Search

We used the molecular modeling program Rosetta to identify clusters of amino acid substitutions in antibody fragments (scFvs and scAbs) that improve global protein stability and resistance to thermal deactivation. Using this methodology, we increased the melting temperature (T(m)) and resistance to heat treatment of an antibody fragment that binds to the Clostridium botulinum hemagglutinin protein (anti-HA33). Two designed antibody fragment variants with two amino acid replacement clusters, designed to stabilize local regions, were shown to have both higher T(m) compared to the parental scFv and importantly, to retain full antigen binding activity after 2 hours of incubation at 70 °C. The crystal structure of one thermostabilized scFv variants was solved at 1.6 Å and shown to be in close agreement with the RosettaAntibody model prediction.

Evolution trains a from-scratch catalyst Metal-bound peptides can catalyze simple reactions such as ester hydrolysis and may have been the starting point for the evolution of modern enzymes. Studer et al. selected progressively more-proficient variants of a small protein derived from a computationally designed zinc-binding peptide. The resulting enzyme could perform the trained reaction at rates typical for naturally evolved enzymes and serendipitously developed a strong preference for a single enantiomer of the substrate. A structure of the final catalyst highlights how small, progressive changes can remodel both catalytic residues and protein architecture in unpredictable ways. Science , this issue p. 1285

Genetic circuits implement computational operations within a cell. Debugging them is difficult because their function is defined by multiple states (e.g., combinations of inputs) that vary in time. Here, we develop RNA‐seq methods that enable the simultaneous measurement of: (i) the states of internal gates, (ii) part performance (promoters, insulators, terminators), and (iii) impact on host gene expression. This is applied to a three‐input one‐output circuit consisting of three sensors, five NOR/NOT gates, and 46 genetic parts. Transcription profiles are obtained for all eight combinations of inputs, from which biophysical models can extract part activities and the response functions of sensors and gates. Various unexpected failure modes are identified, including cryptic antisense promoters, terminator failure, and a sensor malfunction due to media‐induced changes in host gene expression. This can guide the selection of new parts to fix these problems, which we demonstrate by using a bidirectional terminator to disrupt observed antisense transcription. This work introduces RNA‐seq as a powerful method for circuit characterization and debugging that overcomes the limitations of fluorescent reporters and scales to large systems composed of many parts.

DNAplotlib (www.dnaplotlib.org) is a computational toolkit for the programmable visualization of highly customizable, standards-compliant genetic designs. Functions are provided to aid with both visualization tasks and to extract and overlay associated experimental data. High-quality output is produced in the form of vector-based PDFs, rasterized images, and animated movies. All aspects of the rendering process can be easily customized or extended by the user to cover new forms of genetic part or regulation. DNAplotlib supports improved communication of genetic design information and offers new avenues for static, interactive and dynamic visualizations that map and explore the links between the structure and function of genetic parts, devices and systems; including metabolic pathways and genetic circuits. DNAplotlib is crossplatform software developed using Python and released under the MIT license.

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 A) 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 A 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.

We computationally designed a de novo protein-protein interaction between wild-type ubiquitin and a redesigned scaffold. Our strategy was to incorporate zinc at the designed interface to promote affinity and orientation specificity. A large set of monomeric scaffold surfaces were computationally engineered with three-residue zinc coordination sites, and the ubiquitin residue H68 was docked to the open coordination site to complete a tetrahedral zinc site. This single coordination bond was intended as a hotspot and polar interaction for ubiquitin binding, and surrounding residues on the scaffold were optimized primarily as hydrophobic residues using a rotamer-based sequence design protocol in Rosetta. From thousands of independent design simulations, four sequences were selected for experimental characterization. The best performing design, called Spelter, binds tightly to zinc (Kd

Structure-based protein design tests our understanding of the minimal determinants of protein structure and function. Previous studies have demonstrated that placing zinc binding amino acids (His, Glu, Asp or Cys) near each other in a folded protein in an arrangement predicted to be tetrahedral is often sufficient to achieve binding to zinc. However, few designs have been characterized with high-resolution structures. Here, we use X-ray crystallography, binding studies and mutation analysis to evaluate three alternative strategies for designing zinc binding sites with the molecular modeling program Rosetta. While several of the designs were observed to bind zinc, crystal structures of two designs reveal binding configurations that differ from the design model. In both cases, the modeling did not accurately capture the presence or absence of second-shell hydrogen bonds critical in determining binding-site structure. Efforts to more explicitly design second-shell hydrogen bonds were largely unsuccessful as evidenced by mutation analysis and low expression of proteins engineered with extensive primary and secondary networks. Our results suggest that improved methods for designing interaction networks will be needed for creating metal binding sites with high accuracy.

