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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.

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.

Recombinant T cell receptors (TCRs) can be used to redirect naïve T cells to eliminate virally infected or cancerous cells; however, they are plagued by low stability and uneven expression. Here, we use molecular modeling to identify mutations in the TCR constant domains (Cα/Cβ) that increase the unfolding temperature of Cα/Cβ by 20 °C, improve the expression of four separate α/β TCRs by 3- to 10-fold, and improve the assembly and stability of TCRs with poor intrinsic stability. The stabilizing mutations rescue the expression of TCRs destabilized through variable domain mutation. The improved stability and folding of the TCRs reduces glycosylation, perhaps through conformational stabilization that restricts access to N-linked glycosylation enzymes. The Cα/Cβ mutations enables antibody-like expression and assembly of well-behaved bispecific molecules that combine an anti-CD3 antibody with the stabilized TCR. These TCR/CD3 bispecifics can redirect T cells to kill tumor cells with target HLA/peptide on their surfaces in vitro., Recombinant T-cells receptors can redirect naïve T cells but often have low or uneven expression. Here, the authors model mutations in TCR constant domains to increase T cell receptor expression, assembly, and stability and generate bispecific molecules.

Optogenetic techniques use light-responsive proteins to study dynamic processes in living cells and organisms. These techniques typically rely on repurposed naturally occurring light-sensitive proteins to control sub-cellular localization and activity. We previously engineered two optogenetic systems, the Light Activated Nuclear Shuttle (LANS) and the Light-Inducible Nuclear eXporter (LINX), by embedding nuclear import or export sequence motifs into the C-terminal helix of the light-responsive LOV2 domain of Avena sativa phototropin 1, thus enabling light-dependent trafficking of a target protein into and out of the nucleus. While LANS and LINX are effective tools, we posited that mutations within the LOV2 hinge-loop, which connects the core PAS domain and the C-terminal helix, would further improve the functionality of these switches. Here, we identify hinge-loop mutations that favourably shift the dynamic range (the ratio of the on- to off-target subcellular accumulation) of the LANS and LINX photoswitches. We demonstrate the utility of these new optogenetic tools to control gene transcription and epigenetic modifications, thereby expanding the optogenetic ‘tool kit’ for the research community.

Light-sensitive proteins can be used to perturb signaling networks in living cells and animals with high spatiotemporal resolution. We recently engineered a protein heterodimer that dissociates when irradiated with blue light and demonstrated that by fusing each half of the dimer to termini of a protein that it is possible to selectively block binding surfaces on the protein when in the dark. Upon activation with light, the dimer dissociates and exposes the binding surface, allowing the protein to bind its partner. Critical to the success of this system, called Z-lock, is that the linkers connecting the dimer components to the termini are engineered so that the dimer forms over the appropriate binding surface. Here, we develop and test a protocol in the Rosetta molecular modeling program for designing linkers for Z-lock. We show that the protocol can predict the most effective linker sets for three different light-sensitive switches, including a newly designed switch that binds the Rho-family GTPase Cdc42 upon stimulation with blue light. This protocol represents a generalized computational approach to placing a wide variety of proteins under optogenetic control with Z-lock.

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.

Building new proteins from the old Proteins are the workhorses of biology. Designing new, stable proteins with functions desirable in biotechnology or biomedicine remains challenging. Jacobs et al. developed a computational method called SEWING that designs proteins using pieces of existing structures (see the Perspective by Netzer and Fleishman). The new proteins can contain structural features such as pockets or grooves that are required for function. The solved structures of two designed proteins agreed well with the design models. The method allows rapid design of a diverse set of structures that will facilitate functional design. Science , this issue p. 687 ; see also p. 657

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 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second.

A myriad of innovative bispecific antibody (BsAb) platforms have been reported. Most require significant protein engineering to be viable from a development and manufacturing perspective. Single-chain variable fragments (scFvs) and diabodies that consist only of antibody variable domains have been used as building blocks for making BsAbs for decades. The drawback with Fv-only moieties is that they lack the native-like interactions with CH1/CL domains that make antibody Fab regions stable and soluble. Here, we utilize a redesigned Fab interface to explore 2 novel Fab-based BsAbs platforms. The redesigned Fab interface designs limit heavy and light chain mixing when 2 Fabs are co-expressed simultaneously, thus allowing the use of 2 different Fabs within a BsAb construct without the requirement of one or more scFvs. We describe the stability and activity of a HER2×HER2 IgG-Fab BsAb, and compare its biophysical and activity properties with those of an IgG-scFv that utilizes the variable domains of the same parental antibodies. We also generated an EGFR × CD3 tandem Fab protein with a similar format to a tandem scFv (otherwise known as a bispecific T cell engager or BiTE). We show that the Fab-based BsAbs have superior biophysical properties compared to the scFv-based BsAbs. Additionally, the Fab-based BsAbs do not simply recapitulate the activity of their scFv counterparts, but are shown to possess unique biological activity.

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.

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.

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.

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.

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.

