Computation-guided backbone grafting of a discontinuous motif onto a protein scaffold

Rational structure-guided design of a blood stage malaria vaccine immunogen presenting a single epitope from PfRH5

There is an urgent need for improved malaria vaccine immunogens. Invasion of erythrocytes by Plasmodium falciparum is essential for its life cycle, preceding symptoms of disease and parasite transmission. Antibodies which target PfRH5 are highly effective at preventing erythrocyte invasion and the most potent growth-inhibitory antibodies bind a single epitope. Here we use structure-guided approaches to design a small synthetic immunogen, RH5-34EM which recapitulates this epitope. Structural biology and biophysics demonstrate that RH5-34EM is correctly folded and binds neutralising monoclonal antibodies with nanomolar affinity. In immunised rats, RH5-34EM induces PfRH5-targeting antibodies that inhibit parasite growth. While PfRH5-specific antibodies were induced at a lower concentration by RH5-34EM than by PfRH5, RH5-34EM induced antibodies that were a thousand-fold more growth-inhibitory as a factor of PfRH5-specific antibody concentration. Finally, we show that priming with RH5-34EM and boosting with PfRH5 achieves the best balance between antibody quality and quantity and induces the most effective growth-inhibitory response. This rationally designed vaccine immunogen is now available for use as part of future malaria vaccines, alone or in combination with other immunogens.

Opportunities and challenges in design and optimization of protein function

The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calculations, as well as machine learning tools, have dramatically improved protein engineering and design. In this Review, we discuss how these methods have enabled the design of increasingly complex structures and therapeutically relevant activities. Additionally, protein optimization methods have improved the stability and activity of complex eukaryotic proteins. Thanks to their increased reliability, computational design methods have been applied to improve therapeutics and enzymes for green chemistry and have generated vaccine antigens, antivirals and drug-delivery nano-vehicles. Moreover, the high success of design methods reflects an increased understanding of basic rules that govern the relationships among protein sequence, structure and function. However, de novo design is still limited mostly to α-helix bundles, restricting its potential to generate sophisticated enzymes and diverse protein and small-molecule binders. Designing complex protein structures is a challenging but necessary next step if we are to realize our objective of generating new-to-nature activities.

Inducing Long Lasting B Cell and T Cell Immunity Against Multiple Variants of SARS-CoV-2 Through Mutant Bacteriophage Qβ-Receptor Binding Domain Conjugate

More than 3 years into the global pandemic, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains a significant threat to public health. Immunities acquired from infection or current vaccines fail to provide long term protection against subsequent infections, mainly due to their fast-waning nature and the emergence of variants of concerns (VOCs) such as Omicron. To overcome these limitations, SARS-CoV-2 Spike protein receptor binding domain (RBD)-based epitopes are investigated as conjugates with a powerful carrier, the mutant bacteriophage Qβ (mQβ). The epitope design is critical to eliciting potent antibody responses with the full length RBD being superior to peptide and glycopeptide antigens. The full length RBD conjugated with mQβ activates both humoral and cellular immune systems in vivo, inducing broad spectrum, persistent, and comprehensive immune responses effective against multiple VOCs including Delta and Omicron variants, rendering it a promising vaccine candidate.

Conceptual design of a macromolecular diffractometer for the Jülich high brilliance source

In this work, a concept for a neutron diffractometer for high-resolution macromolecular structures has been developed within the Jülich High Brilliance Neutron Source (HBS) project. The SELENE optics are adapted to the requirements of the instrument to achieve a tunable low background neutron beam at mm2 scale sample area. With the optimized guide geometry, a low background neutron beam can be achieved at the small sample area with tunable divergence and size. For the 1 × 1 mm2 sample, a flux of 1.10 × 107 n/s/cm2 for 0.38° divergence is calculated in the 2-4 Å wavelength range, which is about 84.6% of the flux at MaNDi of the high-power spallation source SNS at ORNL. Virtual neutron scattering experiments have been performed to demonstrate the instrument's capabilities for studies of mm scale samples with large unit cells. Results of Vitesse simulations indicate that unit cell sizes of up to 200 Å are possible to be resolved with the proposed instrument.

Bringing immunofocusing into focus

Immunofocusing is a strategy to create immunogens that redirect humoral immune responses towards a targeted epitope and away from non-desirable epitopes. Immunofocusing methods often aim to develop "universal" vaccines that provide broad protection against highly variant viruses such as influenza virus, human immunodeficiency virus (HIV-1), and most recently, severe acute respiratory syndrome coronavirus (SARS-CoV-2). We use existing examples to illustrate five main immunofocusing strategies-cross-strain boosting, mosaic display, protein dissection, epitope scaffolding, and epitope masking. We also discuss obstacles for immunofocusing like immune imprinting. A thorough understanding, advancement, and application of the methods we outline here will enable the design of high-resolution vaccines that protect against future viral outbreaks.

