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The FastDesign protocol in the molecular modeling program Rosetta iterates between sequence optimization and structure refinement to stabilize de novo designed protein structures and complexes. FastDesign has been used previously to design novel protein folds and assemblies with important applications in research and medicine. To promote sampling of alternative conformations and sequences, FastDesign includes stages where the energy landscape is smoothened by reducing repulsive forces. Here, we discover that this process disfavors larger amino acids in the protein core because the protein compresses in the early stages of refinement. By testing alternative ramping strategies for the repulsive weight, we arrive at a scheme that produces lower energy designs with more native-like sequence composition in the protein core. We further validate the protocol by designing and experimentally characterizing over 4000 proteins and show that the new protocol produces higher stability proteins. This article is protected by copyright. All rights reserved.

The FastDesign protocol in the molecular modeling program Rosetta iterates between sequence optimization and structure refinement to stabilize de novo designed protein structures and complexes. FastDesign has been used previously to design novel protein folds and assemblies with important applications in research and medicine. To promote sampling of alternative conformations and sequences, FastDesign includes stages where the energy landscape is smoothened by reducing repulsive forces. Here, we discover that this process disfavors larger amino acids in the protein core because the protein compresses in the early stages of refinement. By testing alternative ramping strategies for the repulsive weight, we arrive at a scheme that produces lower energy designs with more native-like sequence composition in the protein core. We further validate the protocol by designing and experimentally characterizing over 4000 proteins and show that the new protocol produces higher stability proteins.

Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities.

Sactipeptides are ribosomally-synthesized peptides that contain a characteristic thioether bridge (sactionine bond) that is installed posttranslationally and is absolutely required for their antibiotic activity. Sactipeptide biosynthesis requires a unique family of radical SAM enzymes, which contain multiple [4Fe-4S] clusters, to form the requisite thioether bridge between a cysteine and the α-carbon of an opposing amino acid through radical-based chemistry. Here we present the structure of the sactionine bond-forming enzyme CteB, from Clostridium thermocellum ATCC 27405, with both SAM and an N-terminal fragment of its peptidyl-substrate at 2.04 Å resolution. CteB has the (β/α)(6)-TIM barrel fold that is characteristic of radical SAM enzymes, as well as a C-terminal SPASM domain that contains two auxiliary [4Fe-4S] clusters. Importantly, one [4Fe-4S] cluster in the SPASM domain exhibits an open coordination site in absence of peptide substrate, which is coordinated by a peptidyl-cysteine residue in the bound state. The crystal structure of CteB also reveals an accessory N-terminal domain that has high structural similarity to a recently discovered motif present in several enzymes that act on ribosomally-synthesized and post-translationally modified peptides (RiPPs), known as a RiPP precursor peptide recognition element (RRE). This crystal structure is the first of a sactionine bond forming enzyme and sheds light on structures and mechanisms of other members of this class such as AlbA or ThnB.

Proteins perform an amazingly diverse set of functions in all aspects of life. Critical to the function of many proteins are the highly specific three-dimensional structures they adopt. For this reason, there is strong interest in learning how to rationally design proteins that adopt user-defined structures. Over the last 25 years, there has been significant progress in the field of computational protein design as rotamer-based sequence optimization protocols have enabled accurate design of protein tertiary and quaternary structure. In this award article, I will summarize how the molecular modeling program Rosetta is used to design new protein structures and describe how we have taken advantage of this capability to create proteins that have important applications in research and medicine. I will highlight three protein design stories: the use of protein interface design to create therapeutic bispecific antibodies, the engineering of light-inducible proteins that can be used to recruit proteins to specific locations in the cell, and the de novo design of new protein structures from pieces of naturally occurring proteins.

The prediction of protein three-dimensional structure from amino acid sequence has been a grand challenge problem in computational biophysics for decades, owing to its intrinsic scientific interest and also to the many potential applications for robust protein structure prediction algorithms, from genome interpretation to protein function prediction. More recently, the inverse problem - designing an amino acid sequence that will fold into a specified three-dimensional structure - has attracted growing attention as a potential route to the rational engineering of proteins with functions useful in biotechnology and medicine. Methods for the prediction and design of protein structures have advanced dramatically in the past decade. Increases in computing power and the rapid growth in protein sequence and structure databases have fuelled the development of new data-intensive and computationally demanding approaches for structure prediction. New algorithms for designing protein folds and protein-protein interfaces have been used to engineer novel high-order assemblies and to design from scratch fluorescent proteins with novel or enhanced properties, as well as signalling proteins with therapeutic potential. In this Review, we describe current approaches for protein structure prediction and design and highlight a selection of the successful applications they have enabled.

