Computational design of high-affinity epitope scaffolds by backbone grafting of a linear epitope

A two-step mechanism for the binding of the HIV-1 MPER epitope by the 10E8 antibody onto biosensor-supported lipid bilayers

HIV-1 antibodies targeting the carboxy-terminal area of the membrane-proximal external region (ctMPER) are close to exerting viral pan-neutralization. Here, we reconstituted the ctMPER epitope as the N-terminal extremity of the Env glycoprotein transmembrane domain helix and immobilized it onto biosensor-supported lipid bilayers. We assessed the binding mechanism of anti-MPER antibody 10E8 through Surface Plasmon Resonance, and found, through equilibrium and kinetic binding analyses as a function of bilayer thickness, peptide length, and paratope mutations, that 10E8 engages first with the epitope peptide (encounter), limited by ctMPER helix accessibility at the membrane surface, and then inserts into the lipid bilayer assisted by favorable Fab-membrane interactions (docking). This mechanistic information may help in devising new strategies to develop more efficient MPER-targeting vaccines.

Heterologous Sarbecovirus Receptor Binding Domains as Scaffolds for SARS-CoV-2 Receptor Binding Motif Presentation

Structure-guided rational immunogen design can generate optimized immunogens that elicit a desired humoral response. Design strategies often center on targeting conserved sites on viral glycoproteins that will ultimately confer potent neutralization. For SARS-CoV-2 (SARS-2), the surface-exposed spike glycoprotein includes a broadly conserved portion, the receptor binding motif (RBM), that is required to engage the host cellular receptor, ACE2. Expanding humoral responses to this site may result in a more potent neutralizing antibody response against diverse sarbecoviruses. Here, we used a "resurfacing" approach and iterative design cycles to graft the SARS-2 RBM onto heterologous sarbecovirus scaffolds. The scaffolds were selected to vary the antigenic distance relative to SARS-2 to potentially focus responses to RBM. Multimerized versions of these immunogens elicited broad neutralization against sarbecoviruses in the context of preexisting SARS-2 immunity. These validated engineering approaches can help inform future immunogen design efforts for sarbecoviruses and are generally applicable to other viruses.

Engineered immunogens to elicit antibodies against conserved coronavirus epitopes

Immune responses to SARS-CoV-2 primarily target the receptor binding domain of the spike protein, which continually mutates to escape acquired immunity. Other regions in the spike S2 subunit, such as the stem helix and the segment encompassing residues 815-823 adjacent to the fusion peptide, are highly conserved across sarbecoviruses and are recognized by broadly reactive antibodies, providing hope that vaccines targeting these epitopes could offer protection against both current and emergent viruses. Here we employ computational modeling to design scaffolded immunogens that display the spike 815-823 peptide and the stem helix epitopes without the distracting and immunodominant receptor binding domain. These engineered proteins bind with high affinity and specificity to the mature and germline versions of previously identified broadly protective human antibodies. Epitope scaffolds interact with both sera and isolated monoclonal antibodies with broadly reactivity from individuals with pre-existing SARS-CoV-2 immunity. When used as immunogens, epitope scaffolds elicit sera with broad betacoronavirus reactivity and protect as "boosts" against live virus challenge in mice, illustrating their potential as components of a future pancoronavirus vaccine.

Engineered Immunogens to Elicit Antibodies Against Conserved Coronavirus Epitopes

Immune responses to SARS-CoV-2 primarily target the receptor binding domain of the spike protein, which continually mutates to escape acquired immunity. Other regions in the spike S2 subunit, such as the stem helix and the segment encompassing residues 815-823 adjacent to the fusion peptide, are highly conserved across sarbecoviruses and are recognized by broadly reactive antibodies, providing hope that vaccines targeting these epitopes could offer protection against both current and emergent viruses. Here we employed computational modeling to design scaffolded immunogens that display the spike 815-823 peptide and the stem helix epitopes without the distracting and immunodominant RBD. These engineered proteins bound with high affinity and specificity to the mature and germline versions of previously identified broadly protective human antibodies. Epitope scaffolds interacted with both sera and isolated monoclonal antibodies with broadly reactivity from individuals with pre-existing SARS-CoV-2 immunity. When used as immunogens, epitope scaffolds elicited sera with broad betacoronavirus reactivity and protected as "boosts" against live virus challenge in mice, illustrating their potential as components of a future pancoronavirus vaccine.

Heterologous sarbecovirus receptor binding domains as scaffolds for SARS-CoV-2 receptor binding motif presentation

Structure-guided rational immunogen design can generate optimized immunogens that elicit a desired humoral response. Design strategies often center upon targeting conserved sites on viral glycoproteins that will ultimately confer potent neutralization. For SARS-CoV-2 (SARS-2), the surface-exposed spike glycoprotein includes a broadly conserved portion, the receptor binding motif (RBM), that is required to engage the host cellular receptor, ACE2. Expanding humoral responses to this site may result in a more potently neutralizing antibody response against diverse sarbecoviruses. Here, we used a "resurfacing" approach and iterative design cycles to graft the SARS-2 RBM onto heterologous sarbecovirus scaffolds. The scaffolds were selected to vary the antigenic distance relative to SARS-2 to potentially focus responses to RBM. Multimerized versions of these immunogens elicited broad neutralization against sarbecoviruses in the context of preexisting SARS-2 immunity. These validated engineering approaches can help inform future immunogen design efforts for sarbecoviruses and are generally applicable to other viruses.

Targeting Ras with protein engineering

Ras proteins are small GTPases that regulate cell growth and division. Mutations in Ras genes are associated with many types of cancer, making them attractive targets for cancer therapy. Despite extensive efforts, targeting Ras proteins with small molecules has been extremely challenging due to Ras's mostly flat surface and lack of small molecule-binding cavities. These challenges were recently overcome by the development of the first covalent small-molecule anti-Ras drug, sotorasib, highlighting the efficacy of Ras inhibition as a therapeutic strategy. However, this drug exclusively inhibits the Ras G12C mutant, which is not a prevalent mutation in most cancer types. Unlike the G12C variant, other Ras oncogenic mutants lack reactive cysteines, rendering them unsuitable for targeting via the same strategy. Protein engineering has emerged as a promising method to target Ras, as engineered proteins have the ability to recognize various surfaces with high affinity and specificity. Over the past few years, scientists have engineered antibodies, natural Ras effectors, and novel binding domains to bind to Ras and counteract its carcinogenic activities via a variety of strategies. These include inhibiting Ras-effector interactions, disrupting Ras dimerization, interrupting Ras nucleotide exchange, stimulating Ras interaction with tumor suppressor genes, and promoting Ras degradation. In parallel, significant advancements have been made in intracellular protein delivery, enabling the delivery of the engineered anti-Ras agents into the cellular cytoplasm. These advances offer a promising path for targeting Ras proteins and other challenging drug targets, opening up new opportunities for drug discovery and development.