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.

De novo design of stable proteins that efficaciously inhibit oncogenic G proteins

Many protein therapeutics are competitive inhibitors that function by binding to endogenous proteins and preventing them from interacting with native partners. One effective strategy for engineering competitive inhibitors is to graft structural motifs from a native partner into a host protein. Here, we develop and experimentally test a computational protocol for embedding binding motifs in de novo designed proteins. The protocol uses an "inside-out" approach: Starting with a structural model of the binding motif docked against the target protein, the de novo protein is built by growing new structural elements off the termini of the binding motif. During backbone assembly, a score function favors backbones that introduce new tertiary contacts within the designed protein and do not introduce clashes with the target binding partner. Final sequences are designed and optimized using the molecular modeling program Rosetta. To test our protocol, we designed small helical proteins to inhibit the interaction between Gαq and its effector PLC-β isozymes. Several of the designed proteins remain folded above 90°C and bind to Gαq with equilibrium dissociation constants tighter than 80 nM. In cellular assays with oncogenic variants of Gαq , the designed proteins inhibit activation of PLC-β isozymes and Dbl-family RhoGEFs. Our results demonstrate that computational protein design, in combination with motif grafting, can be used to directly generate potent inhibitors without further optimization via high throughput screening or selection.

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.

Computational Protein Design for COVID-19 Research and Emerging Therapeutics

As the world struggles with the ongoing COVID-19 pandemic, unprecedented obstacles have continuously been traversed as new SARS-CoV-2 variants continually emerge. Infectious disease outbreaks are unavoidable, but the knowledge gained from the successes and failures will help create a robust health management system to deal with such pandemics. Previously, scientists required years to develop diagnostics, therapeutics, or vaccines; however, we have seen that, with the rapid deployment of high-throughput technologies and unprecedented scientific collaboration worldwide, breakthrough discoveries can be accelerated and insights broadened. Computational protein design (CPD) is a game-changing new technology that has provided alternative therapeutic strategies for pandemic management. In addition to the development of peptide-based inhibitors, miniprotein binders, decoys, biosensors, nanobodies, and monoclonal antibodies, CPD has also been used to redesign native SARS-CoV-2 proteins and human ACE2 receptors. We discuss how novel CPD strategies have been exploited to develop rationally designed and robust COVID-19 treatment strategies.

Cholera toxin B scaffolded, focused SIV V2 epitope elicits antibodies that influence the risk of SIVmac251 acquisition in macaques

Introduction

An efficacious HIV vaccine will need to elicit a complex package of innate, humoral, and cellular immune responses. This complex package of responses to vaccine candidates has been studied and yielded important results, yet it has been a recurring challenge to determine the magnitude and protective effect of specific in vivo immune responses in isolation. We therefore designed a single, viral-spike-apical, epitope-focused V2 loop immunogen to reveal individual vaccine-elicited immune factors that contribute to protection against HIV/SIV.

Method

We generated a novel vaccine by incorporating the V2 loop B-cell epitope in the cholera toxin B (CTB) scaffold and compared two new immunization regimens to a historically protective 'standard' vaccine regimen (SVR) consisting of 2xDNA prime boosted with 2xALVAC-SIV and 1xΔV1gp120. We immunized a cohort of macaques with 5xCTB-V2c vaccine+alum intramuscularly simultaneously with topical intrarectal vaccination of CTB-V2c vaccine without alum (5xCTB-V2/alum). In a second group, we tested a modified version of the SVR consisting of 2xDNA prime and boosted with 1xALVAC-SIV and 2xALVAC-SIV+CTB-V2/alum, (DA/CTB-V2c/alum).

Results

In the absence of any other anti-viral antibodies, V2c epitope was highly immunogenic when incorporated in the CTB scaffold and generated highly functional anti-V2c antibodies in the vaccinated animals. 5xCTB-V2c/alum vaccination mediated non-neutralizing ADCC activity and efferocytosis, but produced low avidity, trogocytosis, and no neutralization of tier 1 virus. Furthermore, DA/CTB-V2c/alum vaccination also generated lower total ADCC activity, avidity, and neutralization compared to the SVR. These data suggest that the ΔV1gp120 boost in the SVR yielded more favorable immune responses than its CTB-V2c counterpart. Vaccination with the SVR generates CCR5- α4β7+CD4+ Th1, Th2, and Th17 cells, which are less likely to be infected by SIV/HIV and likely contributed to the protection afforded in this regimen. The 5xCTB-V2c/alum regimen likewise elicited higher circulating CCR5- α4β7+ CD4+ T cells and mucosal α4β7+ CD4+ T cells compared to the DA/CTB-V2c/alum regimen, whereas the first cell type was associated with reduced risk of viral acquisition.