Protein binding specificities can be manipulated by redesigning contacts that already exist at an interface or by expanding the interface to allow interactions with residues adjacent to the original binding site. Previously, we developed a strategy, called AnchorDesign, for expanding interfaces around linear binding epitopes. The epitope is embedded in a loop of a scaffold protein, in our case a monobody, and then surrounding residues on the monobody are optimized for binding using directed evolution or computational design. Using this strategy, we have increased binding affinities by over 100-fold, but we have not tested whether it can be used to control protein binding specificities. Here, we test whether AnchorDesign can be used to engineer a monobody that binds specifically to the Mitogen-activated protein kinase (MAPK) p38α, but not to the related MAPKs ERK2 and JNK. To anchor the binding interaction, we used a small (D) docking motif from the Mitogen-activated protein kinase kinase (MAP2K) MKK6 that interacts with similar affinity to p38α and ERK2. Our hypothesis was that by embedding the motif in a larger protein that we could expand the interface and create contacts with residues that are not conserved between p38α and ERK2. Molecular modeling was used to inform insertion of the D motif into the monobody and a combination of phage and yeast display were used to optimize the interface. Binding experiments demonstrate that the engineered monobody binds to the target surface on p38α and does not exhibit detectable binding to ERK2 or JNK.

We have developed a set of protocols in the molecular modeling program Rosetta for performing requirement-driven protein design. First, the user specifies a set of structural features that need to be present in the designed protein. These requirements can be general (e.g., "create a protein with five helices"), or they can be very specific and require the correct placement of a set of amino acids to bind a ligand. Next, a large set of protein models are generated that satisfy the design requirements. The models are built using a method that we recently introduced into Rosetta, called SEWING, that rapidly assembles novel protein backbones by combining pieces of naturally occurring proteins. In the last step of the process, rotamer-based sequence optimization and backbone refinement are performed with Rosetta, and a variety of quality metrics are used to pick sequences for experimental characterization. Here we describe the input files and user options needed to run SEWING and perform requirement-driven design and provide detailed instructions for two specific applications of the process: the design of new structural elements at a protein-protein interface and the design of ligand binding sites.

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

β‐sheets often have one face packed against the core of the protein and the other facing solvent. Mutational studies have indicated that the solvent‐facing residues can contribute significantly to protein stability, and that the preferred amino acid at each sequence position is dependent on the precise structure of the protein backbone and the identity of the neighboring amino acids. This suggests that the most advantageous methods for designing β‐sheet surfaces will be approaches that take into account the multiple energetic factors at play including side chain rotamer preferences, van der Waals forces, electrostatics, and desolvation effects. Here, we show that the protein design software Rosetta, which models these energetic factors, can be used to dramatically increase protein stability by optimizing interactions on the surfaces of small β‐sheet proteins. Two design variants of the β‐sandwich protein from tenascin were made with 7 and 14 mutations respectively on its β‐sheet surfaces. These changes raised the thermal midpoint for unfolding from 45°C to 64°C and 74°C. Additionally, we tested an empirical approach based on increasing the number of potential salt bridges on the surfaces of the β‐sheets. This was not a robust strategy for increasing stability, as three of the four variants tested were unfolded.

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.

The computer-based design of PPIs (protein–protein interactions) is a challenging problem because large desolvation and entropic penalties must be overcome by the creation of favourable hydrophobic and polar contacts at the target interface. Indeed, many computationally designed interactions fail to form when tested in the laboratory. In the present article, we highlight strategies our laboratory has been pursuing to make interface design more tractable. Our general approach has been to make use of structural motifs found in native proteins that are predisposed to interact with a particular binding geometry, and then further bolster these anchor points with favourable hydrophobic contacts. We describe the use of three different anchor points, i.e. β-strand pairing, metal binding and the docking of α-helix into a groove, to successfully design new interfaces. In several cases, high-resolution crystal structures show that the design models closely match the experimental structure. In addition, we have tested the use of buried hydrogen-bond networks as a source of affinity and specificity at interfaces. In these cases, the designed complexes did not form, highlighting the challenges associated with designing buried polar interactions.

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta’s success is the energy function: amodel parameterized from small molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, beta_nov15. Applying these concepts,we explain how to use Rosetta energies to identify and analyze the features of biomolecular models.Finally, we discuss the latest advances in the energy function that extend capabilities from soluble proteins to also include membrane proteins, peptides containing non-canonical amino acids, carbohydrates, nucleic acids, and other macromolecules.

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.

Lysine selectivity is of critical importance during polyubiquitin chain formation because the identity of the lysine controls the biological outcome. Ubiquitins are covalently linked in polyubiquitin chains through one of seven lysine residues on its surface and the C terminus of adjacent protomers. Lys 48-linked polyubiquitin chains signal for protein degradation; however, the structural basis for Lys 48 selectivity remains largely unknown. The ubiquitin-conjugating enzyme Ube2R1/2 has exquisite specificity for Lys 48, and computational docking of Ube2R1/2 and ubiquitin predicts that Lys 48 is guided to the active site through a key electrostatic interaction between Arg 54 on ubiquitin and Asp 143 on Ube2R1/2. The validity of this interaction was confirmed through biochemical experiments. Since structural examples involving Arg 54 in protein-ubiquitin complexes are exceedingly rare, these results provide additional insight into how ubiquitin-protein complexes can be stabilized. We discuss how these findings relate to how other ubiquitin-conjugating enzymes direct the lysine specificity of polyubiquitin chains.