Adaptation-proof SARS-CoV-2 vaccine design

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surface spike glycoprotein - a major antibody target - is critical for virus entry via engagement of human angiotensin-converting enzyme 2 (ACE2) receptor. Despite successes with existing vaccines and therapies that primarily target the receptor binding domain (RBD) of the spike protein, the susceptibility of RBD to mutations provides escape routes for the SARS-CoV-2 from neutralizing antibodies. On the other hand, structural conservation in the spike protein can be targeted to reduce escape mutations and achieve broad protection. Here, we designed candidate stable immunogens that mimic surface features of selected conserved regions of spike protein through 'epitope grafting,' in which we present the target epitope topology on diverse heterologous scaffolds that can structurally accommodate the spike epitopes. Structural characterization of the epitope-scaffolds showed stark agreement with our computational models and target epitopes. The sera from mice immunized with engineered designs display epitope-scaffolds and spike binding activity. We also demonstrated the utility of the designed epitope-scaffolds in diagnostic applications. Taken all together, our study provides important methodology for targeting the conserved, non-RBD structural motifs of spike protein for SARS-CoV-2 epitope vaccine design and demonstrates the potential utility of 'epitope grafting' in rational vaccine design.

Computational design of vaccine immunogens

Computational protein engineering has enabled the rational design of customized proteins, which has propelled both sequence-based and structure-based immunogen engineering and delivery. By discerning antigenic determinants of viral pathogens, computational methods have been implemented to successfully engineer representative viral strains able to elicit broadly neutralizing responses or present antigenic sites of viruses for focused immune responses. Combined with improvements in customizable nanoparticle design, immunogens are multivalently displayed to enhance immune responses. These rationally designed immunogens offer unique and powerful approaches to engineer vaccines for pathogens, which have eluded traditional approaches.

Biotinylation Eliminates the Intermediate State of Top7 Designed with an HIV-1 Epitope

Broadly neutralizing antibodies against HIV-1 are rare with the 2F5 antibody being one of the most protective. Insertion of an antibody epitope into a stable and small protein scaffold overcomes many of the obstacles found to produce antibodies. However, the design leads to grafting of epitopes that may cause protein aggregation. Here, I investigated the 2F5 epitope grafted into the Top7 as the scaffold in which the resulting immunoreactive protein precipitates along the storage time, as opposed to its completely soluble biotinylated version. Molecular dynamics showed that biotinylation eliminates the intermediate state of the scaffold-epitope Top7-2F5 by switching a noncooperative to a cooperative folding. The aggregation propensity of the Top7-designed proteins is examined in light of thermodynamic cooperativity and kinetic traps along the decreasing depth of the intermediate ensemble in the free energy landscape. This protocol may predict stable and soluble scaffold-epitopes with the purpose of composing novel therapeutic and diagnostic platforms.

Antibodies to combat viral infections: development strategies and progress

Monoclonal antibodies (mAbs) are appealing as potential therapeutics and prophylactics for viral infections owing to characteristics such as their high specificity and their ability to enhance immune responses. Furthermore, antibody engineering can be used to strengthen effector function and prolong mAb half-life, and advances in structural biology have enabled the selection and optimization of potent neutralizing mAbs through identification of vulnerable regions in viral proteins, which can also be relevant for vaccine design. The COVID-19 pandemic has stimulated extensive efforts to develop neutralizing mAbs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with several mAbs now having received authorization for emergency use, providing not just an important component of strategies to combat COVID-19 but also a boost to efforts to harness mAbs in therapeutic and preventive settings for other infectious diseases. Here, we describe advances in antibody discovery and engineering that have led to the development of mAbs for use against infections caused by viruses including SARS-CoV-2, respiratory syncytial virus (RSV), Ebola virus (EBOV), human cytomegalovirus (HCMV) and influenza. We also discuss the rationale for moving from empirical to structure-guided strategies in vaccine development, based on identifying optimal candidate antigens and vulnerable regions within them that can be targeted by antibodies to result in a strong protective immune response.

Adaptation-proof SARS-CoV-2 vaccine design

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surface spike glycoprotein - a major antibody target - is critical for virus entry via engagement of human angiotensin-converting enzyme 2 (ACE2) receptor. Despite successes with existing vaccines and therapies that primarily target the receptor binding domain (RBD) of the spike protein, the susceptibility of RBD to mutations provides escape routes for the SARS-CoV-2 from neutralizing antibodies. On the other hand, structural conservation in the spike protein can be targeted to reduce escape mutations and achieve broad protection. Here, we designed candidate stable immunogens that mimic surface features of selected conserved regions of spike protein through 'epitope grafting,' in which we present the target epitope topology on diverse heterologous scaffolds that can structurally accommodate the spike epitopes. Structural characterization of the epitope-scaffolds showed stark agreement with our computational models and target epitopes. The sera from mice immunized with engineered designs display epitope-scaffolds and spike binding activity. We also demonstrated the utility of the designed epitope-scaffolds in diagnostic applications. Taken all together, our study provides important methodology for targeting the conserved, non-RBD structural motifs of spike protein for SARS-CoV-2 epitope vaccine design and demonstrates the potential utility of 'epitope grafting' in rational vaccine design.