Summary Mutation of surface residues to charged amino acids increases resistance to aggregation and can enable reversible unfolding. We have developed a protocol using the Rosetta computational design package that "supercharges" proteins while considering the energetic implications of each mutation. Using a homology model, a single-chain variable fragment antibody was designed that has a markedly enhanced resistance to thermal inactivation and displays an unanticipated ≈30-fold improvement in affinity. Such supercharged antibodies should prove useful for assays in resource-limited settings and for developing reagents with improved shelf lives.

Members of the periplasmic binding protein superfamily are involved in the selective passage of ligands through bacterial cell membranes. The hyperthermophilic eubacterium Thermotoga maritima was found to encode a highly stable and specific periplasmic arginine-binding protein (TM0593). Following signal sequence removal and overexpression in Escherichia coli, TM0593 was purified by thermoprecipitation and affinity chromatography. The ultra-stable protein with a monomeric molecular weight of 27.7 kDa was found to exist as both a homodimer and homotrimer at appreciable concentrations even under strongly denaturing conditions, with an estimated transition temperature of 116 degrees C. Its multimeric structure may provide further evidence of the importance of quaternary structure in the movement of nutrients across bacterial membranes. Purified and refolded TM0593 was further characterized by fluorescence spectroscopy, mass spectrometry, and circular dichroism to demonstrate the specificity of the protein for arginine and to elucidate structural changes associated with arginine binding. The protein binds arginine with a dissociation constant of 20 muM as determined by surface plasmon resonance measurements. Due to its high thermodynamic stability, TM0593 may serve as a scaffold for the creation of a robust fluorescent biosensor.

Computational design of proteins with altered ligand specificity is an emerging method for the creation of new biosensing systems. In this work, we investigated the outcome of site-directed mutagenesis on the Escherichia coli ribose binding protein (RBP), which is frequently used as a design scaffold for computational searches. A ribose biosensor was first constructed whereby an environmentally sensitive fluorescent probe was covalently attached to RBP at position S265C. This protein conjugate displayed a 54% decrease in emission intensity upon the addition of saturating ribose concentrations and exhibited an apparent dissociation constant (K(d) ) of 3.4 microM. Site-directed mutants within the RBP binding pocket were created and examined for ribose binding ability and overall structural stability. Because as many as 12 mutations are needed to alter ligand specificity in RBP, we measured the effect of single and multiple alanine mutations on stability and signal transduction potential of the ribose biosensor. Single alanine mutations had significant impact on both stability and signaling. Mutations of N190A and F214A each produced melting temperatures8 degrees C below those observed for the wild-type protein. Residue Q235, located in the hinge region of RBP, appeared to be a hot spot for global protein stability as well. Additional single alanine mutations demonstrated as much as 200-fold increase in apparent K(d) but retained overall protein stability. The data collected from this study may be incorporated into design algorithms to help create more stable biosensors and optimize signal transduction properties for a variety of important analytes.

INTRODUCTION Cells respond to their environment, make decisions, build structures, and coordinate tasks. Underlying these processes are computational operations performed by networks of regulatory proteins that integrate signals and control the timing of gene expression. Harnessing this capability is critical for biotechnology projects that require decision-making, control, sensing, or spatial organization. It has been shown that cells can be programmed using synthetic genetic circuits composed of regulators organized to generate a desired operation. However, the construction of even simple circuits is time-intensive and unreliable. RATIONALE Electronic design automation (EDA) was developed to aid engineers in the design of semiconductor-based electronics. In an effort to accelerate genetic circuit design, we applied principles from EDA to enable increased circuit complexity and to simplify the incorporation of synthetic gene regulation into genetic engineering projects. We used the hardware description language Verilog to enable a user to describe a circuit function. The user also specifies the sensors, actuators, and “user constraints file” (UCF), which defines the organism, gate technology, and valid operating conditions. Cello (www.cellocad.org) uses this information to automatically design a DNA sequence encoding the desired circuit. This is done via a set of algorithms that parse the Verilog text, create the circuit diagram, assign gates, balance constraints to build the DNA, and simulate performance. RESULTS Cello designs circuits by drawing upon a library of Boolean logic gates. Here, the gate technology consists of NOT/NOR logic based on repressors. Gate connection is simplified by defining the input and output signals as RNA polymerase (RNAP) fluxes. We found that the gates need to be insulated from their genetic context to function reliably in the context of different circuits. Each gate is isolated using strong terminators to block RNAP leakage, and input interchangeability is improved using ribozymes and promoter spacers. These parts are varied for each gate to avoid breakage due to recombination. Measuring the load of each gate and incorporating this into the optimization algorithms further reduces evolutionary pressure. Cello was applied to the design of 60 circuits for Escherichia coli , where the circuit function was specified using Verilog code and transformed to a DNA sequence. The DNA sequences were built as specified with no additional tuning, requiring 880,000 base pairs of DNA assembly. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts). Across all circuits, 92% of the 412 output states functioned as predicted. CONCLUSION Our work constitutes a hardware description language for programming living cells. This required the co-development of design algorithms with gates that are sufficiently simple and robust to be connected by automated algorithms. We demonstrate that engineering principles can be applied to identify and suppress errors that complicate the compositions of larger systems. This approach leads to highly repetitive and modular genetics, in stark contrast to the encoding of natural regulatory networks. The use of a hardware-independent language and the creation of additional UCFs will allow a single design to be transformed into DNA for different organisms, genetic endpoints, operating conditions, and gate technologies.