SummaryProtein design tests our understanding of protein stability and structure. Successful design methods should allow the exploration of sequence space not found in nature. However, when redesigning naturally occurring protein structures, most fixed backbone design algorithms return amino acid sequences that share strong sequence identity with wild-type sequences, especially in the protein core. This behavior places a restriction on functional space that can be explored and is not consistent with observations from nature, where sequences of low identity have similar structures. Here, we allow backbone flexibility during design to mutate every position in the core (38 residues) of a four-helix bundle protein. Only small perturbations to the backbone, 1–2 Å, were needed to entirely mutate the core. The redesigned protein, DRNN, is exceptionally stable (melting point >140°C). An NMR and X-ray crystal structure show that the side chains and backbone were accurately modeled (all-atom RMSD = 1.3 Å).

Computational design of novel protein–protein interfaces is a test of our understanding of protein interactions and has the potential to allow modification of cellular physiology. Methods for designing high-affinity interactions that adopt a predetermined binding mode have proved elusive, suggesting the need for new strategies that simplify the design process. A solvent-exposed backbone on a β-strand is thought of as “sticky” and β-strand pairing stabilizes many naturally occurring protein complexes. Here, we computationally redesign a monomeric protein to form a symmetric homodimer by pairing exposed β-strands to form an intermolecular β-sheet. A crystal structure of the designed complex closely matches the computational model (rmsd = 1.0 Å ). This work demonstrates that β-strand pairing can be used to computationally design new interactions with high accuracy.

Naturally occurring proteins often consist of multiple distinct domains joined by linker regions. Similarly, the ability to combine globular protein domains through engineered linkers would allow the creation of a wide variety of complex and useful multifunctional proteins. Recent advances in computational design of protein structures have enabled highly accurate design of novel protein structures. In this chapter we outline a computational protocol for the de novo design of protein linkers, and apply this protocol to the design of a helical linker between two rigid protein domains.

SummaryB. stearothermophilus tryptophanyl-tRNA synthetase catalysis proceeds via high-energy protein conformations. Unliganded MD trajectories of the pretransition-state complex with Mg2+•ATP and the (post) transition-state analog complex with adenosine tetraphosphate relax rapidly in opposite directions, the former regressing, the latter progressing along the structural reaction coordinate. The two crystal structures (rmsd 0.7 Å) therefore lie on opposite sides of a conformational free-energy maximum as the chemical transition state forms. SNAPP analysis illustrates the complexity of the associated long-range conformational coupling. Switching interactions in four nonpolar core regions are locally isoenergetic throughout the transition. Different configurations, however, propagate their effects to unfavorable, longer-range interactions at the molecular surface. Designed mutation shows that switching interactions enhance the rate, perhaps by destabilizing the ground state immediately before the transition state and limiting nonproductive diffusion before and after the chemical transition state, thereby reducing the activation entropy. This paradigm may apply broadly to energy-transducing enzymes.

The ability to manipulate protein binding affinities is important for the development of proteins as biosensors, industrial reagents, and therapeutics. We have developed a structure-based method to rationally predict single mutations at protein-protein interfaces that enhance binding affinities. The protocol is based on the premise that increasing buried hydrophobic surface area and/or reducing buried hydrophilic surface area will generally lead to enhanced affinity if large steric clashes are not introduced and buried polar groups are not left without a hydrogen bond partner. The procedure selects affinity enhancing point mutations at the protein-protein interface using three criteria: 1) the mutation must be from a polar amino acid to a non-polar amino acid or from a non-polar amino acid to a larger non-polar amino acid, 2) the free energy of binding as calculated with the Rosetta protein modeling program should be more favorable than the free energy of binding calculated for the wild type complex and 3) the mutation should not be predicted to significantly destabilize the monomers. The Rosetta energy function emphasizes short-range interactions: steric repulsion, Van der Waals forces, hydrogen bonding, and an implicit solvation model that penalizes placing atoms adjacent to polar groups. The performance of the computational protocol was experimentally tested on two separate protein complexes; Gαi1 from the heterotrimeric G-protein system bound to the RGS14 GoLoco motif, and the E2, UbcH7, bound to the E3, E6AP from the ubiquitin pathway. 12 single-site mutations that were predicted to be stabilizing were synthesized and characterized in the laboratory. 9 of the 12 mutations successfully increased binding affinity with 5 of these increasing binding by over 1.0 kcal/mol. To further assess our approach we searched the literature for point mutations that pass our criteria and have experimentally determined binding affinities. Of the 8 mutations identified, 5 were accurately predicted to increase binding affinity, further validating the method as a useful tool to increase protein-protein binding affinities.