Toward rational vaccine engineering

Technological revolutions in several fields have pushed the boundaries of vaccine design and provided new avenues for vaccine development. Next-generation vaccine platforms have shown promise in targeting challenging antigens, for which traditional approaches have been ineffective. With advances in protein engineering, structural biology, computational biology and immunology, the structural vaccinology approach, which uses protein structure information to develop immunogens, holds promise for future vaccine design. In this review, we highlight various vaccine development strategies, along with their advantages and limitations. We discuss the rational vaccine design approach, which focuses on structure-based vaccine design. Finally, we discuss antigen engineering using the epitope-scaffold approach, gaps in structural vaccinology, and remaining challenges in vaccine design.

Protein Assembly by Design

Proteins are nature's primary building blocks for the construction of sophisticated molecular machines and dynamic materials, ranging from protein complexes such as photosystem II and nitrogenase that drive biogeochemical cycles to cytoskeletal assemblies and muscle fibers for motion. Such natural systems have inspired extensive efforts in the rational design of artificial protein assemblies in the last two decades. As molecular building blocks, proteins are highly complex, in terms of both their three-dimensional structures and chemical compositions. To enable control over the self-assembly of such complex molecules, scientists have devised many creative strategies by combining tools and principles of experimental and computational biophysics, supramolecular chemistry, inorganic chemistry, materials science, and polymer chemistry, among others. Owing to these innovative strategies, what started as a purely structure-building exercise two decades ago has, in short order, led to artificial protein assemblies with unprecedented structures and functions and protein-based materials with unusual properties. Our goal in this review is to give an overview of this exciting and highly interdisciplinary area of research, first outlining the design strategies and tools that have been devised for controlling protein self-assembly, then describing the diverse structures of artificial protein assemblies, and finally highlighting the emergent properties and functions of these assemblies.

Computationally grafting an IgE epitope onto a scaffold: Implications for a pan anti-allergy vaccine design

Allergy is becoming an intensifying disease among the world population, particularly in the developed world. Once allergy develops, sufferers are permanently trapped in a hyper-immune response that makes them sensitive to innocuous substances. The immune pathway concerned with developing allergy is the Th2 immune pathway where the IgE antibody binds to its Fc ∊ RI receptor on Mast and Basophil cells. This paper discusses a protocol that could disrupt the binding between the antibody and its receptor for a potential permanent treatment. Ten proteins were computationally designed to display a human IgE motif very close in proximity to the IgE antibody's Fc ∊ RI receptor's binding site in an effort for these proteins to be used as a vaccine against our own IgE antibody. The motif of interest was the FG loop motif and it was excised and grafted onto a Staphylococcus aureus protein (PDB ID 1YN3), then the motif + scaffold structure had its sequence re-designed around the motif to find an amino acid sequence that would fold to the designed structure correctly. These ten computationally designed proteins showed successful folding when simulated using Rosetta's AbinitioRelax folding simulation and the IgE epitope was clearly displayed in its native three-dimensional structure in all of them. These designed proteins have the potential to be used as a pan anti-allergy vaccine. This work employedin silicobased methods for designing the proteins and did not include any experimental verifications.

Guiding the Immune Response to a Conserved Epitope in MSP2, an Intrinsically Disordered Malaria Vaccine Candidate

The malaria vaccine candidate merozoite surface protein 2 (MSP2) has shown promise in clinical trials and is in part responsible for a reduction in parasite densities. However, strain-specific reductions in parasitaemia suggested that polymorphic regions of MSP2 are immuno-dominant. One strategy to bypass the hurdle of strain-specificity is to bias the immune response towards the conserved regions. Two mouse monoclonal antibodies, 4D11 and 9H4, recognise the conserved C-terminal region of MSP2. Although they bind overlapping epitopes, 4D11 reacts more strongly with native MSP2, suggesting that its epitope is more accessible on the parasite surface. In this study, a structure-based vaccine design approach was applied to the intrinsically disordered antigen, MSP2, using a crystal structure of 4D11 Fv in complex with its minimal binding epitope. Molecular dynamics simulations and surface plasmon resonance informed the design of a series of constrained peptides that mimicked the 4D11-bound epitope structure. These peptides were conjugated to keyhole limpet hemocyanin and used to immunise mice, with high to moderate antibody titres being generated in all groups. The specificities of antibody responses revealed that a single point mutation can focus the antibody response towards a more favourable epitope. This structure-based approach to peptide vaccine design may be useful not only for MSP2-based malaria vaccines, but also for other intrinsically disordered antigens.

Targeting Viral Surface Proteins through Structure-Based Design

The emergence of novel viral infections of zoonotic origin and mutations of existing human pathogenic viruses represent a serious concern for public health. It warrants the establishment of better interventions and protective therapies to combat the virus and prevent its spread. Surface glycoproteins catalyzing the fusion of viral particles and host cells have proven to be an excellent target for antivirals as well as vaccines. This review focuses on recent advances for computational structure-based design of antivirals and vaccines targeting viral fusion machinery to control seasonal and emerging respiratory viruses.

The Status and Prospects of Epstein-Barr Virus Prophylactic Vaccine Development

Epstein–Barr virus (EBV) is a human herpesvirus that is common among the global population, causing an enormous disease burden. EBV can directly cause infectious mononucleosis and is also associated with various malignancies and autoimmune diseases. In order to prevent primary infection and subsequent chronic disease, efforts have been made to develop a prophylactic vaccine against EBV in recent years, but there is still no vaccine in clinical use. The outbreak of the COVID-19 pandemic and the global cooperation in vaccine development against SARS-CoV-2 provide insights for next-generation antiviral vaccine design and opportunities for developing an effective prophylactic EBV vaccine. With improvements in antigen selection, vaccine platforms, formulation and evaluation systems, novel vaccines against EBV are expected to elicit dual protection against infection of both B lymphocytes and epithelial cells. This would provide sustainable immunity against EBV-associated malignancies, finally enabling the control of worldwide EBV infection and management of EBV-associated diseases.

A Strategy Based on Loop Analysis to Develop Peptide Epitopes: Application to SARS-CoV-2 Spike Protein

Many current strategies for inducing an immune response rely on the production of an antigenic protein. Such methods can be problematic if the folding of the antigenic protein is incorrect. To avoid this problem, we propose a method based on grafting specific regions of the chosen antigenic protein onto biocompatible polymeric matrices, so that they can mimic portions of the antigenic protein. These regions are selected following the criterion according to which they are not folded, are exposed to the solvent and are not already present in the human body, so that they are not recognized by the immune system as self. Regions are selected using the primary sequence of the protein and, where possible, its tertiary structure. The application of this strategy to the Spike protein of SARS-CoV-2 is presented.