Conclusion

Taken together, these data suggest that individual viral spike B-cell epitopes can be highly immunogenic and functional as isolated immunogens, although they might not be sufficient on their own to provide full protection against HIV/SIV infection.

De novo design of stable proteins that efficaciously inhibit oncogenic G proteins

Many protein therapeutics are competitive inhibitors that function by binding to endogenous proteins and preventing them from interacting with native partners. One effective strategy for engineering competitive inhibitors is to graft structural motifs from a native partner into a host protein. Here, we develop and experimentally test a computational protocol for embedding binding motifs in de novo designed proteins. The protocol uses an "inside-out" approach: Starting with a structural model of the binding motif docked against the target protein, the de novo protein is built by growing new structural elements off the termini of the binding motif. During backbone assembly, a score function favors backbones that introduce new tertiary contacts within the designed protein and do not introduce clashes with the target binding partner. Final sequences are designed and optimized using the molecular modeling program Rosetta. To test our protocol, we designed small helical proteins to inhibit the interaction between Gα q and its effector PLC-β isozymes. Several of the designed proteins remain folded above 90°C and bind to Gα q with equilibrium dissociation constants tighter than 80 nM. In cellular assays with oncogenic variants of Gα q , the designed proteins inhibit activation of PLC-β isozymes and Dbl-family RhoGEFs. Our results demonstrate that computational protein design, in combination with motif grafting, can be used to directly generate potent inhibitors without further optimization via high throughput screening or selection.

statement for broader audience

Engineered proteins that bind to specific target proteins are useful as research reagents, diagnostics, and therapeutics. We used computational protein design to engineer de novo proteins that bind and competitively inhibit the G protein, Gα q , which is an oncogene for uveal melanomas. This computational method is a general approach that should be useful for designing competitive inhibitors against other proteins of interest.

Inhibition of a malaria host-pathogen interaction by a computationally designed inhibitor

Malaria is a substantial global health burden with 229 million cases in 2019 and 450,000 deaths annually. Plasmodium vivax is the most widespread malaria-causing parasite putting 2.5 billion people at risk of infection. P. vivax has a dormant liver stage and therefore can exist for long periods undetected. Its blood-stage can cause severe reactions and hospitalization. Few treatment and detection options are available for this pathogen. A unique characteristic of P. vivax is that it depends on the Duffy antigen/receptor for chemokines (DARC) on the surface of host red blood cells for invasion. P. vivax employs the Duffy binding protein (DBP) to bind to DARC. We first de novo designed a three helical bundle scaffolding database which was screened via protease digestions for stability. Protease-resistant scaffolds highlighted thresholds for stability, which we utilized for selecting DARC mimetics that we subsequentially designed through grafting and redesign of these scaffolds. The optimized design small helical protein disrupts the DBP:DARC interaction. The inhibitor blocks the receptor binding site on DBP and thus forms a strong foundation for a therapeutic that will inhibit reticulocyte infection and prevent the pathogenesis of P. vivax malaria.

Coordinate-Dependent Drift-Diffusion Reveals the Kinetic Intermediate Traps of Top7-Based Proteins

The computer-designed Top7 served as a scaffold to produce immunoreactive proteins by grafting of the 2F5 HIV-1 antibody epitope (Top7-2F5) followed by biotinylation (Top7-2F5-biotin). The resulting nonimmunoglobulin affinity proteins were effective in inducing and detecting the HIV-1 antibody. However, the grafted Top7-2F5 design led to protein aggregation, as opposed to the soluble biotinylated Top7-2F5-biotin. The structure-based model predicted that the thermodynamic cooperativity of Top7 increases after grafting and biotin-labeling, reducing their intermediate state populations. In this work, the folding kinetic traps that might contribute to the aggregation propensity are investigated by the diffusion theory. Since the engineered proteins have similar sequence and structural homology, they served as protein models to study the kinetic intermediate traps that were uncovered by characterizing the position-dependent drift-velocity (v(Q)) and the diffusion (D(Q)) coefficients. These coordinate-dependent coefficients were taken into account to obtain the folding and transition path times over the free energy transition states containing the intermediate kinetic traps. This analysis may be useful to predict the aggregated kinetic traps of scaffold-epitope proteins that might compose novel diagnostic and therapeutic platforms.