Although quantities derived from solvent accessible surface areas (SASA) are useful in many applications in protein design and structural biology, the computational cost of accurate SASA calculation makes SASA-based scores difficult to integrate into commonly used protein design methodologies. We demonstrate a method for maintaining accurate SASA during a Monte Carlo search of sequence and rotamer space for a fixed protein backbone. We extend the fast Le Grand and Merz algorithm (Le Grand and Merz, J Comput Chem, 14, 349), which discretizes the solvent accessible surface for each atom by placing dots on a sphere and combines Boolean masks to determine which dots are exposed. By replacing semigroup operations with group operations (from Boolean logic to counting dot coverage) we support SASA updates. Our algorithm takes time proportional to the number of atoms affected by rotamer substitution, rather than the number of atoms in the protein. For design simulations with a one hundred residue protein our approach is approximately 145 times faster than performing a Le Grand and Merz SASA calculation from scratch following each rotamer substitution. To demonstrate practical effectiveness, we optimize a SASA-based measure of protein packing in the complete redesign of a large set of proteins and protein-protein interfaces.

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.

In this section we have assembled a set of reviews that focus on the design of proteins and peptides with new molecular recognition capabilities. These include proteins that promote crystallization of target proteins, peptides useful for creating nanoelectronic circuits, peptide therapeutics, and switchable enzymes that respond to novel molecular inputs. Allosteric modulation of enzyme activity is typically rapid and reversible and is used to create positive and negative feedback loops in cellular signaling networks. Marc Ostermeier reviews progress in the engineering of switchable enzymes that respond to new signaling inputs. One common strategy is to fuse a catalytic domain with a binding domain that changes conformation when bound to a target ligand. The conformational change can be used to disrupt or assemble the active site as well as relieve steric inhibition of activity. Circular permutation of the host protein allows for a variety of fusion sites, for which the best sites can be identified computationally or with high-throughput screening. There is considerable interest in the design of new switches because they can be used to probe interaction dependencies and kinetics in signaling cascades. Shohei Koide describes recent progress in engineering crystallization chaperones. These are proteins that bind to specified target molecules and promote crystal formation by reducing conformational heterogeneity of the target and providing extra surface area for crystal contact formation. They can also increase or decrease the solubility of the target protein as needed. Fragments of monoclonal antibodies were among the first proteins used as crystallization chaperones and have been used to help solve structures of several important membrane proteins. However, monoclonal antibodies are slow to create and their production at a milligram scale is expensive. Koide describes several newer strategies that do not require animal immunization, but rather use molecular display technologies to identify proteins that bind tightly to the crystallization target. One advantage of this approach is that it can be used with a variety of protein scaffolds, including single chain antibodies, ankyrin repeat proteins, and fibronectin domains. This approach has been used to crystallize the full-length form of the potassium channel KcsA as well as wild-type Polo-like kinase 1. One important drawback of the chaperone approach is that it requires the production of a new chaperone for each target, for this reason, this technology will in general be reserved for high impact targets. Protein design tests our understanding of protein structure and stability. This is particularly true of computer-based studies that use physical models of protein energetics to predict amino acid sequences that will form predetermined structures, complexes or binding sites. John Karanicolas and Brian Kuhlman review recent progress in computational design of protein–protein interactions. They focus on strategies developed for enhancing the affinity of naturally occurring interactions and redesigning protein binding specificities. Particularly exciting is progress in the use of explicit negative design to create sequences that bind to specific targets within large protein families. There is considerable interest in designing proteins that adopt specific conformations when embedded in a membrane. Critical to such efforts is a good understanding of the factors that determine the forces and sequence features that dictate the insertion of transmembrane helices into membranes. Erwin London and Khurshida Shahidullah review studies that probe the relationship between sequence and helix topography in membranes. These include the effects of overall hydrophobicity, helix length, polar residue placement, and the role of flanker sequences. They demonstrate that there is a remarkable similarity between the conclusions from experiments involving the translocon-mediated insertion of model peptides and biophysical studies of fully synthetic peptides in model membranes. These findings suggest that the interaction of potential TM segments with the lipid bilayer during their residence in the translocon, or possibly that the environment experienced by a helix in the pore of the translocon is similar to that of a phospholipid bilayer. Irrespective of the precise mechanism, this paper provides a lucid overview of the features that must be considered in designing and predicting transmembrane helices. Fred Naider and Jacob Anglister describe how structural biology studies have directed the design of peptides that bind to the HIV-1 envelope protein gp41 and inhibit fusion of the virus to target cells. One of these peptides is currently used in the clinic in cases where patients have developed resistance to more standard cocktails of protease and transcriptase inhibitors. This paper provides a particularly interesting analysis of the role of structural, thermodynamic, and kinetic studies in the design and analysis of inhibitors of gp41, and also in devising strategies to combat the growing problem of resistance to this class of pharmaceutical agents. In addition to being useful as regulators of biological systems, peptides can be engineered to form novel materials. Robert Fairman and Brian Pepe-Mooney examine recent progress toward creating nanocircuits based on peptides. They describe new strategies for depositing peptides on surfaces and methods for attaching cofactors that can be used to generate new electronic properties.