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.

On the irrationality of rational design of an HIV vaccine in light of protein intrinsic disorder

The lack of progress in finding an efficient vaccine for a human immunodeficiency virus (HIV) is daunting. In fact, this search has spanned nearly four decades without much success. There are several objective reasons for such a failure, which include the highly glycosylated nature of HIV-1, the presence of neotopes, and high mutation rates. This article argues that the presence of highly flexible and intrinsically disordered regions in both human anti-HIV-1 antibodies and the major HIV-1immunogen, its surface glycoprotein gp120, represent one of the major causes for the lack of success in utilization of structure-based reverse vaccinology.

Computational design and experimental optimization of protein binders with prospects for biomedical applications

Protein-based binders have become increasingly more attractive candidates for drug and imaging agent development. Such binders could be evolved from a number of different scaffolds, including antibodies, natural protein effectors and unrelated small protein domains of different geometries. While both computational and experimental approaches could be utilized for protein binder engineering, in this review we focus on various computational approaches for protein binder design and demonstrate how experimental selection could be applied to subsequently optimize computationally-designed molecules. Recent studies report a number of designed protein binders with pM affinities and high specificities for their targets. These binders usually characterized with high stability, solubility, and low production cost. Such attractive molecules are bound to become more common in various biotechnological and biomedical applications in the near future.

Exploring the binding of rationally engineered tandem-repeat proteins to E3 ubiquitin ligase Keap1

The process of displaying functional peptides by 'grafting' them onto loops of a stable protein scaffold can be used to impart binding affinity for a target, but it can be difficult to predict the affinity of the grafted peptide and the effect of grafting on scaffold stability. In this study, we show that a series of peptides that bind to the E3 ubiquitin ligase Keap1 can be grafted into the inter-repeat loop of a consensus-designed tetratricopeptide repeat (CTPR) protein resulting in proteins with high stability. We found that these CTPR-grafted peptides had similar affinities to their free peptide counterparts and achieved a low nanomolar range. This result is likely due to a good structural match between the inter-repeat loop of the CTPR and the Keap1-binding peptide. The grafting process led to the discovery of a new Keap1-binding peptide, Ac-LDPETGELL-NH2, with low nanomolar affinity for Keap1, highlighting the potential of the repeat-protein class for application in peptide display.

Structure-Guided Design of a Synthetic Mimic of an Endothelial Protein C Receptor-Binding PfEMP1 Protein

Vaccines train our immune systems to generate antibodies which recognize pathogens. Some of these antibodies are highly protective, preventing infection, while others are ineffective.

Structure-guided vaccine design provides a route to elicit a focused immune response against the most functionally important regions of a pathogen surface. This can be achieved by identifying epitopes for neutralizing antibodies through structural methods and recapitulating these epitopes by grafting their core structural features onto smaller scaffolds. In this study, we conducted a modified version of this protocol. We focused on the PfEMP1 protein family found on the surfaces of erythrocytes infected with Plasmodium falciparum. A subset of PfEMP1 proteins bind to endothelial protein C receptor (EPCR), and their expression correlates with development of the symptoms of severe malaria. Structural studies revealed that PfEMP1 molecules present a helix-kinked-helix motif that forms the core of the EPCR-binding site. Using Rosetta-based design, we successfully grafted this motif onto a three-helical bundle scaffold. We show that this synthetic binder interacts with EPCR with nanomolar affinity and adopts the expected structure. We also assessed its ability to bind to antibodies found in immunized animals and in humans from malaria-endemic regions. Finally, we tested the capacity of the synthetic binder to effectively elicit antibodies that prevent EPCR binding and analyzed the degree of cross-reactivity of these antibodies across a diverse repertoire of EPCR-binding PfEMP1 proteins. Despite our synthetic binder adopting the correct structure, we find that it is not as effective as the CIDRα domain on which it is based for inducing adhesion-inhibitory antibodies. This cautions against the rational design of focused immunogens that contain the core features of a ligand-binding site of a protein family, rather than those of a neutralizing antibody epitope.

IMPORTANCE Vaccines train our immune systems to generate antibodies which recognize pathogens. Some of these antibodies are highly protective, preventing infection, while others are ineffective. Structure-guided rational approaches allow design of synthetic molecules which contain only the regions of a pathogen required to induce production of protective antibodies. On the surfaces of red blood cells infected by the malaria parasite Plasmodium falciparum are parasite molecules called PfEMP1 proteins. PfEMP1 proteins, which bind to human receptor EPCR, are linked to development of severe malaria. We have designed a synthetic protein on which we grafted the EPCR-binding surface of a PfEMP1 protein. We use this molecule to show which fraction of protective antibodies recognize the EPCR-binding surface and test its effectiveness as a vaccine immunogen.

Rosetta-Enabled Structural Prediction of Permissive Loop Insertion Sites in Proteins

While loop motifs frequently play a major role in protein function, our understanding of how to rationally engineer proteins with novel loop domains remains limited. In the absence of rational approaches, the incorporation of loop domains often destabilizes proteins, thereby requiring massive screening and selection to identify sites that can accommodate loop insertion. We developed a computational strategy for rapidly scanning the entire structure of a scaffold protein to determine the impact of loop insertion at all possible amino acid positions. This approach is based on the Rosetta kinematic loop modeling protocol and was demonstrated by identifying sites in lipase that were permissive to insertion of the LAP peptide. Interestingly, the identification of permissive sites was dependent on the contribution of the residues in the near-loop environment on the Rosetta score and did not correlate with conventional structural features (e.g., B-factors). As evidence of this, several insertion sites (e.g., following residues 17, 47-49, and 108), which were predicted and confirmed to be permissive, interrupted helices, while others (e.g., following residues 43, 67, 116, 119, and 121), which are situated in loop regions, were nonpermissive. This approach was further shown to be predictive for β-glucosidase and human phosphatase and tensin homologue (PTEN), and to facilitate the engineering of insertion sites through in silico mutagenesis. By enabling the design of loop-containing protein libraries with high probabilities of soluble expression, this approach has broad implications in many areas of protein engineering, including antibody design, improving enzyme activity, and protein modification.

