Search

Many proteins have low thermodynamic stability, which can lead to low expression yields and limit functionality in research, industrial and clinical settings. This article introduces two, web-based tools that use the high-resolution structure of a protein along with the Rosetta molecular modeling program to predict stabilizing mutations. The protocols were recently applied to three genetically and structurally distinct proteins and successfully predicted mutations that improved thermal stability and/or protein yield. In all three cases, combining the stabilizing mutations raised the protein unfolding temperatures by more than 20°C. The first protocol evaluates point mutations and can generate a site saturation mutagenesis heatmap. The second identifies mutation clusters around user-defined positions. Both applications only require a protein structure and are particularly valuable when a deep multiple sequence alignment is not available. These tools were created to simplify protein engineering and enable research that would otherwise be infeasible due to poor expression and stability of the native molecule.

Using the molecular modeling program Rosetta, we designed a de novo protein, called SEWN0.1, which binds the heterotrimeric G protein Gα(q.) The design is helical, well‐folded, and primarily monomeric in solution at a concentration of 10 μM. However, when we solved the crystal structure of SEWN0.1 at 1.9 Å, we observed a dimer in a conformation incompatible with binding Gα(q). Unintentionally, we had designed a protein that adopts alternate conformations depending on its oligomeric state. Recently, there has been tremendous progress in the field of protein structure prediction as new methods in artificial intelligence have been used to predict structures with high accuracy. We were curious if the structure prediction method AlphaFold could predict the structure of SEWN0.1 and if the prediction depended on oligomeric state. When AlphaFold was used to predict the structure of monomeric SEWN0.1, it produced a model that resembles the Rosetta design model and is compatible with binding Gα(q), but when used to predict the structure of a dimer, it predicted a conformation that closely resembles the SEWN0.1 crystal structure. AlphaFold's ability to predict multiple conformations for a single protein sequence should be useful for engineering protein switches.

During signal transduction, the G protein, Gαq, binds and activates phospholipase C-β isozymes. Several diseases have been shown to manifest upon constitutively activating mutation of Gαq, such as uveal melanoma. Therefore, methods are needed to directly inhibit Gαq. Previously, we demonstrated that a peptide derived from a helix-turn-helix (HTH) region of PLC-β3 (residues 852–878) binds Gαq with low micromolar affinity and inhibits Gαq by competing with full-length PLC-β isozymes for binding. Since the HTH peptide is unstructured in the absence of Gαq, we hypothesized that embedding the HTH in a folded protein might stabilize the binding-competent conformation and further improve the potency of inhibition. Using the molecular modeling software Rosetta, we searched the Protein Data Bank for proteins with similar HTH structures near their surface. The candidate proteins were computationally docked against Gαq, and their surfaces were redesigned to stabilize this interaction. We then used yeast surface display to affinity mature the designs. The most potent design bound Gαq/i with high affinity in vitro (KD = 18 nM) and inhibited activation of PLC-β isozymes in HEK293 cells. We anticipate that our genetically encoded inhibitor will help interrogate the role of Gαq in healthy and disease model systems. Our work demonstrates that grafting interaction motifs into folded proteins is a powerful approach for generating inhibitors of protein–protein interactions.

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.

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at ., This Perspective reviews tools developed over the past five years in the macromolecular modeling, docking and design software Rosetta.

Protein ubiquitination involves E1, E2, and E3 trienzyme cascades. E2 and RING E3 enzymes often collaborate to first prime a substrate with a single ubiquitin (UB) and then achieve different forms of polyubiquitination: multiubiquitination of several sites and elongation of linkage-specific UB chains. Here, cryo-EM and biochemistry show that the human E3 anaphase-promoting complex/cyclosome (APC/C) and its two partner E2s, UBE2C (aka UBCH10) and UBE2S, adopt specialized catalytic architectures for these two distinct forms of polyubiquitination. The APC/C RING constrains UBE2C proximal to a substrate and simultaneously binds a substrate-linked UB to drive processive multiubiquitination. Alternatively, during UB chain elongation, the RING does not bind UBE2S but rather lures an evolving substrate-linked UB to UBE2S positioned through a cullin interaction to generate a Lys11-linked chain. Our findings define mechanisms of APC/C regulation, and establish principles by which specialized E3-E2-substrate-UB architectures control different forms of polyubiquitination.