We computationally designed a de novo protein-protein interaction between wild-type ubiquitin and a redesigned scaffold. Our strategy was to incorporate zinc at the designed interface to promote affinity and orientation specificity. A large set of monomeric scaffold surfaces were computationally engineered with three-residue zinc coordination sites, and the ubiquitin residue H68 was docked to the open coordination site to complete a tetrahedral zinc site. This single coordination bond was intended as a hotspot and polar interaction for ubiquitin binding, and surrounding residues on the scaffold were optimized primarily as hydrophobic residues using a rotamer-based sequence design protocol in Rosetta. From thousands of independent design simulations, four sequences were selected for experimental characterization. The best performing design, called Spelter, binds tightly to zinc (Kd 10 nM) and binds ubiquitin with a Kd of 20 µM in the presence of zinc and 68 µM in the absence of zinc. Mutagenesis studies and nuclear magnetic resonance chemical shift perturbation experiments indicate that Spelter interacts with H68 and the target surface on ubiquitin; however, H68 does not form a hotspot as intended. Instead, mutation of H68 to alanine results in tighter binding. Although a 3/1 zinc coordination arrangement at an interface cannot be ruled out as a means to improve affinity, our study led us to conclude that 2/2 coordination arrangements or multiple-zinc designs are more likely to promote high-affinity protein interactions.

Here we show that a recent computationally designed zinc-mediated protein interface is serendipitously capable of catalyzing carboxyester and phosphoester hydrolysis. Although the original motivation was to design a de novo zinc-mediated protein-protein interaction (called MID1-zinc), we observed in the homodimer crystal structure a small cleft and open zinc coordination site. We investigated if the cleft and zinc site at the designed interface were sufficient for formation of a primitive active site that can perform hydrolysis. MID1-zinc hydrolyzes 4-nitrophenyl acetate with a rate acceleration of 10(5) and a k(cat)/K(M) of 630 M(-1) s(-1) and 4-nitrophenyl phosphate with a rate acceleration of 10(4) and a k(cat)/K(M) of 14 M(-1) s(-1). These rate accelerations by an unoptimized active site highlight the catalytic power of zinc and suggest that the clefts formed by protein-protein interactions are well-suited for creating enzyme active sites. This discovery has implications for protein evolution and engineering: from an evolutionary perspective, three-coordinated zinc at a homodimer interface cleft represents a simple evolutionary path to nascent enzymatic activity; from a protein engineering perspective, future efforts in de novo design of enzyme active sites may benefit from exploring clefts at protein interfaces for active site placement.

ABC transport systems provide selective passage of metabolites across cell membranes and typically require the presence of a soluble binding protein with high specificity to a specific ligand. In addition to their primary role in nutrient gathering, the binding proteins associated with bacterial transport systems have been studied for their potential to serve as design scaffolds for the development of fluorescent protein biosensors. In this work, we used Fourier transform infrared spectroscopy and molecular dynamics simulations to investigate the physicochemical properties of a hyperthermophilic binding protein from Thermotoga maritima. We demonstrated preferential binding for the polar amino acid arginine and experimentally monitored the significant stabilization achieved upon binding of ligand to protein. The effect of temperature, pH, and detergent was also studied to provide a more complete picture of the protein dynamics. A protein structure model was obtained and molecular dynamic experiments were performed to investigate and couple the spectroscopic observations with specific secondary structural elements. The data determined the presence of a buried beta-sheet providing significant stability to the protein under all conditions investigated. The specific amino acid residues responsible for arginine binding were also identified. Our data on dynamics and stability will contribute to our understanding of bacterial binding protein family members and their potential biotechnological applications.