RamaNet: Computational de novo helical protein backbone design using a long short-term memory generative neural network

The ability to perform de novo protein design will allow researchers to expand the variety of available proteins. By designing synthetic structures computationally, they can utilise more structures than those available in the Protein Data Bank, design structures that are not found in nature, or direct the design of proteins to acquire a specific desired structure. While some researchers attempt to design proteins from first physical and thermodynamic principals, we decided to attempt to test whether it is possible to perform de novo helical protein design of just the backbone statistically using machine learning by building a model that uses a long short-term memory (LSTM) architecture. The LSTM model used only the φ and ψ angles of each residue from an augmented dataset of only helical protein structures. Though the network’s generated backbone structures were not perfect, they were idealised and evaluated post generation where the non-ideal structures were filtered out and the adequate structures kept. The results were successful in developing a logical, rigid, compact, helical protein backbone topology. This paper is a proof of concept that shows it is possible to generate a novel helical backbone topology using an LSTM neural network architecture using only the φ and ψ angles as features. The next step is to attempt to use these backbone topologies and sequence design them to form complete protein structures.

Passive immunotherapies targeting Aβ and tau in Alzheimer's disease

Amyloid-β (Aβ) and tau proteins currently represent the two most promising targets to treat Alzheimer's disease. The most extensively developed method to treat the pathologic forms of these proteins is through the administration of exogenous antibodies, or passive immunotherapy. In this review, we discuss the molecular-level strategies that researchers are using to design an effective therapeutic antibody, given the challenges in treating this disease. These challenges include selectively targeting a protein that has misfolded or is pathological rather than the more abundant, healthy protein, designing strategic constructs for immunizing an animal to raise an antibody that has the appropriate conformational selectivity to achieve this end, and clearing the pathological protein species before prion-like cell-to-cell spread of misfolded protein has irreparably damaged neurons, without invoking damaging inflammatory responses in the brain that naturally arise when the innate immune system is clearing foreign agents. The various solutions to these problems in current clinical trials will be discussed.

A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction

Protein-protein interactions regulate almost all cellular functions and rely on a fine tune of surface amino acids properties involved on both molecular partners. The disruption of a molecular association can be caused even by a single residue mutation, often leading to a pathological modification of a biochemical pathway. Therefore the evaluation of the effects of amino acid substitutions on binding, and the ad hoc design of protein-protein interfaces, is one of the biggest challenges in computational biology. Here, we present a novel strategy for computational mutation and optimization of protein-protein interfaces. Modeling the interaction surface properties using the Zernike polynomials, we describe the shape and electrostatics of binding sites with an ordered set of descriptors, making possible the evaluation of complementarity between interacting surfaces. With a Monte Carlo approach, we obtain protein mutants with controlled molecular complementarities. Applying this strategy to the relevant case of the interaction between Ferritin and Transferrin Receptor, we obtain a set of Ferritin mutants with increased or decreased complementarity. The extensive molecular dynamics validation of the method results confirms its efficacy, showing that this strategy represents a very promising approach in designing correct molecular interfaces.

DisruPPI: structure-based computational redesign algorithm for protein binding disruption

Motivation

Disruption of protein–protein interactions can mitigate antibody recognition of therapeutic proteins, yield monomeric forms of oligomeric proteins, and elucidate signaling mechanisms, among other applications. While designing affinity-enhancing mutations remains generally quite challenging, both statistically and physically based computational methods can precisely identify affinity-reducing mutations. In order to leverage this ability to design variants of a target protein with disrupted interactions, we developed the DisruPPI protein design method (DISRUpting Protein–Protein Interactions) to optimize combinations of mutations simultaneously for both disruption and stability, so that incorporated disruptive mutations do not inadvertently affect the target protein adversely.

Results

Two existing methods for predicting mutational effects on binding, FoldX and INT5, were demonstrated to be quite precise in selecting disruptive mutations from the SKEMPI and AB-Bind databases of experimentally determined changes in binding free energy. DisruPPI was implemented to use an INT5-based disruption score integrated with an AMBER-based stability assessment and was applied to disrupt protein interactions in a set of different targets representing diverse applications. In retrospective evaluation with three different case studies, comparison of DisruPPI-designed variants to published experimental data showed that DisruPPI was able to identify more diverse interaction-disrupting and stability-preserving variants more efficiently and effectively than previous approaches. In prospective application to an interaction between enhanced green fluorescent protein (EGFP) and a nanobody, DisruPPI was used to design five EGFP variants, all of which were shown to have significantly reduced nanobody binding while maintaining function and thermostability. This demonstrates that DisruPPI may be readily utilized for effective removal of known epitopes of therapeutically relevant proteins.

Availability and implementation

DisruPPI is implemented in the EpiSweep package, freely available under an academic use license.

Supplementary information

Supplementary data are available at Bioinformatics online.

Moving from Empirical to Rational Vaccine Design in the 'Omics' Era

An ideal vaccine provides long lasting protection against a pathogen by eliciting a well-rounded immune response which engages both innate and adaptive immunity. However, we have a limited understanding of how components of innate immunity, antibody and cell-mediated adaptive immunity interact and function together at a systems level. With advances in high-throughput ‘Omics’ methodologies it has become possible to capture global changes in the host, at a cellular and molecular level, that are induced by vaccination and infection. Analysis of these datasets has shown the promise of discovering mechanisms behind vaccine mediated protection, immunological memory, adverse effects as well as development of more efficient antigens and adjuvants. In this review, we will discuss how systems vaccinology takes advantage of new technology platforms and big data analysis, to enable the rational development of better vaccines.