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.

Lipoprotein lipase (LPL) is a dimeric enzyme that is responsible for clearing triglyceride-rich lipoproteins from the blood. Although LPL plays a key role in cardiovascular health, an experimentally derived three-dimensional structure has not been determined. Such a structure would aid in understanding mutations in LPL that cause familial LPL deficiency in patients and help in the development of therapeutic strategies to target LPL. A major obstacle to structural studies of LPL is that LPL is an unstable protein that is difficult to produce in the quantities needed for nuclear magnetic resonance or crystallography. We present updated LPL structural models generated by combining disulfide mapping, computational modeling, and data derived from single-molecule Förster resonance energy transfer (smFRET). We pioneer the technique of smFRET for use with LPL by developing conditions for imaging active LPL and identifying positions in LPL for the attachment of fluorophores. Using this approach, we measure LPL-LPL intermolecular interactions to generate experimental constraints that inform new computational models of the LPL dimer structure. These models suggest that LPL may dimerize using an interface that is different from the dimerization interface suggested by crystal packing contacts seen in structures of pancreatic lipase.

The use of bispecific antibodies (BsAbs) to treat human diseases is on the rise. Increasingly complex and powerful therapeutic mechanisms made possible by BsAbs are spurring innovation of novel BsAb formats and methods for their production. The long-lived in vivo pharmacokinetics, optimal biophysical properties and potential effector functions of natural IgG monoclonal (and monospecific) antibodies has resulted in a push to generate fully IgG BsAb formats with the same quaternary structure as monoclonal IgGs. The production of fully IgG BsAbs is challenging because of the highly heterogeneous pairing of heavy chains (HCs) and light chains (LCs) when produced in mammalian cells with two IgG HCs and two LCs. A solution to the HC heterodimerization aspect of IgG BsAb production was first discovered two decades ago; however, addressing the LC mispairing issue has remained intractable until recently. Here, we use computational and rational engineering to develop novel designs to the HC/LC pairing issue, and particularly for κ LCs. Crystal structures of these designs highlight the interactions that provide HC/LC specificity. We produce and characterize multiple fully IgG BsAbs using these novel designs. We demonstrate the importance of specificity engineering in both the variable and constant domains to achieve robust HC/LC specificity within all the BsAbs. These solutions facilitate the production of fully IgG BsAbs for clinical use.

The discovery of light-inducible protein-protein interactions has allowed for the spatial and temporal control of a variety of biological processes. To be effective, a photodimerizer should have several characteristics: it should show a large change in binding affinity upon light stimulation, it should not cross-react with other molecules in the cell, and it should be easily used in a variety of organisms to recruit proteins of interest to each other. To create a switch that meets these criteria we have embedded the bacterial SsrA peptide in the C-terminal helix of a naturally occurring photoswitch, the light-oxygen-voltage 2 (LOV2) domain from Avena sativa. In the dark the SsrA peptide is sterically blocked from binding its natural binding partner, SspB. When activated with blue light, the C-terminal helix of the LOV2 domain undocks from the protein, allowing the SsrA peptide to bind SspB. Without optimization, the switch exhibited a twofold change in binding affinity for SspB with light stimulation. Here, we describe the use of computational protein design, phage display, and high-throughput binding assays to create an improved light inducible dimer (iLID) that changes its affinity for SspB by over 50-fold with light stimulation. A crystal structure of iLID shows a critical interaction between the surface of the LOV2 domain and a phenylalanine engineered to more tightly pin the SsrA peptide against the LOV2 domain in the dark. We demonstrate the functional utility of the switch through light-mediated subcellular localization in mammalian cell culture and reversible control of small GTPase signaling.