Recent efforts to design de novo or redesign the sequence and structure of proteins using computational techniques have met with significant success. Most, if not all, of these computational methodologies attempt to model atomic-level interactions, and hence high-resolution structural characterization of the designed proteins is critical for evaluating the atomic-level accuracy of the underlying design force-fields. We previously used our computational protein design protocol RosettaDesign to completely redesign the sequence of the activation domain of human procarboxypeptidase A2. With 68% of the wild-type sequence changed, the designed protein, AYEdesign, is over 10 kcal/mol more stable than the wild-type protein. Here, we describe the high-resolution crystal structure and solution NMR structure of AYEdesign, which show that the experimentally determined backbone and side-chains conformations are effectively superimposable with the computational model at atomic resolution. To isolate the origins of the remarkable stabilization, we have designed and characterized a new series of procarboxypeptidase mutants that gain significant thermodynamic stability with a minimal number of mutations; one mutant gains more than 5 kcal/mol of stability over the wild-type protein with only four amino acid changes. We explore the relationship between force-field smoothing and conformational sampling by comparing the experimentally determined free energies of the overall design and these focused subsets of mutations to those predicted using modified force-fields, and both fixed and flexible backbone sampling protocols.

The structurally defined ubiquitin-like homology fold (UBL) can engage in several unique protein–protein interactions and many of these complexes have been characterized with high-resolution techniques. Using Rosetta's structural classification tools, we have created the Ubiquitin Structural Relational Database (UbSRD), an SQL database of features for all 509 UBL-containing structures in the PDB, allowing users to browse these structures by protein–protein interaction and providing a platform for quantitative analysis of structural features. We used UbSRD to define the recognition features of ubiquitin (UBQ) and SUMO observed in the PDB and the orientation of the UBQ tail while interacting with certain types of proteins. While some of the interaction surfaces on UBQ and SUMO overlap, each molecule has distinct features that aid in molecular discrimination. Additionally, we find that the UBQ tail is malleable and can adopt a variety of conformations upon binding. UbSRD is accessible as an online resource at rosettadesign.med.unc.edu/ubsrd.

G-proteins cycle between an inactive GDP-bound state and an active GTP-bound state, serving as molecular switches that coordinate cellular signaling. We recently used phage display to identify a series of peptides that bind G alpha subunits in a nucleotide-dependent manner [Johnston, C. A., Willard, F. S., Jezyk, M. R., Fredericks, Z., Bodor, E. T., Jones, M. B., Blaesius, R., Watts, V. J., Harden, T. K., Sondek, J., Ramer, J. K., and Siderovski, D. P. (2005) Structure 13, 1069-1080]. Here we describe the structural features and functions of KB-1753, a peptide that binds selectively to GDP x AlF4(-)- and GTPgammaS-bound states of G alpha(i) subunits. KB-1753 blocks interaction of G alpha(transducin) with its effector, cGMP phosphodiesterase, and inhibits transducin-mediated activation of cGMP degradation. Additionally, KB-1753 interferes with RGS protein binding and resultant GAP activity. A fluorescent KB-1753 variant was found to act as a sensor for activated G alpha in vitro. The crystal structure of KB-1753 bound to G alpha(i1) x GDP x AlF4(-) reveals binding to a conserved hydrophobic groove between switch II and alpha3 helices and, along with supporting biochemical data and previous structural analyses, supports the notion that this is the site of effector interactions for G alpha(i) subunits.

Protein conformational switches are ubiquitous in nature and often regulate key biological processes. To design new proteins that can switch conformation, protein designers have focused on the two key components of protein switches: the amino acid sequence must be compatible with the multiple target states and there must be a mechanism for perturbing the relative stability of these states. Proteins have been designed that can switch between folded and disordered states, between distinct folded states and between different aggregation states. A variety of trigger mechanisms have been used, including pH shifts, post-translational modification and ligand binding. Recently, computational protein design methods have been applied to switch design. These include algorithms for designing novel ligand-binding sites and simultaneously optimizing a sequence for multiple target structures.

A major challenge of computational protein design is the creation of novel proteins with arbitrarily chosen three-dimensional structures. Here, we used a general computational strategy that iterates between sequence design and structure prediction to design a 93-residue α/β protein called Top7 with a novel sequence and topology. Top7 was found experimentally to be folded and extremely stable, and the x-ray crystal structure of Top7 is similar (root mean square deviation equals 1.2 angstroms) to the design model. The ability to design a new protein fold makes possible the exploration of the large regions of the protein universe not yet observed in nature.

A previously developed computer program for protein design, RosettaDesign, was used to predict low free energy sequences for nine naturally occurring protein backbones. RosettaDesign had no knowledge of the naturally occurring sequences and on average 65% of the residues in the designed sequences differ from wild-type. Synthetic genes for ten completely redesigned proteins were generated, and the proteins were expressed, purified, and then characterized using circular dichroism, chemical and temperature denaturation and NMR experiments. Although high-resolution structures have not yet been determined, eight of these proteins appear to be folded and their circular dichroism spectra are similar to those of their wild-type counterparts. Six of the proteins have stabilities equal to or up to 7 kcal/mol greater than their wild-type counterparts, and four of the proteins have NMR spectra consistent with a well-packed, rigid structure. These encouraging results indicate that the computational protein design methods can, with significant reliability, identify amino acid sequences compatible with a target protein backbone.