Lessons for general vaccinology research from attempts to develop an HIV vaccine

In the past when large investments have been made in tackling narrow scientific challenges, the enormous expansion in our knowledge in one small area has had a spill-over effect on research and treatment of other diseases. The large investment in HIV vaccine development in recent years has the potential for such an effect on vaccine development for other diseases. HIV vaccine developers have experienced repeated failure using the standard approaches to vaccine development. This has forced them to consider immune responses in greater depth and detail. It has led to a recognition of the importance of epitopic specificity in both antibody and T cell responses. Also, it has led to an understanding of the importance of affinity maturation in antibody responses and the quality of T cell responses in T cell-mediated immunity. It has advanced the development of many novel vaccine vectors and vehicles that are now available for use in other vaccines. Further, it has focused attention on the impact of research funding mechanisms and community engagement on vaccine development. These developments and considerations have implications for vaccinology more generally. Some suggestions are made for investigators working on other "hard-to-develop" vaccines.

Exploring new strategies for grafting binding peptides onto protein loops using a consensus-designed tetratricopeptide repeat scaffold

Peptide display approaches, in which peptide epitopes of known binding activities are grafted onto stable protein scaffolds, have been developed to constrain the peptide in its bioactive conformation and to enhance its stability. However, peptide grafting can be a lengthy process requiring extensive computational modeling and/or optimisation by directed evolution techniques. In this study, we show that ultra-stable consensus-designed tetratricopeptide repeat (CTPR) proteins are amenable to the grafting of peptides that bind the Kelch-like ECH-associated protein 1 (Keap1) onto the loop between adjacent repeats. We explore simple strategies to optimize the grafting process and show that modest improvements in Keap1-binding affinity can be obtained by changing the composition of the linker sequence flanking either side of the binding peptide.

Potent neutralization activity against type O foot-and-mouth disease virus elicited by a conserved type O neutralizing epitope displayed on bovine parvovirus virus-like particles

In this study, ten sites on the N terminus and different surface variable regions (VRs) of the bovine parvovirus (BPV) VP2 capsid protein were selected according to an alignment of its sequence with that of the BPV-1 strain HADEN for insertion of the type O foot-and-mouth disease virus (FMDV) conserved neutralizing epitope 8E8. Ten epitope-chimeric BPV VP2 capsid proteins carrying the 8E8 epitope were expressed in Sf9 cells, and electron micrographs demonstrated that these fusion proteins self-assembled into virus-like particles (VLPs) with properties similar to those of natural BPV virions. Immunofluorescence assay (IFA) and Western blot analysis demonstrated that each of the ten epitope-chimeric VLPs reacted with both anti-BPV serum and anti-type O FMDV mAb 8E8. These results indicated that insertions of the 8E8 epitope at these sites on the BPV VP2 protein did not interfere with the immunoreactivity of VP2 or VLP formation, and that the exogenous epitope 8E8 was correctly expressed in BPV VLPs. In addition, anti-BPV IgG antibodies were induced in mice by intramuscular inoculation with each of the ten chimeric VLPs, indicating that the immunogenicity of the chimeric VLPs was not disrupted. Importantly, potent anti-FMDV viral neutralizing (VN) antibodies, which exhibited the highest titre of 1 : 176, were induced by two chimeric VLPs, rBPV-VLP-8E8(391) and rBPV-VLP-8E8(395), in which the 8E8 epitope was inserted into positions 391/392 and 395/396, respectively, in the VR VIII of BPV VP2. Our results demonstrated that the 391/392 and 395/396 positions in the VR VIII of the BPV VP2 protein can effectively display a foreign epitope, making this an attractive approach for the design of nanoparticle-vectored and epitope-based vaccines.

Rosetta FunFolDes - A general framework for the computational design of functional proteins

The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols and the extensive in vitro optimization often required, highlight the challenge of designing proteins that perform essential biochemical functions, such as binding or catalysis. One of the most simplistic approaches for the design of function is to adopt functional motifs in naturally occurring proteins and transplant them to computationally designed proteins. The structural complexity of the functional motif largely determines how readily one can find host protein structures that are "designable", meaning that are likely to present the functional motif in the desired conformation. One promising route to enhance the "designability" of protein structures is to allow backbone flexibility. Here, we present a computational approach that couples conformational folding with sequence design to embed functional motifs into heterologous proteins-Rosetta Functional Folding and Design (FunFolDes). We performed extensive computational benchmarks, where we observed that the enforcement of functional requirements resulted in designs distant from the global energetic minimum of the protein. An observation consistent with several experimental studies that have revealed function-stability tradeoffs. To test the design capabilities of FunFolDes we transplanted two viral epitopes into distant structural templates including one de novo "functionless" fold, which represent two typical challenges where the designability problem arises. The designed proteins were experimentally characterized showing high binding affinities to monoclonal antibodies, making them valuable candidates for vaccine design endeavors. Overall, we present an accessible strategy to repurpose old protein folds for new functions. This may lead to important improvements on the computational design of proteins, with structurally complex functional sites, that can perform elaborate biochemical functions related to binding and catalysis.

Prediction of Misfolding-Specific Epitopes in SOD1 Using Collective Coordinates

We introduce a global, collective coordinate bias into molecular dynamics simulations that partially unfolds a protein, in order to predict misfolding-specific epitopes based on the regions that locally unfold. Several metrics are used to measure local disorder, including solvent exposed surface area (SASA), native contacts ( Q), and root mean squared fluctuations (RMSF). The method is applied to Cu, Zn superoxide dismutase (SOD1). For this protein, the processes of monomerization, metal loss, and conformational unfolding due to microenvironmental stresses are all separately taken into account. Several misfolding-specific epitopes are predicted, and consensus epitopes are calculated. These predicted epitopes are consistent with the "lower-resolution" peptide sequences used to raise disease-specific antibodies, but the epitopes derived from collective coordinates contain shorter, more refined sequences for the key residues constituting the epitope.

Studies on computational grafting of malarial epitopes in serum albumin

BACKGROUND

Antigens (or their epitopes)-carrier protein combinations are extensively utilized for vaccine development strategies. Chemical conjugation methods are cumbersome with limited conjugation sites. Computational protein modelling methods can evaluate every position of a carrier protein for conjugation via epitope grafting in a reasonable time frame as compared to wet experimental techniques. Graftibility of positions can be estimated by the presence of native atomic contacts in resulting chimeric antigen.

METHODOLOGY

Five epitopes were selected, and computational grafting at each position was performed in three templates of serum albumin. Protein modelling algorithms such as segment matching and satisfaction of spatial restraints were employed for computational grafting. Contact-based protein discriminatory function was used to evaluate the chimeric proteins having native atomic contacts.