Hypoxia-inducible factors (HIFs) are heterodimeric transcription factors central to hypoxia response and cancer development. Within the HIF-2 complex, one domain (HIF-2α PAS-B) contains a large (290 A3) buried cavity filled with water molecules within its hydrophobic core. Such cavities are uncommon except in the case of ligand-binding proteins, leading to the hypothesis that HIF-2α can be regulated by small molecules. The development of artificial HIF-2α inhibitors validates this hypothesis but raises questions about the impact of this cavity on HIF-2α PAS-B structure and function. To answer these points, we used computational methods to construct a repacked protein containing a smaller cavity within the native fold. Experimental validation of a five-mutation variant confirms achieving these objectives and stabilizing the folded structure. Complementary functional data establish that ligands cannot bind this variant although heterodimerization remains unchanged. Altogether, our strategy innovatively addresses the roles of solvated cavities in maintaining protein stability and function.

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).

Pathways of ubiquitin-like (UBL) molecule transfer regulate a myriad of cellular cascades. Here, we report a high-throughput assay that correlates catalytic human NEDD8 transfer to bacterial survival. The assay was utilized to screen mutant NEDD8 and NAE (NEDD8-activating enzyme) libraries to engineer a more stable NEDD8 and redesign the NEDD8-NAE interface. This approach will be useful in understanding the specificities underlying UBL pathways.

Fluorescent biosensors for living cells currently require laborious optimization and a unique design for each target. They are limited by the availability of naturally occurring ligands with appropriate target specificity. Here we describe a biosensor based on an engineered fibronectin monobody scaffold that can be tailored to bind different targets via high throughput screening. This Src family kinase (SFK) biosensor was made by derivatizing a monobody specific for activated SFK with a bright dye whose fluorescence increases upon target binding. We identified sites for dye attachment and alterations to eliminate vesiculation in living cells, providing a generalizable scaffold for biosensor production. This approach minimizes cell perturbation because it senses endogenous, unmodified target, and because sensitivity is enhanced by direct dye excitation. Automated correlation of cell velocities and SFK activity revealed that SFK are activated specifically during protrusion. Activity correlates with velocity, and peaks 1–2 microns from the leading edge.

Computational algorithms for protein design can sample large regions of sequence space, but suffer from undersampling of conformational space and energy function inaccuracies. Experimental screening of combinatorial protein libraries avoids the need for accurate energy functions, but has limited access to vast amounts of sequence space. Here, we test if these two traditionally alternative, but potentially complementary approaches can be combined to design a variant of the ubiquitin-ligase E6AP that will bind to a nonnatural partner, the NEDD8-conjugating enzyme Ubc12. Three E6AP libraries were constructed: ( i ) a naive library in which all 20 amino acids were allowed at every position on the target-binding surface of E6AP (13 positions), ( ii ) a semidirected library that varied the same residue positions as in the naive library but disallowed mutations computationally predicted to destabilize E6AP, and ( iii ) a directed library that used docking and sequence optimization simulations to identify mutations predicted to be favorable for binding Ubc12. Both of the directed libraries showed > 30-fold enrichment over the naive library after the first round of screening with a split-dihydrofolate reductase complementation assay and produced multiple tight binders ( K d K d ’s lower than 50 μM. These results indicate that protein design simulations can be used to create directed libraries that are enriched in tight binders and that in some cases it is sufficient to computationally screen for well-folded sequences without explicit binding calculations.

SummaryDegradation by the ubiquitin-proteasome system requires assembly of a polyubiquitin chain upon substrate. However, the structural and mechanistic features that enable template-independent processive chain synthesis are unknown. We show that chain assembly by ubiquitin ligase SCF and ubiquitin-conjugating enzyme Cdc34 is facilitated by the unusual nature of Cdc34-SCF transactions: Cdc34 binds SCF with nanomolar affinity, nevertheless the complex is extremely dynamic. These properties are enabled by rapid association driven by electrostatic interactions between the acidic tail of Cdc34 and a basic ‘canyon’ in the Cul1 subunit of SCF. Ab initio docking between Cdc34 and Cul1 predicts intimate contact between the tail and the basic canyon, an arrangement confirmed by crosslinking and kinetic analysis of mutants. Basic canyon residues are conserved in both Cul1 paralogs and orthologs, suggesting that the same mechanism underlies processivity for all cullin-RING ubiquitin ligases. We discuss different strategies by which processive ubiquitin chain synthesis may be achieved.