Chimeric Human Papillomavirus-16 Virus-like Particles Presenting P18I10 and T20 Peptides from HIV-1 Envelope Induce HPV16 and HIV-1-Specific Humoral and T Cell-Mediated Immunity in BALB/c Mice

In this study, the HIV-1 P18I10 CTL peptide derived from the V3 loop of HIV-1 gp120 and the T20 anti-fusion peptide of HIV-1 gp41 were inserted into the HPV16 L1 capsid protein to construct chimeric HPV:HIV (L1:P18I10 and L1:T20) VLPs by using the mammalian cell expression system. The HPV:HIV VLPs were purified by chromatography. We demonstrated that the insertion of P18I10 or T20 peptides into the DE loop of HPV16 L1 capsid proteins did not affect in vitro stability, self-assembly and morphology of chimeric HPV:HIV VLPs. Importantly, it did not interfere either with the HIV-1 antibody reactivity targeting sequential and conformational P18I10 and T20 peptides presented on chimeric HPV:HIV VLPs or with the induction of HPV16 L1-specific antibodies in vivo. We observed that chimeric L1:P18I10/L1:T20 VLPs vaccines could induce HPV16- but weak HIV-1-specific antibody responses and elicited HPV16- and HIV-1-specific T-cell responses in BALB/c mice. Moreover, could be a potential booster to increase HIV-specific cellular responses in the heterologous immunization after priming with rBCG.HIVA vaccine. This research work would contribute a step towards the development of the novel chimeric HPV:HIV VLP-based vaccine platform for controlling HPV16 and HIV-1 infection, which is urgently needed in developing and industrialized countries.

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.

Novel chimeric proteins mimicking SARS-CoV-2 spike epitopes with broad inhibitory activity

SARS-CoV-2 spike (S) protein mediates virus attachment to the cells and fusion between viral and cell membranes. Membrane fusion is driven by mutual interaction between the highly conserved heptad-repeat regions 1 and 2 (HR1 and HR2) of the S2 subunit of the spike. For this reason, these S2 regions are interesting therapeutic targets for COVID-19. Although HR1 and HR2 have been described as transiently exposed during the fusion process, no significant antibody responses against these S2 regions have been reported. Here we designed chimeric proteins that imitate highly stable HR1 helical trimers and strongly bind to HR2. The proteins have broad inhibitory activity against WT B.1 and BA.1 viruses. Sera from COVID-19 convalescent donors showed significant levels of reactive antibodies (IgG and IgA) against the HR1 mimetic proteins, whereas these antibody responses were absent in sera from uninfected donors. Moreover, both inhibitory activity and antigenicity of the proteins correlate positively with their structural stability but not with the number of amino acid changes in their HR1 sequences, indicating a conformational and conserved nature of the involved epitopes. Our results reveal previously undetected spike epitopes that may guide the design of new robust COVID-19 vaccines and therapies.

AmyloGraph: a comprehensive database of amyloid-amyloid interactions

Information about the impact of interactions between amyloid proteins on their fibrillization propensity is scattered among many experimental articles and presented in unstructured form. We manually curated information located in almost 200 publications (selected out of 562 initially considered), obtaining details of 883 experimentally studied interactions between 46 amyloid proteins or peptides. We also proposed a novel standardized terminology for the description of amyloid-amyloid interactions, which is included in our database, covering all currently known types of such a cross-talk, including inhibition of fibrillization, cross-seeding and other phenomena. The new approach allows for more specific studies on amyloids and their interactions, by providing very well-defined data. AmyloGraph, an online database presenting information on amyloid-amyloid interactions, is available at (http://AmyloGraph.com/). Its functionalities are also accessible as the R package (https://github.com/KotulskaLab/AmyloGraph). AmyloGraph is the only publicly available repository for experimentally determined amyloid-amyloid interactions.

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.

A Hemagglutinin Stem Vaccine Designed Rationally by AlphaFold2 Confers Broad Protection against Influenza B Infection

Two lineages of influenza B viruses (IBV) co-circulating in human beings have been posing a significant public health burden worldwide. A substantial number of broadly neutralizing antibodies (bnAbs) have been identified targeting conserved epitopes on hemagglutinin (HA) stem domain, posing great interest for universal influenza vaccine development. Various strategies to design immunogens that selectively present these conserved epitopes are being explored. However, it has been a challenge to retain native conformation of the HA stem region, especially for soluble expression in prokaryotic systems. Here, using a structure prediction tool AlphaFold2, we rationally designed a stable stem antigen “B60-Stem-8071”, an HA stem vaccine derived from B/Brisbane/60/2006 grafted with a CR8071 epitope as a linker. The B60-Stem-8071 exhibited better solubility and more stable expression in the E. coli system compared to the naïve HA stem antigen. Immunization with B60-Stem-8071 in mice generated cross-reactive antibodies and protected mice broadly against lethal challenge with Yamagata and Victoria lineages of influenza B virus. Notably, soluble expression of B60-stem-8071 in the E. coli system showed the potential to produce the influenza B vaccine in a low-cost way. This study represents a proof of concept for the rational design of HA stem antigen based on structure prediction and analysis.