RESULTS

On the evaluation of approximately 1 million distinct protein modelling simulations, region around the 450^th position of serum albumin was observed to be suitable for epitope grafting.

CONCLUSION

Computational protein modelling tools may be used to design a chimeric antigen. The approach may overcome the limitations associated with chemical conjugation and furthermore harness the potential of custom gene synthesis/recombinant protein production.

Computational B-cell epitope identification and production of neutralizing murine antibodies against Atroxlysin-I

Epitope identification is essential for developing effective antibodies that can detect and neutralize bioactive proteins. Computational prediction is a valuable and time-saving alternative for experimental identification. Current computational methods for epitope prediction are underused and undervalued due to their high false positive rate. In this work, we targeted common properties of linear B-cell epitopes identified in an individual protein class (metalloendopeptidases) and introduced an alternative method to reduce the false positive rate and increase accuracy, proposing to restrict predictive models to a single specific protein class. For this purpose, curated epitope sequences from metalloendopeptidases were transformed into frame-shifted Kmers (3 to 15 amino acid residues long). These Kmers were decomposed into a matrix of biochemical attributes and used to train a decision tree classifier. The resulting prediction model showed a lower false positive rate and greater area under the curve when compared to state-of-the-art methods. Our predictions were used for synthesizing peptides mimicking the predicted epitopes for immunization of mice. A predicted linear epitope that was previously undetected by an experimental immunoassay was able to induce neutralizing-antibody production in mice. Therefore, we present an improved prediction alternative and show that computationally identified epitopes can go undetected during experimental mapping.

Creation of artificial protein-protein interactions using α-helices as interfaces

Designing novel protein-protein interactions (PPIs) with high affinity is a challenging task. Directed evolution, a combination of randomization of the gene for the protein of interest and selection using a display technique, is one of the most powerful tools for producing a protein binder. However, the selected proteins often bind to the target protein at an undesired surface. More problematically, some selected proteins bind to their targets even though they are unfolded. Current state-of-the-art computational design methods have successfully created novel protein binders. These computational methods have optimized the non-covalent interactions at interfaces and thus produced artificial protein complexes. However, to date there are only a limited number of successful examples of computationally designed de novo PPIs. De novo design of coiled-coil proteins has been extensively performed and, therefore, a large amount of knowledge of the sequence-structure relationship of coiled-coil proteins has been accumulated. Taking advantage of this knowledge, de novo design of inter-helical interactions has been used to produce artificial PPIs. Here, we review recent progress in the in silico design and rational design of de novo PPIs and the use of α-helices as interfaces.

Coiled coil protein origami: from modular design principles towards biotechnological applications

This review illustrates the current state in designing coiled-coil-based proteins with an emphasis on coiled coil protein origami structures and their potential.

In silico methods for design of biological therapeutics

It has been twenty years since the first rationally designed small molecule drug was introduced into the market. Since then, we have progressed from designing small molecules to designing biotherapeutics. This class of therapeutics includes designed proteins, peptides and nucleic acids that could more effectively combat drug resistance and even act in cases where the disease is caused because of a molecular deficiency. Computational methods are crucial in this design exercise and this review discusses the various elements of designing biotherapeutic proteins and peptides. Many of the techniques discussed here, such as the deterministic and stochastic design methods, are generally used in protein design. We have devoted special attention to the design of antibodies and vaccines. In addition to the methods for designing these molecules, we have included a comprehensive list of all biotherapeutics approved for clinical use. Also included is an overview of methods that predict the binding affinity, cell penetration ability, half-life, solubility, immunogenicity and toxicity of the designed therapeutics. Biotherapeutics are only going to grow in clinical importance and are set to herald a new generation of disease management and cure.

Computational design of trimeric influenza-neutralizing proteins targeting the hemagglutinin receptor binding site

Many viral surface glycoproteins and cell surface receptors are homo-oligomers, and thus can potentially be targeted by geometrically matched homo-oligomers that engage all subunits simultaneously to attain high avidity and/or lock subunits together. The adaptive immune system cannot generally employ this strategy since the individual antibody binding sites are not arranged with appropriate geometry to simultaneously engage multiple sites in a single target homo-oligomer. We describe a general strategy for the computational design of homo-oligomeric protein assemblies with binding functionality precisely matched to homo-oligomeric target sites. In the first step, a small protein is designed that binds a single site on the target. In the second step, the designed protein is assembled into a homo-oligomer such that the designed binding sites are aligned with the target sites. We use this approach to design high-avidity trimeric proteins that bind influenza A hemagglutinin (HA) at its conserved receptor binding site. The designed trimers can both capture and detect HA in a paper-based diagnostic format, neutralizes influenza in cell culture, and completely protects mice when given as a single dose 24 h before or after challenge with influenza.

How HIV-1 entry mechanism and broadly neutralizing antibodies guide structure-based vaccine design

PURPOSE OF REVIEW

An HIV-1 vaccine that elicits broadly neutralizing antibodies (bNAbs) remains to be developed. Here, we review how knowledge of bNAbs and HIV-1 entry mechanism is guiding the structure-based design of vaccine immunogens and immunization regimens.

RECENT FINDINGS

Isolation of bNAbs from HIV-1-infected donors has led to an unprecedented understanding of the sites of vulnerability that these antibodies target on the HIV-1 envelope (Env) as well as of the immunological pathways that these antibody lineages follow to develop broad and potent neutralization. Sites of vulnerability, however, reside in the context of diverse Env conformations required for HIV-1 entry, including a prefusion-closed state, a single-CD4-bound intermediate, a three-CD4-bound intermediate, a prehairpin intermediate and postfusion states, and it is not always clear which structural state optimally presents a particular site of vulnerability in the vaccine context. Furthermore, detailed knowledge of immunological pathways has led to debate among vaccine developers as to how much of the natural antibody-developmental pathway immunogens should mimic, ranging from only the recognized epitope to multiple antigens from the antibody-virus coevolution process.

SUMMARY

A plethora of information on bNAbs is guiding HIV-1-vaccine development. We highlight consideration of the appropriate structural context from the HIV-1-entry mechanism and extraordinary progress with replicating template B-cell ontogenies.