We recently described two protein G variants (NuG1 and NuG2) with redesigned first hairpins that were almost twice as stable, folded 100-fold faster, and had a switched folding mechanism relative to the wild-type protein. To test the structural accuracy of our design algorithm and to provide insights to the dramatic changes in the kinetics and thermodynamics of folding, we have now determined the crystal structures of NuG1 and NuG2 to 1.8 A and 1.85 A, respectively. We find that they adopt hairpin structures that are closer to the computational models than to wild-type protein G; the RMSD of the NuG1 hairpin to the design model and the wild-type structure are 1.7 A and 5.1 A, respectively. The crystallographic B factor in the redesigned first hairpin of NuG1 is systematically higher than the second hairpin, suggesting that the redesigned region is somewhat less rigid. A second round of structure-based design yielded new variants of NuG1 and NuG2, which are further stabilized by 0.5 kcal/mole and 0.9 kcal/mole.

A challenge in the structure-based design of specificity is modeling the negative states, i.e., the complexes that you do not want to form. This is a difficult problem because mutations predicted to destabilize the negative state might be accommodated by small conformational rearrangements. To overcome this challenge, we employ an iterative strategy that cycles between sequence design and protein docking in order to build up an ensemble of alternative negative state conformations for use in specificity prediction. We have applied our technique to the design of heterodimeric CH3 interfaces in the Fc region of antibodies. Combining computationally and rationally designed mutations produced unique designs with heterodimer purities greater than 90%. Asymmetric Fc crystallization was able to resolve the interface mutations; the heterodimer structures confirmed that the interfaces formed as designed. With these CH3 mutations, and those made at the heavy-/light-chain interface, we demonstrate one-step synthesis of four fully IgG-bispecific antibodies.

Cellular optogenetic switches, a novel class of biological tools, have improved our understanding of biological phenomena that were previously intractable. While the design and engineering of these proteins has historically varied, they are all based on borrowed elements from plant and bacterial photoreceptors. In general terms, each of the optogenetic switches designed to date exploits the endogenous light-induced change in photoreceptor conformation while repurposing its effect to target a different biological phenomenon. We focus on the well-characterized light-oxygen-voltage 2 (LOV2) domain from Avena sativa phototropin 1 as our cornerstone for design. While the function of the LOV2 domain in the context of the phototropin protein is not fully elucidated, its thorough biophysical characterization as an isolated domain has created a strong foundation for engineering of photoswitches. In this chapter, we examine the biophysical characteristics of the LOV2 domain that may be exploited to produce an optogenetic switch and summarize previous design efforts to provide guidelines for an effective design. Furthermore, we provide protocols for assays including fluorescence polarization, phage display, and microscopy that are optimized for validating, improving, and using newly designed photoswitches.

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.

We recently used computational protein design to create an extremely stable, globular protein, Top7, with a sequence and fold not observed previously in nature. Since Top7 was created in the absence of genetic selection, it provides a rare opportunity to investigate aspects of the cellular protein production and surveillance machinery that are subject to natural selection. Here we show that a portion of the Top7 protein corresponding to the final 49 C-terminal residues is efficiently mis-translated and accumulates at high levels in Escherichia coli. We used circular dichroism, size-exclusion chromatography, small-angle X-ray scattering, analytical ultra-centrifugation, and NMR spectroscopy to show that the resulting C-terminal fragment (CFr) protein adopts a compact, extremely stable, homo-dimeric structure. Based on the solution structure, we engineered an even more stable variant of CFr by disulfide-induced covalent circularisation that should be an excellent platform for design of novel functions. The accumulation of high levels of CFr exposes the high error rate of the protein translation machinery. The rarity of correspondingly stable fragments in natural proteins coupled with the observation that high quality ribosome binding sites are found to occur within E. coli protein-coding regions significantly less often than expected by random chance implies a stringent evolutionary pressure against protein sub-fragments that can independently fold into stable structures. The symmetric self-association between two identical mis-translated CFr sub-domains to generate an extremely stable structure parallels a mechanism for natural protein-fold evolution by modular recombination of protein sub-structures.