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

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

Noncanonical amino acids (NCAAs) can be used in a variety of protein design contexts. For example, they can be used in place of the canonical amino acids (CAAs) to improve the biophysical properties of peptides that target protein interfaces. We describe the incorporation of 114 NCAAs into the protein-modeling suite Rosetta. We describe our methods for building backbone dependent rotamer libraries and the parameterization and construction of a scoring function that can be used to score NCAA containing peptides and proteins. We validate these additions to Rosetta and our NCAA-rotamer libraries by showing that we can improve the binding of a calpastatin derived peptides to calpain-1 by substituting NCAAs for native amino acids using Rosetta. Rosetta (executables and source), auxiliary scripts and code, and documentation can be found at (http://www.rosettacommons.org/).

This article provides information to support the database article titled “UbSRD: The Ubiquitin Structural Relational Database” (Harrison et al., 2015) [1] . The ubiquitin-like homology fold (UBL) represents a large family that encompasses both post-translational modifications, like ubiquitin (UBQ) and SUMO, and functional domains on many biologically important proteins like Parkin, UHRF1 (ubiquitin-like with PDB and RING finger domains-1), and Usp7 (ubiquitin-specific protease-7) (Zhang et al., 2015; Rothbart et al., 2013; Burroughs et al., 2012; Wauer et al., 2015) [2], [3], [4], [5]. The UBL domain can participate in several unique protein–protein interactions (PPI) since protein adducts can be attached to and removed from amino groups of lysine side chains and the N-terminus of proteins. Given the biological significance of UBL domains, many have been characterized with high-resolution techniques, and for UBQ and SUMO, many protein complexes have been characterized. We identified all the UBL domains in the PDB and created a relational database called UbSRD (Ubiquitin Structural Relational Database) by using structural analysis tools in the Rosetta (Leaver et al., 2013; O’Meara et al., 2015; Leaver-fay et al., 2011) [1], [6], [7], [8]. Querying UbSRD permitted us to report many quantitative properties of UBQ and SUMO recognition at different types interfaces (noncovalent: NC, conjugated: CJ, and deubiquitanse: DB). In this data article, we report the average number of non-UBL neighbors, secondary structure of interacting motifs, and the type of inter-molecular hydrogen bonds for each residue of UBQ and SUMO. Additionally, we used PROMALS3D to generate a multiple sequence alignment used to construct a phylogram for the entire set of UBLs (Pei and Grishin, 2014) [9]. The data described here will be generally useful to scientists studying the molecular basis for recognition of UBQ or SUMO.

The de novo design of globular beta sheet proteins remains largely an unsolved problem. It is unclear whether most designs are failing because the designed sequences do not have favorable energies in the target conformations or whether more emphasis should be placed on negative design, that is, explicitly identifying sequences that have poor energies when adopting undesired conformations. We tested whether we could redesign the sequence of a naturally occurring beta sheet protein, tenascin, with a design algorithm that does not include explicit negative design. Denaturation experiments indicate that the designs are significantly more stable than the wild-type protein and the crystal structure of one design closely matches the design model. These results suggest that extensive negative design is not required to create well-folded beta sandwich proteins. However, it is important to note that negative design elements may be encoded in the conformation of the protein backbone which was preserved from the wild-type protein.

Larger rotamer libraries, which provide a fine grained discretization of side chain conformation space by sampling near the canonical rotamers, allow protein designers to find better conformations, but slow down the algorithms that search for them. We present a dynamic programming solution to the side chain placement problem which treats rotamers at high or low resolution only as necessary. Dynamic programming is an exact technique; we turn it into an approximation, but can still analyze the error that can be introduced. We have used our algorithm to redesign the surface residues of ubiquitin's beta sheet.

Structure-based design efforts on antibodies are frequently hamstrung by the general difficulty of crystallizing antibody molecules. Computational approaches are getting more success and playing a very important role in protein structure prediction and design. A combined platform with both computational predication and experimental verification would have a transformative research capability on antibody engineering. We have been developing and integrating RosettaAntibody (homology modeling and H3 loop modeling), RosettaDock (SnugDock and EnsembleDock) and RosettaDesign (non-canonical amino acids design) into a systematic computational pipeline. Using the targets of M18/Anthrax complex, which has solved crystal structure, and anti-MS2/MS2 complex, whose antibody structure is not available, the new pipeline is capable of building homology models for antibody from its sequence, and predicting the docked antibody-antigen structures. The correct antigen epitope can be identified by iteratively refining the predicted candidates with experimental verifications such as interface alanine scanning. This is followed by computational CDR designs utilizing non-canonical amino acids, which can form covalent bonds with epitope residues. Along with experimental confirmations, the incorporation of the systematical computational method was proved to significantly facilitate the epitope identification and non-canonical amino acid designs. These efforts eventually substantially increased the antibody-antigen binding affinity of the two targets.