Fluorescent protein biosensors, which exhibit a significant change in fluorescence based on the physical interaction between protein and ligand, may prove to be effective tools to measure a variety of analytes. In particular, real-time monitoring of glucose levels has potential applications in bioprocess monitoring and in minimizing health complications caused by diabetes. In this work, site-directed mutagenesis of the Escherichia coli glucose/galactose binding protein (GGBP) was used to engineer double-cysteine mutations that allowed selective covalent attachment of thiol-reactive dyes. Because GGBP undergoes a large conformational change on the addition of glucose, rational placement of these sites allowed glucose-dependent spatial realignment of the two fluorophores, which was monitored as a change in fluorescence intensity and extinction coefficients. Using targeted mutagenesis of the GGBP binding pocket, glucose biosensors were created to measure concentrations spanning five orders of magnitude (0.04–12,000 μM). The glucose biosensor retained its function in complex solutions that contained realistic concentrations of protein and potential interfering agents found in blood serum. In addition to the development of a fluorescent protein sensor for glucose, this work helps to expand the spectroscopic tools used for the detection of conformational movements within a single polypeptide chain.

Protein structures evolved through a complex interplay of cooperative interactions and it is still very challenging to design new protein folds de novo. Here, we present a strategy to design self-assembling polypeptide nanostructured polyhedra, based on modularization using orthogonal dimerizing segments. We designed end experimentally demonstrated formation of the tetrahedron that self-assembles from a single polypeptide chain comprising 12 concatenated coiled-coil-forming segments separated by flexible peptide hinges. Path of the polypeptide chain is guided by the defined order of segments that traverse each of the 6 edges of the tetrahedron exactly twice, forming coiled-coil dimers with their corresponding partners. Coincidence of the polypeptide termini in the same vertex is demonstrated by reconstitution of the split fluorescent protein by the polypeptide with the correct tetrahedral topology, while polypeptides with a deleted or scrambled segment order fail to self-assemble correctly. This design platform provides the basis for construction of new topological polypeptide folds based on the set of orthogonal interacting polypeptide segments.

Protein-protein interactions are critical for many biological processes, and over the past several decades, this importance has prompted researchers to investigate the physical and chemical bases of protein binding. How much do we now understand about how proteins interact? Perhaps the most rigorous way to answer this question is to endeavor to design, at an atomic level of detail, such an interaction from scratch. On page 816 of this issue, Fleishman et al. ( 1 ) take on this challenge. They used a computational method that enabled them to design two proteins that bind to a preselected surface on an influenza virus. This work demonstrates how far we have come in understanding and being able to predict protein-protein interactions, and the technique could prove useful for developing biosensors, reagents, and more effective drugs.

Reengineering protein surfaces to exhibit high net charge, referred to as "supercharging", can improve reversibility of unfolding by preventing aggregation of partially unfolded states. Incorporation of charged side chains should be optimized while considering structural and energetic consequences, as numerous mutations and accumulation of like-charges can also destabilize the native state. A previously demonstrated approach deterministically mutates flexible polar residues (amino acids DERKNQ) with the fewest average neighboring atoms per side chain atom (AvNAPSA). Our approach uses Rosetta-based energy calculations to choose the surface mutations. Both protocols are available for use through the ROSIE web server. The automated Rosetta and AvNAPSA approaches for supercharging choose dissimilar mutations, raising an interesting division in surface charging strategy. Rosetta-supercharged variants of GFP (RscG) ranging from -11 to -61 and +7 to +58 were experimentally tested, and for comparison, we re-tested the previously developed AvNAPSA-supercharged variants of GFP (AscG) with +36 and -30 net charge. Mid-charge variants demonstrated ∼3-fold improvement in refolding with retention of stability. However, as we pushed to higher net charges, expression and soluble yield decreased, indicating that net charge or mutational load may be limiting factors. Interestingly, the two different approaches resulted in GFP variants with similar refolding properties. Our results show that there are multiple sets of residues that can be mutated to successfully supercharge a protein, and combining alternative supercharge protocols with experimental testing can be an effective approach for charge-based improvement to refolding.

The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code’s difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step ‘serverification’ protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org.