The functions of many proteins are mediated by specific conformational changes, and therefore the ability to design primary sequences capable of secondary and tertiary changes is an important step toward the creation of novel functional proteins. To this end, we have developed an algorithm that can optimize a single amino acid sequence for multiple target structures. The algorithm consists of an outer loop, in which sequence space is sampled by a Monte Carlo search with simulated annealing, and an inner loop, in which the effect of a given mutation is evaluated on the various target structures by using the rotamer packing routine and composite energy function of the protein design software, RosettaDesign. We have experimentally tested the method by designing a peptide, Sw2, which can be switched from a 2Cys-2His zinc finger-like fold to a trimeric coiled-coil fold, depending upon the pH or the presence of transition metals. Physical characterization of Sw2 confirms that it is able to reversibly adopt each intended target fold.

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.

Protein –protein docking algorithms provide a means to elucidate structural details for presently unknown complexes. Here, we present and evaluate a new method to predict protein –protein complexes from the coordinates of the unbound monomer components. The method employs a low-resolution, rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations using Monte Carlo minimization. Up to 10 5 independent simulations are carried out, and the resulting “decoys” are ranked using an energy function dominated by van der Waals interactions, an implicit solvation model, and an orientation-dependent hydrogen bonding potential. Top-ranking decoys are clustered to select the final predictions. Small-perturbation studies reveal the formation of binding funnels in 42 of 54 cases using coordinates derived from the bound complexes and in 32 of 54 cases using independently determined coordinates of one or both monomers. Experimental binding affinities correlate with the calculated score function and explain the predictive success or failure of many targets. Global searches using one or both unbound components predict at least 25% of the native residue –residue contacts in 28 of the 32 cases where binding funnels exist. The results suggest that the method may soon be useful for generating models of biologically important complexes from the structures of the isolated components, but they also highlight the challenges that must be met to achieve consistent and accurate prediction of protein –protein interactions. q 2003 Elsevier Ltd. All rights reserved

In the ubiquitin-proteasome system, protein substrates are degraded via covalent modification by a polyubiquitin chain. The polyubiquitin chain must be assembled rapidly in cells, because a chain of at least four ubiquitins is required to signal for degradation, and chain-editing enzymes in the cell may cleave premature polyubiquitin chains before achieving this critical length. The ubiquitin-conjugating enzyme Cdc34 and ubiquitin ligase SCF are capable of building polyubiquitin chains onto protein substrates both rapidly and processively; this may be explained at least in part by the atypically fast rate of Cdc34 and SCF association. This rapid association has been attributed to electrostatic interactions between the acidic C-terminal tail of Cdc34 and a feature on SCF called the basic canyon. However, the structural aspects of the Cdc34-SCF interaction and how they permit rapid complex formation remain elusive. Here, we use protein cross-linking to demonstrate that the Cdc34-SCF interaction occurs in multiple conformations, where several residues from the Cdc34 acidic tail are capable of contacting a broad region of the SCF basic canyon. Similar patterns of cross-linking are also observed between Cdc34 and the Cul1 paralog Cul2, implicating the same mechanism for the Cdc34-SCF interaction in other members of the cullin-RING ubiquitin ligases. We discuss how these results can explain the rapid association of Cdc34 and SCF.