Epitope-focused immunogen design based on the ebolavirus glycoprotein HR2-MPER region

The three human pathogenic ebolaviruses: Zaire (EBOV), Bundibugyo (BDBV), and Sudan (SUDV) virus, cause severe disease with high fatality rates. Epitopes of ebolavirus glycoprotein (GP) recognized by antibodies with binding breadth for all three ebolaviruses are of major interest for rational vaccine design. In particular, the heptad repeat 2 -membrane-proximal external region (HR2-MPER) epitope is relatively conserved between EBOV, BDBV, and SUDV GP and targeted by human broadly-neutralizing antibodies. To study whether this epitope can serve as an immunogen for the elicitation of broadly-reactive antibody responses, protein design in Rosetta was employed to transplant the HR2-MPER epitope identified from a co-crystal structure with the known broadly-reactive monoclonal antibody (mAb) BDBV223 onto smaller scaffold proteins. From computational analysis, selected immunogen designs were produced as recombinant proteins and functionally validated, leading to the identification of a sterile alpha motif (SAM) domain displaying the BDBV-HR2-MPER epitope near its C terminus as a promising candidate. The immunogen was fused to one component of a self-assembling, two-component nanoparticle and tested for immunogenicity in rabbits. Robust titers of cross-reactive serum antibodies to BDBV and EBOV GPs and moderate titers to SUDV GP were induced following immunization. To confirm the structural composition of the immunogens, solution NMR studies were conducted and revealed structural flexibility in the C-terminal residues of the epitope. Overall, our study represents the first report on an epitope-focused immunogen design based on the structurally challenging BDBV-HR2-MPER epitope.

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.

Motif-driven protein binder design towards transferrin receptor helical domain

Human transferrin receptor 1 (TfR) is necessary for the delivery of the iron carrier protein transferrin into cells and can be utilized for targeted delivery across cellular membranes. Binding of transferrin to the receptor is regulated by hereditary hemochromatosis protein (HFE), an iron regulatory protein that partly shares a binding site with transferrin on TfR. Here, we derived essential binding interactions from HFE and computationally grafted these into a library of small protein scaffolds. One of the designed proteins, TB08, was further optimized computationally and experimentally to identify variants with improved binding to TfR. The optimized variant, TB08 S3.1, expressed well in the E. coli expression system and had an affinity to TfR in the low micromolar range, K_d  ≈ 1 μm, as determined by surface plasmon resonance. A binding competition assay with transferrin further confirmed the interaction of the evolved variant to TfR at the shared binding surface. Additionally, the GFP-tagged evolved variant of TB08 demonstrated cellular internalization as determined by fluorescent and confocal microscopy in HeLa cells. The designed protein is small, allows for robust cargo tagging, and interacts specifically with TfR, thus making it a valuable tool for the characterization of TfR-mediated cellular transport mechanisms and for the assessment of engineering strategies for cargo delivery across cell membranes.

Designer proteins that competitively inhibit Gαq by targeting its effector site

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

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.

Broad betacoronavirus neutralization by a stem helix-specific human antibody

The spillovers of betacoronaviruses in humans and the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highlight the need for broad coronavirus countermeasures. We describe five monoclonal antibodies (mAbs) cross-reacting with the stem helix of multiple betacoronavirus spike glycoproteins isolated from COVID-19 convalescent individuals. Using structural and functional studies, we show that the mAb with the greatest breadth (S2P6) neutralizes pseudotyped viruses from three different subgenera through the inhibition of membrane fusion, and we delineate the molecular basis for its cross-reactivity. S2P6 reduces viral burden in hamsters challenged with SARS-CoV-2 through viral neutralization and Fc-mediated effector functions. Stem helix antibodies are rare, oftentimes of narrow specificity, and can acquire neutralization breadth through somatic mutations. These data provide a framework for structure-guided design of pan-betacoronavirus vaccines eliciting broad protection.

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.

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.

Structural basis for broad coronavirus neutralization

Three highly pathogenic β-coronaviruses have crossed the animal-to-human species barrier in the past two decades: SARS-CoV, MERS-CoV and SARS-CoV-2. To evaluate the possibility of identifying antibodies with broad neutralizing activity, we isolated a monoclonal antibody, termed B6, that cross-reacts with eight β-coronavirus spike glycoproteins, including all five human-infecting β-coronaviruses. B6 broadly neutralizes entry of pseudotyped viruses from lineages A and C, but not from lineage B, and the latter includes SARS-CoV and SARS-CoV-2. Cryo-EM, X-ray crystallography and membrane fusion assays reveal that B6 binds to a conserved cryptic epitope located in the fusion machinery. The data indicate that antibody binding sterically interferes with the spike conformational changes leading to membrane fusion. Our data provide a structural framework explaining B6 cross-reactivity with β-coronaviruses from three lineages, along with a proof of concept for antibody-mediated broad coronavirus neutralization elicited through vaccination. This study unveils an unexpected target for next-generation structure-guided design of a pan-β-coronavirus vaccine.

