when the secondary structure intrinsic propensities are in opposition to it. When the parameters are in the biophysically relevant range, we observe that the fold of small, globular proteins is determined by the pattern of polar, non polar amino acids regardless of their instrinsic secondary structure propensities. Our simulations shed new light on previous observations that tertiary interactions are more influential in determining protein structure than secondary structure propensity. The fact that this can be inferred using a simple polymer model that lacks most of the biochemical details points to the fundamental importance of binary patterning in governing folding.

Simple tests for the validation of multiple field spin relaxation data

(15)N spin relaxation data is widely used to extract detailed dynamic information regarding bond vectors such as the amide N-H bond of the protein backbone. Analysis is typically carried using the Lipari-Szabo model-free approach. Even though the original model-free equation can be determined from single field R (1), R (2) and NOE, over-determination of more complex motional models is dependent on the recording of multiple field datasets. This is especially important for the characterization of conformational exchange which affects R (2) in a field dependent manner. However, severe artifacts can be introduced if inconsistencies arise between experimental setups with different magnets (or samples). Here, we propose the use of simple tests as validation tools for the assessment of consistency between different datasets recorded at multiple magnetic fields. Synthetic data are used to show the effects of inconsistencies on the proposed tests. Moreover, an analysis of data currently deposited in the BMRB is performed. Finally, two cases from our laboratory are presented. These tests are implemented in the open-source program relax, and we propose their use as a routine check-up for assessment of multiple field dataset consistency prior to any analysis such as model-free calculations. We believe this will aid in the extraction of higher quality dynamics information from (15)N spin relaxation data.

Generic coarse-grained model for protein folding and aggregation

A generic coarse-grained (CG) protein model is presented. The intermediate level of resolution (four beads per amino acid, implicit solvent) allows for accurate sampling of local conformations. It relies on simple interactions that emphasize structure, such as hydrogen bonds and hydrophobicity. Realistic alpha/beta content is achieved by including an effective nearest-neighbor dipolar interaction. Parameters are tuned to reproduce both local conformations and tertiary structures. The thermodynamics and kinetics of a three-helix bundle are studied. We check that the CG model is able to fold proteins with tertiary structures and amino acid sequences different from the one used for parameter tuning. By studying both helical and extended conformations we make sure the force field is not biased toward any particular secondary structure. The accuracy involved in folding not only the test protein but also other ones show strong evidence for amino acid cooperativity embedded in the model. Without any further adjustments or bias a realistic oligopeptide aggregation scenario is observed.

Cofactor binding and enzymatic activity in an unevolved superfamily of de novo designed 4-helix bundle proteins

To probe the potential for enzymatic activity in unevolved amino acid sequence space, we created a combinatorial library of de novo 4-helix bundle proteins. This collection of novel proteins can be considered an "artificial superfamily" of helical bundles. The superfamily of 102-residue proteins was designed using binary patterning of polar and nonpolar residues, and expressed in Escherichia coli from a library of synthetic genes. Sequences from the library were screened for a range of biological functions including heme binding and peroxidase, esterase, and lipase activities. Proteins exhibiting these functions were purified and characterized biochemically. The majority of de novo proteins from this superfamily bound the heme cofactor, and a sizable fraction of the proteins showed activity significantly above background for at least one of the tested enzymatic activities. Moreover, several of the designed 4-helix bundles proteins showed activity in all of the assays, thereby demonstrating the functional promiscuity of unevolved proteins. These studies reveal that de novo proteins-which have neither been designed for function, nor subjected to evolutionary pressure (either in vivo or in vitro)-can provide rudimentary activities and serve as a "feedstock" for evolution.