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.

pKa values were measured for the 6 carboxylates in the N-terminal domain of L9 (NTL9) by following NMR chemical shifts as a function of pH. The contribution of each carboxylate to the pH dependent stability of NTL9 was estimated by comparing the pKa values for the native and denatured state of the protein. A set of peptides with sequences derived from NTL9 were used to model the denatured state. In the protein fragments, the pKa values measured for the aspartates varied between 3.8 and 4.1 and the pKa values measured for the glutamates varied between 4.1 and 4.6. These results indicate that the local sequence can significantly influence pKa values in the denatured state and highlight the difficulties in using standard pKa values derived from small compounds. Calculations based on the measured pKa values suggest that the free energy of unfolding of NTL9 should decrease by 4.4 kcal mol-1 when the pH is lowered from 6 to 2. In contrast, urea and thermal denaturation experiments indicate that the stability of the protein decreases by only 2.6 kcal mol-1 when the carboxylates are protonated. This discrepancy indicates that the protein fragments are not a complete representation of the denatured state and that nonlocal sequence effects perturb the pKa's in the denatured state. Increasing the salt concentration from 100 to 750 mM NaCl removes the discrepancy between the stabilities derived from denaturation experiments and the stability changes calculated from the pKa values. At high concentrations of salt there is also less variation of the pKa values measured in the protein fragments. Our results argue that in the denatured state of NTL9 there are electrostatic interactions between groups both local and nonlocal in primary sequence.

The non-homologous end joining (NHEJ) pathway is used in diverse species to repair chromosome breaks, and is defined in part by a requirement for Ku. We previously demonstrated mammalian Ku has intrinsic 5' deoxyribosephosphate (5'dRP) and apurinic/apyrimidinic (AP) lyase activity, and showed this activity is important for excising abasic site damage from ends. Here we employ systematic mutagenesis to clarify the protein requirements for this activity. We identify lysine 31 in the 70 kD subunit (Ku70 K31) as the primary candidate nucleophile required for catalysis, but additional mutation of Ku70 K160 and six other lysines within Ku80 were required to eliminate all activity. Ku from Saccharomyces cerevisiae also possesses 5'dRP/AP lyase activity, and robust activity was also reliant on lysines in Ku70 analogous to K31 and K160. By comparison, these lysines are not conserved in Xenopus laevis Ku, and Ku from this species has negligible activity. A role for residues flanking Ku70 K31 in expanding the range of abasic site contexts that can be used as substrate was also identified. Our results suggest an active site well located to provide the substrate specificity required for its biological role.

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.

International audience; The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.

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.

De novo protein design requires the identification of amino-acid sequences that favor the target-folded conformation and are soluble in water. One strategy for promoting solubility is to disallow hydrophobic residues on the protein surface during design. However, naturally occurring proteins often have hydrophobic amino acids on their surface that contribute to protein stability via the partial burial of hydrophobic surface area or play a key role in the formation of protein-protein interactions. A less restrictive approach for surface design that is used by the modeling program Rosetta is to parameterize the energy function so that the number of hydrophobic amino acids designed on the protein surface is similar to what is observed in naturally occurring monomeric proteins. Previous studies with Rosetta have shown that this limits surface hydrophobics to the naturally occurring frequency (∼28%), but that it does not prevent the formation of hydrophobic patches that are considerably larger than those observed in naturally occurring proteins. Here, we describe a new score term that explicitly detects and penalizes the formation of hydrophobic patches during computational protein design. With the new term, we are able to design protein surfaces that include hydrophobic amino acids at naturally occurring frequencies, but do not have large hydrophobic patches. By adjusting the strength of the new score term, the emphasis of surface redesigns can be switched between maintaining solubility and maximizing folding free energy.

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.

We have recently completed a full re-architecturing of the Rosetta molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy to use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as Rosetta3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This document describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

During ubiquitin conjugation, the thioester bond that links ‘donor’ ubiquitin to ubiquitin-conjugating enzyme (E2) undergoes nucleophilic attack by the ε-amino group of an acceptor lysine, resulting in formation of an isopeptide bond. Models of ubiquitination have envisioned the donor ubiquitin to be a passive participant in this process. However, we show here that the I44A mutation in ubiquitin profoundly inhibits its ability to serve as a donor for ubiquitin chain initiation or elongation, but can be rescued by computationally-predicted compensatory mutations in the E2 Cdc34. The donor defect of ubiquitin-I44A can be partially suppressed either by using a low pKa amine (hydroxylamine) as the acceptor or by performing reactions at higher pH, suggesting that the discharge defect arises in part due to inefficient deprotonation of the acceptor lysine. We propose that interaction between Cdc34 and the donor ubiquitin organizes the active site to promote efficient ubiquitination of substrate.