Bottom-up de novo design of functional proteins with complex structural features

De novo protein design has enabled the creation of new protein structures. However, the design of functional proteins has proved challenging, in part due to the difficulty of transplanting structurally complex functional sites to available protein structures. Here, we used a bottom-up approach to build de novo proteins tailored to accommodate structurally complex functional motifs. We applied the bottom-up strategy to successfully design five folds for four distinct binding motifs, including a bifunctionalized protein with two motifs. Crystal structures confirmed the atomic-level accuracy of the computational designs. These de novo proteins were functional as components of biosensors to monitor antibody responses and as orthogonal ligands to modulate synthetic signaling receptors in engineered mammalian cells. Our work demonstrates the potential of bottom-up approaches to accommodate complex structural motifs, which will be essential to endow de novo proteins with elaborate biochemical functions, such as molecular recognition or catalysis.

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.

Potential neutralizing antibodies discovered for novel corona virus using machine learning

The fast and untraceable virus mutations take lives of thousands of people before the immune system can produce the inhibitory antibody. The recent outbreak of COVID-19 infected and killed thousands of people in the world. Rapid methods in finding peptides or antibody sequences that can inhibit the viral epitopes of SARS-CoV-2 will save the life of thousands. To predict neutralizing antibodies for SARS-CoV-2 in a high-throughput manner, in this paper, we use different machine learning (ML) model to predict the possible inhibitory synthetic antibodies for SARS-CoV-2. We collected 1933 virus-antibody sequences and their clinical patient neutralization response and trained an ML model to predict the antibody response. Using graph featurization with variety of ML methods, like XGBoost, Random Forest, Multilayered Perceptron, Support Vector Machine and Logistic Regression, we screened thousands of hypothetical antibody sequences and found nine stable antibodies that potentially inhibit SARS-CoV-2. We combined bioinformatics, structural biology, and Molecular Dynamics (MD) simulations to verify the stability of the candidate antibodies that can inhibit SARS-CoV-2.

Potential neutralizing antibodies discovered for novel corona virus using machine learning

The fast and untraceable virus mutations take lives of thousands of people before the immune system can produce the inhibitory antibody. The recent outbreak of COVID-19 infected and killed thousands of people in the world. Rapid methods in finding peptides or antibody sequences that can inhibit the viral epitopes of SARS-CoV-2 will save the life of thousands. To predict neutralizing antibodies for SARS-CoV-2 in a high-throughput manner, in this paper, we use different machine learning (ML) model to predict the possible inhibitory synthetic antibodies for SARS-CoV-2. We collected 1933 virus-antibody sequences and their clinical patient neutralization response and trained an ML model to predict the antibody response. Using graph featurization with variety of ML methods, like XGBoost, Random Forest, Multilayered Perceptron, Support Vector Machine and Logistic Regression, we screened thousands of hypothetical antibody sequences and found nine stable antibodies that potentially inhibit SARS-CoV-2. We combined bioinformatics, structural biology, and Molecular Dynamics (MD) simulations to verify the stability of the candidate antibodies that can inhibit SARS-CoV-2.

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.

Structural basis for broad coronavirus neutralization

Three highly pathogenic β-coronaviruses crossed the animal-to-human species barrier in the past two decades: SARS-CoV, MERS-CoV and SARS-CoV-2. SARS-CoV-2 has infected more than 64 million people worldwide, claimed over 1.4 million lives and is responsible for the ongoing COVID-19 pandemic. We isolated a monoclonal antibody, termed B6, cross-reacting with eight β-coronavirus spike glycoproteins, including all five human-infecting β-coronaviruses, and broadly inhibiting entry of pseudotyped viruses from two coronavirus lineages. Cryo-electron microscopy and X-ray crystallography characterization reveal that B6 binds to a conserved cryptic epitope located in the fusion machinery and indicate that antibody binding sterically interferes with spike conformational changes leading to membrane fusion. Our data provide a structural framework explaining B6 cross-reactivity with β-coronaviruses from three lineages along with proof-of-concept for antibody-mediated broad coronavirus neutralization elicited through vaccination. This study unveils an unexpected target for next-generation structure-guided design of a pan-coronavirus vaccine.

Reprogramming the Specificity of a Protein Interface by Computational and Data-Driven Design

The formation of specific protein complexes in a cell is a non-trivial problem given the co-existence of thousands of different polypeptide chains. A particularly difficult case are two glutamine amidotransferase complexes (anthranilate synthase [AS] and aminodeoxychorismate synthase [ADCS]), which are composed of homologous pairs of synthase and glutaminase subunits. We have attempted to identify discriminating interface residues of the glutaminase subunit TrpG from AS, which are responsible for its specific interaction with the synthase subunit TrpEx and prevent binding to the closely related synthase subunit PabB from ADCS. For this purpose, TrpG-specific interface residues were grafted into the glutaminase subunit PabA from ADCS by two different approaches, namely a computational and a data-driven one. Both approaches resulted in PabA variants that bound TrpEx with higher affinity than PabB. Hence, we have accomplished a reprogramming of protein-protein interaction specificity that provides insights into the evolutionary adaptation of protein interfaces.