We have improved the original Rosetta centroid/backbone decoy set by increasing the number of proteins and frequency of near native models and by building on sidechains and minimizing clashes. The new set consists of 1,400 model structures for 78 different and diverse protein targets and provides a challenging set for the testing and evaluation of scoring functions. We evaluated the extent to which a variety of all-atom energy functions could identify the native and close-to-native structures in the new decoy sets. Of various implicit solvent models, we found that a solvent-accessible surface area-based solvation provided the best enrichment and discrimination of close-to-native decoys. The combination of this solvation treatment with Lennard Jones terms and the original Rosetta energy provided better enrichment and discrimination than any of the individual terms. The results also highlight the differences in accuracy of NMR and X-ray crystal structures: a large energy gap was observed between native and non-native conformations for X-ray structures but not for NMR structures.

Light-activatable proteins allow precise spatial and temporal control of biological processes in living cells and animals. Several approaches have been developed for controlling protein localization with light, including the conditional inhibition of a nuclear localization signal (NLS) with the Light Oxygen Voltage (AsLOV2) domain of phototropin 1 from Avena sativa. In the dark, the switch adopts a closed conformation that sterically blocks the NLS motif. Upon activation with blue light the C-terminus of the protein unfolds, freeing the NLS to direct the protein to the nucleus. A previous study showed that this approach can be used to control the localization and activity of proteins in mammalian tissue culture cells. Here, we extend this result by characterizing the binding properties of a LOV/NLS switch and demonstrating that it can be used to control gene transcription in yeast. Additionally, we show that the switch, referred to as LANS (light-activated nuclear shuttle), functions in the C. elegans embryo and allows for control of nuclear localization in individual cells. By inserting LANS into the C. elegans lin-1 locus using Cas9-triggered homologous recombination, we demonstrated control of cell fate via light-dependent manipulation of a native transcription factor. We conclude that LANS can be a valuable experimental method for spatial and temporal control of nuclear localization in vivo.

The rational design of loops and turns is a key step towards creating proteins with new functions. We used a computational design procedure to create new backbone conformations in the second turn of protein L. The Protein Data Bank was searched for alternative turn conformations, and sequences optimal for these turns in the context of protein L were identified using a Monte Carlo search procedure and an energy function that favors close packing. Two variants containing 12 and 14 mutations were found to be as stable as wild-type protein L. The crystal structure of one of the variants has been solved at a resolution of 1.9 A, and the backbone conformation in the second turn is remarkably close to that of the in silico model (1.1 A RMSD) while it differs significantly from that of wild-type protein L (the turn residues are displaced by an average of 7.2 A). The folding rates of the redesigned proteins are greater than that of the wild-type protein and in contrast to wild-type protein L the second beta-turn appears to be formed at the rate limiting step in folding.

Protein L consists of a single α-helix packed on a four-stranded β-sheet formed by two symmetrically opposed β-hairpins. We use a computer-based protein design procedure to stabilize a domain-swapped dimer of protein L in which the second β-turn straightens and the C-terminal strand inserts into the β-sheet of the partner. The designed obligate dimer contains three mutations (A52V, N53P, and G55A) and has a dissociation constant of ≈700 pM, which is comparable to the dissociation constant of many naturally occurring protein dimers. The structure of the dimer has been determined by x-ray crystallography and is close to the in silico model.

A fundamental test of our current understanding of protein folding is to rationally redesign protein folding pathways. We use a computer-based design strategy to switch the folding pathway of protein G, which normally involves formation of the second, but not the first, beta-turn at the rate limiting step in folding. Backbone conformations and amino acid sequences that maximize the interaction density in the first beta-hairpin were identified, and two variants containing 11 amino acid replacements were found to be approximately 4 kcal mol-1 more stable than wild type protein G. Kinetic studies show that the redesigned proteins fold approximately 100 x faster than wild type protein and that the first beta-turn is formed and the second disrupted at the rate limiting step in folding.

Ubiquitination by HECT E3 enzymes regulates myriad processes, including tumor suppression, transcription, protein trafficking, and degradation. HECT E3s use a two-step mechanism to ligate ubiquitin to target proteins. The first step is guided by interactions between the catalytic HECT domain and the E2∼ubiquitin intermediate, which promote formation of a transient, thioester-bonded HECT∼ubiquitin intermediate. Here we report that the second step of ligation is mediated by a distinct catalytic architecture established by both the HECT E3 and its covalently linked ubiquitin. The structure of a chemically trapped proxy for an E3∼ubiquitin-substrate intermediate reveals three-way interactions between ubiquitin and the bilobal HECT domain orienting the E3∼ubiquitin thioester bond for ligation, and restricting the location of the substrate-binding domain to prioritize target lysines for ubiquitination. The data allow visualization of an E2-to-E3-to-substrate ubiquitin transfer cascade, and show how HECT-specific ubiquitin interactions driving multiple reactions are repurposed by a major E3 conformational change to promote ligation. DOI:http://dx.doi.org/10.7554/eLife.00828.001.