We substantiate our preliminary description of the class I tryptophanyl-tRNA synthetase minimal catalytic domain with details of its construction, structure, and steady-state kinetic parameters. Generating that active fragment involved deleting 65% of the contemporary enzyme, including the anticodon-binding domain and connecting peptide 1, CP1, a 74-residue internal segment from within the Rossmann fold. We used protein design (Rosetta), rather than phylogenetic sequence alignments, to identify mutations to compensate for the severe loss of modularity, thus restoring stability, as evidenced by renaturation described previously and by 70-ns molecular dynamics simulations. Sufficient solubility to enable biochemical studies was achieved by expressing the redesigned Urzyme as a maltose-binding protein fusion. Michaelis-Menten kinetic parameters from amino acid activation assays showed that, compared with the native full-length enzyme, TrpRS Urzyme binds ATP with similar affinity. This suggests that neither of the two deleted structural modules has a strong influence on ground-state ATP binding. However, tryptophan has 10(3) lower affinity, and the Urzyme has comparably reduced specificity relative to the related amino acid, tyrosine. Molecular dynamics simulations revealed how CP1 may contribute significantly to cognate amino acid specificity. As class Ia editing domains are nested within the CP1, this finding suggests that this module enhanced amino acid specificity continuously, throughout their evolution. We call this type of reconstructed protein catalyst an Urzyme (Ur prefix indicates original, primitive, or earliest). It establishes a model for recapitulating very early steps in molecular evolution in which fitness may have been enhanced by accumulating entire modules, rather than by discrete amino acid sequence changes.

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.

The importance of a protein-protein interaction to a signaling pathway can be established by showing that amino acid mutations that weaken the interaction disrupt signaling, and that additional mutations that rescue the interaction recover signaling. Identifying rescue mutations, often referred to as second-site suppressor mutations, controls against scenarios in which the initial deleterious mutation inactivates the protein or disrupts alternative protein-protein interactions. Here, we test a structure-based protocol for identifying second-site suppressor mutations that is based on a strategy previously described by Kortemme and Baker. The molecular modeling software Rosetta is used to scan an interface for point mutations that are predicted to weaken binding but can be rescued by mutations on the partner protein. The protocol typically identifies three types of specificity switches: knob-in-to-hole redesigns, switching hydrophobic interactions to hydrogen bond interactions, and replacing polar interactions with nonpolar interactions. Computational predictions were tested with two separate protein complexes; the G-protein Galpha(i1) bound to the RGS14 GoLoco motif, and UbcH7 bound to the ubiquitin ligase E6AP. Eight designs were experimentally tested. Swapping a buried hydrophobic residue with a polar residue dramatically weakened binding affinities. In none of these cases were we able to identify compensating mutations that returned binding to wild-type affinity, highlighting the challenges inherent in designing buried hydrogen bond networks. The strongest specificity switches were a knob-in-to-hole design (20-fold) and the replacement of a charge-charge interaction with nonpolar interactions (55-fold). In two cases, specificity was further tuned by including mutations distant from the initial design. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

The computer-based design of protein-protein interactions is a rigorous test of our understanding of molecular recognition and an attractive approach for creating novel tools for cell and molecular research. Considerable attention has been placed on redesigning the affinity and specificity of naturally occurring interactions. Several studies have shown that reducing the desolvation costs for binding while preserving shape complimentarity and hydrogen bonding is an effective strategy for improving binding affinities. In favorable cases specificity has been designed by focusing only on interactions with the target protein, while in cases with closely related off-target proteins, it has been necessary to explicitly disfavor unwanted binding partners. The rational design of protein-protein interactions from scratch is still an unsolved problem, but recent developments in flexible backbone design and energy functions hold promise for the future.