Differential Antibody Responses to Conserved HIV-1 Neutralizing Epitopes in the Context of Multivalent Scaffolds and Native-Like gp140 Trimers

Broadly neutralizing antibodies (bNAbs) have provided valuable insights into the humoral immune response to HIV-1. While rationally designed epitope scaffolds and well-folded gp140 trimers have been proposed as vaccine antigens, a comparative understanding of their antibody responses has not yet been established. In this study, we probed antibody responses to the N332 supersite and the membrane-proximal external region (MPER) in the context of heterologous protein scaffolds and native-like gp140 trimers. Ferritin nanoparticles and fragment crystallizable (Fc) regions were utilized as multivalent carriers to display scaffold antigens with grafted N332 and MPER epitopes, respectively. Trimeric scaffolds were also identified to stabilize the MPER-containing BG505 gp140.681 trimer in a native-like conformation. Following structural and antigenic evaluation, a subset of scaffold and trimer antigens was selected for immunization in BALB/c mice. Serum binding revealed distinct patterns of antibody responses to these two bNAb targets presented in different structural contexts. For example, the N332 nanoparticles elicited glycan epitope-specific antibody responses that could also recognize the native trimer, while a scaffolded BG505 gp140.681 trimer generated a stronger and more rapid antibody response to the trimer apex than its parent gp140.664 trimer. Furthermore, next-generation sequencing (NGS) of mouse splenic B cells revealed expansion of antibody lineages with long heavy-chain complementarity-determining region 3 (HCDR3) loops upon activation by MPER scaffolds, in contrast to the steady repertoires primed by N332 nanoparticles and a soluble gp140.664 trimer. These findings will facilitate the future development of a coherent vaccination strategy that combines both epitope-focused and trimer-based approaches.IMPORTANCE Both epitope-focused and trimer-based strategies are currently being explored in HIV-1 vaccine development, which aims to elicit broadly neutralizing antibodies (bNAbs) targeting conserved epitopes on the viral envelope (Env). However, little is known about the differences in antibody response to these bNAb targets presented by foreign scaffolds and native Env. In this study, a systematic effort was undertaken to design multivalent epitope scaffolds and soluble gp140.681 trimers with a complete antigenic surface, and to comparatively analyze the antibody responses elicited by these antigens to the N332 supersite and MPER in a mouse model. This study will inform both epitope-focused and trimer-based vaccine design and will facilitate integration of the two vaccine strategies.

SAGE: A Fast Computational Tool for Linear Epitope Grafting onto a Foreign Protein Scaffold

Computational design is becoming a driving force of structural vaccinology, whereby protein antigens are engineered to generate new biomolecules with optimized immunological properties. In particular, the design of new proteins that contain multiple, different epitopes can potentially provide novel highly efficient vaccine candidates. In this context, epitope grafting, which entails the transplantation of an antibody recognition motif from one protein onto a different protein scaffold (possibly containing other immunoreactive sequences) holds great promise for the realization of superantigens. Herein, we present SAGE (strategy for alignment and grafting of epitopes), an automated computational tool for the implantation of immunogenic epitopes onto a given scaffold. It is based on the comparison between the expected secondary structures of the candidates to be grafted with all the secondary structures in the target scaffold. Evaluating the differences both in sequence and in structure between the epitope and the scaffold returns a ranking of most probable molecules containing the new antigenic sequence. We validate this approach identifying the grafting positions obtained in previous works by experimental and computational methods, proving an efficient, flexible, and fast tool to perform the initial scanning for epitope grafting. This approach is fully general and may be applied to any target antigen and candidate epitopes with known 3D structures.

Achievements and Challenges in Computational Protein Design

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a "CPD 101". These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

Rational design of TNFα binding proteins based on the de novo designed protein DS119

De novo protein design offers templates for engineering tailor-made protein functions and orthogonal protein interaction networks for synthetic biology research. Various computational methods have been developed to introduce functional sites in known protein structures. De novo designed protein scaffolds provide further opportunities for functional protein design. Here we demonstrate the rational design of novel tumor necrosis factor alpha (TNFα) binding proteins using a home-made grafting program AutoMatch. We grafted three key residues from a virus 2L protein to a de novo designed small protein, DS119, with consideration of backbone flexibility. The designed proteins bind to TNFα with micromolar affinities. We further optimized the interface residues with RosettaDesign and significantly improved the binding capacity of one protein Tbab1-4. These designed proteins inhibit the activity of TNFα in cellular luciferase assays. Our work illustrates the potential application of the de novo designed protein DS119 in protein engineering, biomedical research, and protein sequence-structure-function studies.

Motif-Driven Design of Protein-Protein Interfaces

Protein-protein interfaces regulate many critical processes for cellular function. The ability to accurately control and regulate these molecular interactions is of major interest for biomedical and synthetic biology applications, as well as to address fundamental biological questions. In recent years, computational protein design has emerged as a tool for designing novel protein-protein interactions with functional relevance. Although attractive, these computational tools carry a steep learning curve. In order to make some of these methods more accessible, we present detailed descriptions and examples of ROSETTA computational protocols for the design of functional protein binders using seeded protein interface design. In these protocols, a motif of known structure that interacts with the target site is grafted into a scaffold protein, followed by design of the surrounding interaction surface.

A Framework to Simplify Combined Sampling Strategies in Rosetta

A core task in computational structural biology is the search of conformational space for low energy configurations of a biological macromolecule. Because conformational space has a very high dimensionality, the most successful search methods integrate some form of prior knowledge into a general sampling algorithm to reduce the effective dimensionality. However, integrating multiple types of constraints can be challenging. To streamline the incorporation of diverse constraints, we developed the Broker: an extension of the Rosetta macromolecular modeling suite that can express a wide range of protocols using constraints by combining small, independent modules, each of which implements a different set of constraints. We demonstrate expressiveness of the Broker through several code vignettes. The framework enables rapid protocol development in both biomolecular design and structural modeling tasks and thus is an important step towards exposing the rich functionality of Rosetta's core libraries to a growing community of users addressing a diverse set of tasks in computational biology.