We have developed a protocol for identifying proteins that are predisposed to bind linear epitopes on target proteins of interest. The protocol searches through the protein database for proteins (scaffolds) that are bound to peptides with sequences similar to accessible, linear epitopes on the target protein. The sequence match is considered more significant if residues calculated to be important in the scaffold-peptide interaction are present in the target epitope. The crystal structure of the scaffold-peptide complex is then used as a template for creating a model of the scaffold bound to the target epitope. This model can then be used in conjunction with sequence optimization algorithms or directed evolution methods to search for scaffold mutations that further increase affinity for the target protein. To test the applicability of this approach we targeted three disease-causing proteins: a tuberculosis virulence factor (TVF), the apical membrane antigen (AMA) from malaria, and hemagglutinin from influenza. In each case the best scoring scaffold was tested, and binders with Kds equal to 37 μM and 50 nM for TVF and AMA, respectively, were identified. A web server (http://rosettadesign.med.unc.edu/scaffold/) has been created for performing the scaffold search process with user-defined target sequences.

The accurate design of new protein–protein interactions is a longstanding goal of computational protein design. However, most computationally designed interfaces fail to form experimentally. This investigation compares five previously described successful de novo interface designs with 158 failures. Both sets of proteins were designed with the molecular modeling program Rosetta. Designs were considered a success if a high-resolution crystal structure of the complex closely matched the design model and the equilibrium dissociation constant for binding was less than 10 μM. The successes and failures represent a wide variety of interface types and design goals including heterodimers, homodimers, peptide-protein interactions, one-sided designs (i.e., where only one of the proteins was mutated) and two-sided designs. The most striking feature of the successful designs is that they have fewer polar atoms at their interfaces than many of the failed designs. Designs that attempted to create extensive sets of interface-spanning hydrogen bonds resulted in no detectable binding. In contrast, polar atoms make up more than 40% of the interface area of many natural dimers, and native interfaces often contain extensive hydrogen bonding networks. These results suggest that Rosetta may not be accurately balancing hydrogen bonding and electrostatic energies against desolvation penalties and that design processes may not include sufficient sampling to identify side chains in preordered conformations that can fully satisfy the hydrogen bonding potential of the interface.

SummaryPhotocontrol of functional peptides is a powerful tool for spatial and temporal control of cell signaling events. We show that the genetically encoded light-sensitive LOV2 domain of Avena Sativa phototropin 1 (AsLOV2) can be used to reversibly photomodulate the affinity of peptides for their binding partners. Sequence analysis and molecular modeling were used to embed two peptides into the Jα helix of the AsLOV2 domain while maintaining AsLOV2 structure in the dark but allowing for binding to effector proteins when the Jα helix unfolds in the light. Caged versions of the ipaA and SsrA peptides, LOV-ipaA and LOV-SsrA, bind their targets with 49- and 8-fold enhanced affinity in the light, respectively. These switches can be used as general tools for light-dependent colocalization, which we demonstrate with photo-activable gene transcription in yeast.

The inhibitory switch (IS) domain of p21-activated kinase 1 (PAK1) stabilizes full-length PAK1 in an inactive conformation by binding to the PAK1 kinase domain. Competitive binding of small guanosine triphosphatases to the IS domain disrupts the autoinhibitory interactions and exposes the IS domain binding site on the surface of the kinase domain. To build an affinity reagent that selectively binds the activated state of PAK1, we used molecular modeling to reengineer the isolated IS domain so that it was soluble and stable, did not bind to guanosine triphosphatases and bound more tightly to the PAK1 kinase domain. Three design strategies were tested: in the first and second cases, extension and redesign of the N-terminus were used to expand the hydrophobic core of the domain, and in the third case, the termini were redesigned to be adjacent in space so that the domain could be stabilized by insertion into a loop in a host cyan fluorescent protein (CFP). The best-performing design, called CFP-PAcKer, was based on the third strategy and bound the kinase domain of PAK1 with an affinity of 400 nM. CFP-PAcKer binds more tightly to a full-length variant of PAK1 that is stabilized in the “open” state (Kd = 3.3 μM) than to full-length PAK1 in the “closed” state (undetectable affinity), and binding can be monitored with fluorescence by placing an environmentally sensitive fluorescence dye on CFP-PAcKer adjacent to the binding site.

Background Few existing protein-protein interface design methods allow for extensive backbone rearrangements during the design process. There is also a dichotomy between redesign methods, which take advantage of the native interface, and de novo methods, which produce novel binders. Methodology Here, we propose a new method for designing novel protein reagents that combines advantages of redesign and de novo methods and allows for extensive backbone motion. This method requires a bound structure of a target and one of its natural binding partners. A key interaction in this interface, the anchor, is computationally grafted out of the partner and into a surface loop on the design scaffold. The design scaffold's surface is then redesigned with backbone flexibility to create a new binding partner for the target. Careful choice of a scaffold will bring experimentally desirable characteristics into the new complex. The use of an anchor both expedites the design process and ensures that binding proceeds against a known location on the target. The use of surface loops on the scaffold allows for flexible-backbone redesign to properly search conformational space. Conclusions and Significance This protocol was implemented within the Rosetta3 software suite. To demonstrate and evaluate this protocol, we have developed a benchmarking set of structures from the PDB with loop-mediated interfaces. This protocol can recover the correct loop-mediated interface in 15 out of 16 tested structures, using only a single residue as an anchor.