Local environment effects on charged mutations for developing aggregation-resistant monoclonal antibodies

Protein aggregation is a major concern in biotherapeutic applications of monoclonal antibodies. Introducing charged mutations is among the promising strategies to improve aggregation resistance. However, the impact of such mutations on solubilizing activity depends largely on the inserting location, whose mechanism is still not well understood. Here, we address this issue from a solvation viewpoint, and this is done by analyzing how the change in solvation free energy upon charged mutation is composed of individual contributions from constituent residues. To this end, we perform molecular dynamics simulations for a number of antibody mutants and carry out the residue-wise decomposition of the solvation free energy. We find that, in addition to the previously identified “global” principle emphasizing the key role played by the protein total net charge, a local net charge within \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim$$\end{document}∼15 Å from the mutation site exerts significant effects. For example, when the net charge of an antibody is positive, the global principle states that introducing a positively charged mutation will lead to more favorable solvation. Our finding further adds that an even more optimal mutation can be done at the site around which more positively charged residues and fewer negatively charged residues are present. Such a “local” design principle accounts for the location dependence of charged mutations, and will be useful in producing aggregation-resistant antibodies.

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.

De novo protein design enables the precise induction of RSV-neutralizing antibodies

De novo protein design has been successful in expanding the natural protein repertoire. However, most de novo proteins lack biological function, presenting a major methodological challenge. In vaccinology, the induction of precise antibody responses remains a cornerstone for next-generation vaccines. Here, we present a protein design algorithm called TopoBuilder, with which we engineered epitope-focused immunogens displaying complex structural motifs. In both mice and nonhuman primates, cocktails of three de novo-designed immunogens induced robust neutralizing responses against the respiratory syncytial virus. Furthermore, the immunogens refocused preexisting antibody responses toward defined neutralization epitopes. Overall, our design approach opens the possibility of targeting specific epitopes for the development of vaccines and therapeutic antibodies and, more generally, will be applicable to the design of de novo proteins displaying complex functional motifs.

Development of a multivalent enterovirus subunit vaccine based on immunoinformatic design principles for the prevention of HFMD

Hand, foot and mouth disease (HFMD) is mainly caused by EV-A71 and CV-A16. An increasing number of cases have been found to be caused by CV-A10, CV-A6, CV-B3 and the outbreaks are becoming increasingly more complex, often accompanied by the prevalence of a variety of enteroviruses. Based on the principle of synthetic peptide vaccines, we applied immune-informatics to design a highly efficient and safe multivalent epitope-based vaccine against EV-A71, CV-A16, CV-A10, CV-A6 and CV-B3. By screening B-cells, HTL and CTL cell antigen epitopes with high conservativity and immunogenicity that have no toxic effect on the host, further analysis confirmed that the vaccine built was IFN-γ inductive and IL-4 non-inductive HTL cell epitopes and had population coverage corresponding to MHC molecular alleles associated with T-cell phenotype. The multivalent enterovirus vaccine was constructed to connect the 50 s ribosomal protein L7/L12 adjuvant and candidate epitopes sequentially through appropriate linkers. Then, the antigenic, allergen and physical properties of the vaccine were evaluated, followed by a secondary structure analysis and tertiary structure modeling, disulfide engineering, refinement and validation. Moreover, the conformational B cell epitope of the vaccine was analyzed. The stability of the TLR4/MD2/Vaccine complex and details at atomic level were investigated by docking and molecular dynamics simulation. Finally, in silico immune simulation and in vivo immune experiments were done. This study provides a high cost-effective method of designing a multivalent enterovirus vaccine protect against a wide range of enterovirus pathogens.

Antibody Lineages with Vaccine-Induced Antigen-Binding Hotspots Develop Broad HIV Neutralization

The vaccine-mediated elicitation of antibodies (Abs) capable of neutralizing diverse HIV-1 strains has been a long-standing goal. To understand how broadly neutralizing antibodies (bNAbs) can be elicited, we identified, characterized, and tracked five neutralizing Ab lineages targeting the HIV-1-fusion peptide (FP) in vaccinated macaques over time. Genetic and structural analyses revealed two of these lineages to belong to a reproducible class capable of neutralizing up to 59% of 208 diverse viral strains. B cell analysis indicated each of the five lineages to have been initiated and expanded by FP-carrier priming, with envelope (Env)-trimer boosts inducing cross-reactive neutralization. These Abs had binding-energy hotspots focused on FP, whereas several FP-directed Abs induced by immunization with Env trimer-only were less FP-focused and less broadly neutralizing. Priming with a conserved subregion, such as FP, can thus induce Abs with binding-energy hotspots coincident with the target subregion and capable of broad neutralization.