The de novo design of protein-binding peptides is challenging because it requires the identification of both a sequence and a backbone conformation favorable for binding. We used a computational strategy that iterates between structure and sequence optimization to redesign the C-terminal portion of the RGS14 GoLoco motif peptide so that it adopts a new conformation when bound to Gα(i1). An X-ray crystal structure of the redesigned complex closely matches the computational model, with a backbone root-mean-square deviation of 1.1 Å.

Some protein design tasks cannot be modeled by the traditional single state design strategy of finding a sequence that is optimal for a single fixed backbone. Such cases require multistate design, where a single sequence is threaded onto multiple backbones (states) and evaluated for its strengths and weaknesses on each backbone. For example, to design a protein that can switch between two specific conformations, it is necessary to to find a sequence that is compatible with both backbone conformations. We present in this paper a generic implementation of multistate design that is suited for a wide range of protein design tasks and demonstrate in silico its capabilities at two design tasks: one of redesigning an obligate homodimer into an obligate heterodimer such that the new monomers would not homodimerize, and one of redesigning a promiscuous interface to bind to only a single partner and to no longer bind the rest of its partners. Both tasks contained negative design in that multistate design was asked to find sequences that would produce high energies for several of the states being modeled. Success at negative design was assessed by computationally redocking the undesired protein-pair interactions; we found that multistate design's accuracy improved as the diversity of conformations for the undesired protein-pair interactions increased. The paper concludes with a discussion of the pitfalls of negative design, which has proven considerably more challenging than positive design.

GoLoco motif proteins bind to the inhibitory G(i) subclass of G-protein α subunits and slow the release of bound GDP; this interaction is considered critical to asymmetric cell division and neuro-epithelium and epithelial progenitor differentiation. To provide protein tools for interrogating the precise cellular role(s) of GoLoco motif/Gα(i) complexes, we have employed structure-based protein design strategies to predict gain-of-function mutations that increase GoLoco motif binding affinity. Here, we describe fluorescence polarization and isothermal titration calorimetry measurements showing three predicted Gα(i1) point mutations, E116L, Q147L, and E245L; each increases affinity for multiple GoLoco motifs. A component of this affinity enhancement results from a decreased rate of dissociation between the Gα mutants and GoLoco motifs. For Gα(i1)(Q147L), affinity enhancement was seen to be driven by favorable changes in binding enthalpy, despite reduced contributions from binding entropy. The crystal structure of Gα(i1)(Q147L) bound to the RGS14 GoLoco motif revealed disorder among three peptide residues surrounding a well defined Leu-147 side chain. Monte Carlo simulations of the peptide in this region showed a sampling of multiple backbone conformations in contrast to the wild-type complex. We conclude that mutation of Glu-147 to leucine creates a hydrophobic surface favorably buried upon GoLoco peptide binding, yet the hydrophobic Leu-147 also promotes flexibility among residues 511-513 of the RGS14 GoLoco peptide.

Metal coordination is a key structural and functional component of a large fraction of proteins. Given this dual role we considered the possibility that metal coordination may have played a templating role in the early evolution of protein folds and complexes. We describe here a rational design approach, Metal Templated Interface Redesign (MeTIR), that mimics the time course of a hypothetical evolutionary pathway for the formation of stable protein assemblies through an initial metal coordination event. Using a folded monomeric protein, cytochrome cb 562 , as a building block we show that its non-self-associating surface can be made self-associating through a minimal number of mutations that enable Zn coordination. The protein interfaces in the resulting Zn-directed, D 2 -symmetrical tetramer are subsequently redesigned, yielding unique protein architectures that self-assemble in the presence or absence of metals. Aside from its evolutionary implications, MeTIR provides a route to engineer de novo protein interfaces and metal coordination environments that can be tuned through the extensive noncovalent bonding interactions in these interfaces.

Amino acid side chains adopt a discrete set of favorable conformations typically referred to as rotamers. The relative energies of rotamers partially determine which side chain conformations are more often observed in protein structures and accurate estimates of these energies are important for predicting protein structure and designing new proteins. Protein modelers typically calculate side chain rotamer energies by using molecular mechanics (MM) potentials or by converting rotamer probabilities from the protein database (PDB) into relative free energies. One limitation of the knowledge-based energies is that rotamer preferences observed in the PDB can reflect internal side chain energies as well as longer-range interactions with the rest of the protein. Here, we test an alternative approach for calculating rotamer energies. We use three different quantum mechanics (QM) methods (second order Moller-Plesset (MP2), density functional theory (DFT) energy calculation using the B3LYP functional, and Hartree-Fock) to calculate the energy of amino acid rotamers in a dipeptide model system, and then use these pre-calculated values in side chain placement simulations. Energies were calculated for over 36,000 different conformations of leucine, isoleucine, and valine dipeptides with backbone torsion angles from the helical and strand regions of the Ramachandran plot. In a subset of cases these energies differ significantly from those calculated with standard molecular mechanics potentials or those derived from PDB statistics. We find that in these cases the energies from the QM methods result in more accurate placement of amino acid side chains in structure prediction tests.

Despite having irregular structure, protein loops often adopt specific conformations that are critical to protein function. Most studies in de novo protein design have focused on creating proteins with regular elements of secondary structure connected by very short loops or turns. To design longer protein loops that adopt specific conformations, we have developed a protocol within the Rosetta molecular modeling program that iterates between optimizing the sequence and conformation of a loop in search of low-energy sequence–structure pairs. We have tested the procedure by designing 10-residue loops for the connection between the second and third strand in the β-sandwich protein tenascin. Three low-energy designs from 7,200 flexible backbone trajectories were selected for experimental characterization. All three designs, called LoopA, LoopB, and LoopC, adopt stable folded structures. High-resolution crystal structures of LoopA and LoopB have been solved. LoopB adopts a structure very similar to the design model (0.46 Å rmsd), and all but one of the side chains are modeled in the correct rotamers. LoopA crystallized at low pH in a structure that differs dramatically from our design model. It forms a strand-swapped dimer mediated by hydrogen bonds to protonated glutamic acids. Gel filtration indicates that the protein is not a dimer at neutral pH. These results suggest that the high-resolution design of protein loops is possible; however, they also highlight how small changes in protein energetics can dramatically perturb the low free energy structure of a protein.

The conjugation of ubiquitin to substrates requires a series of enzymatic reactions consisting of an activating enzyme (E1), conjugating enzymes (E2) and ligases (E3). Tagging the appropriate substrate with ubiquitin is achieved by specific E2-E3 and E3-substrate interactions. E6AP, a member of the HECT family of E3s, has been previously shown to bind and function with the E2s UbcH7 and UbcH8. To decipher the sequence determinants of this specificity we have developed a quantitative E2-E3 binding assay based on fluorescence polarization and used this assay to measure the affinity of wild-type and mutant E2-E6AP interactions. Alanine scanning of the E6AP-UbcH7 binding interface identified four side-chains on UbcH7 and six side-chains on E6AP that contribute more than 1 kcal/mol to the binding free energy. Two of the hot spot residues from UbcH7 (K96 and K100) are conserved in UbcH8 but vary across other E2s. To determine if these are key specificity determining residues, we attempted to induce a tighter association between the E2 UbcH5b and E6AP by mutating the corresponding positions in UbcH5b to lysine residues. Surprisingly, the mutations had little effect, but rather a mutation at UbcH7 position 4, which is not at a hot spot on the UbcH7-E6AP interface, significantly strengthened UbcH5bs affinity for E6AP. This result indicates that E2-E3 binding specificities are a function of both favorable interactions that promote binding, and unfavorable interactions that prevent binding with unwanted partners.

The emergence of polypeptide catalysts for amino acid activation, the slowest step in protein synthesis, poses a significant puzzle associated with the origin of biology. This problem is compounded as the 20 contemporary aminoacyl-tRNA synthetases belong to two quite distinct families. We describe here the use of protein design to show experimentally that a minimal class I aminoacyl-tRNA synthetase active site might have functioned in the distant past. We deleted the anticodon binding domain from tryptophanyl-tRNA synthetase and fused the discontinuous segments comprising its active site. The resulting 130 residue minimal catalytic domain activates tryptophan. This residual catalytic activity constitutes the first experimental evidence that the conserved class I signature sequences, HIGH and KMSKS, might have arisen in-frame, opposite motifs 2 and 1 from class II, as complementary sense and antisense strands of the same ancestral gene.

The RosettaDesign server identifies low energy amino acid sequences for target protein structures (http://rosettadesign.med.unc.edu). The client provides the backbone coordinates of the target structure and specifies which residues to design. The server returns to the client the sequences, coordinates and energies of the designed proteins. The simulations are performed using the design module of the Rosetta program (RosettaDesign). RosettaDesign uses Monte Carlo optimization with simulated annealing to search for amino acids that pack well on the target structure and satisfy hydrogen bonding potential. RosettaDesign has been experimentally validated and has been used previously to stabilize naturally occurring proteins and design a novel protein structure.

Over the past 10 years there has been tremendous success in the area of computational protein design. Protein design software has been used to stabilize proteins, solubilize membrane proteins, design intermolecular interactions, and design new protein structures. A key motivation for these studies is that they test our understanding of protein energetics and structure. De novo design of novel structures is a particularly rigorous test because the protein backbone must be designed in addition to the amino acid side chains. A priori it is not guaranteed that the target backbone is even designable. To address this issue, researchers have developed a variety of methods for generating protein-like scaffolds and for optimizing the protein backbone in conjunction with the amino acid sequence. These protocols have been used to design proteins from scratch and to explore sequence space for naturally occurring protein folds.

Recent advances in computational protein design have allowed exciting new insights into the sequence dependence of protein folding free energy landscapes. Whereas most previous studies have examined the sequence dependence of protein stability and folding kinetics by characterizing naturally occurring proteins and variants of these proteins that contain a small number of mutations, it is now possible to generate and characterize computationally designed proteins that differ significantly from naturally occurring proteins in sequence and/or structure. These computer-generated proteins provide insights into the determinants of protein structure, stability and folding, and make it possible to disentangle the properties of proteins that are the consequence of natural selection from those that reflect the fundamental physical chemistry of polypeptide chains.