One-step sequence and structure-guided optimization of HIV-1 envelope gp140

Stabilization of the metastable envelope glycoprotein (Env) of HIV-1 is hypothesized to improve induction of broadly neutralizing antibodies. We improved the expression yield and stability of the HIV-1 envelope glycoprotein BG505SOSIP.664 gp140 by means of a previously described automated sequence and structure-guided computational thermostabilization approach, PROSS. This combines sequence conservation information with computational assessment of mutant stabilization, thus taking advantage of the extensive natural sequence variation present in HIV-1 Env. PROSS is used to design three gp140 variants with 17–45 mutations relative to the parental construct. One of the designs is experimentally observed to have a fourfold improvement in yield and a 4 °C increment in thermostability. In addition, the designed immunogens have similar antigenicity profiles to the native flexible linker version of wild type, BG505SOSIP.664 gp140 (NFL Wt) to major epitopes targeted by broadly neutralizing antibodies. PROSS eliminates the laborious process of screening many variants for stability and functionality, providing a proof of principle of the method for stabilization and improvement of yield without compromising antigenicity for next generation complex, highly glycosylated vaccine candidates.

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One-step stabilization of HIV-1 Env gp140.

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One-step yield improvement of HIV-1 Env gp140.

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Native-like oligomeric conformation of designed vaccine candidates.

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Unaltered antigenicity of designed vaccine candidates.

Anti-idiotypic antibodies elicit anti-HIV-1-specific B cell responses

Human anti-HIV-1 broadly neutralizing antibodies (bNAbs) protect against infection in animal models. However, bNAbs have not been elicited by vaccination in diverse wild-type animals or humans, in part because B cells expressing the precursors of these antibodies do not recognize most HIV-1 envelopes (Envs). Immunogens have been designed that activate these B cell precursors in vivo, but they also activate competing off-target responses. Here we report on a complementary approach to expand specific B cells using an anti-idiotypic antibody, iv8, that selects for naive human B cells expressing immunoglobulin light chains with 5-amino acid complementarity determining region 3s, a key feature of anti-CD4 binding site (CD4bs)-specific VRC01-class antibodies. In mice, iv8 induced target cells to expand and mature in the context of a polyclonal immune system and produced serologic responses targeting the CD4bs on Env. In summary, the results demonstrate that an anti-idiotypic antibody can specifically recognize and expand rare B cells that express VRC01-class antibodies against HIV-1.

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.

Identification of an Immunogenic Broadly Inhibitory Surface Epitope of the Plasmodium vivax Duffy Binding Protein Ligand Domain

Vivax malaria is the second leading cause of malaria worldwide and the major cause of non-African malaria. Unfortunately, efforts to develop antimalarial vaccines specifically targeting Plasmodium vivax have been largely neglected, and few candidates have progressed into clinical trials. The Duffy binding protein is considered a leading blood-stage vaccine candidate because this ligand’s recognition of the Duffy blood group reticulocyte surface receptor is considered essential for infection. This study identifies a new target epitope on the ligand’s surface that may serve as the target of vaccine-induced binding-inhibitory antibody (BIAb). Understanding the potential targets of vaccine protection will be important for development of an effective vaccine.

The Plasmodium vivax Duffy binding protein region II (DBPII) is a vital ligand for the parasite’s invasion of reticulocytes, thereby making this molecule an attractive vaccine candidate against vivax malaria. However, strain-specific immunity due to DBPII allelic variation in Bc epitopes may complicate vaccine efficacy, suggesting that an effective DBPII vaccine needs to target conserved epitopes that are potential targets of strain-transcending neutralizing immunity. The minimal epitopes reactive with functionally inhibitory anti-DBPII monoclonal antibody (MAb) 3C9 and noninhibitory anti-DBPII MAb 3D10 were mapped using phage display expression libraries, since previous attempts to deduce the 3C9 epitope by cocrystallographic methods failed. Inhibitory MAb 3C9 binds to a conserved conformation-dependent epitope in subdomain 3, while noninhibitory MAb 3D10 binds to a linear epitope in subdomain 1 of DBPII, consistent with previous studies. Immunogenicity studies using synthetic linear peptides of the minimal epitopes determined that the 3C9 epitope, but not the 3D10 epitope, could induce functionally inhibitory anti-DBPII antibodies. Therefore, the highly conserved binding-inhibitory 3C9 epitope offers the potential as a component in a broadly inhibitory, strain-transcending DBP subunit vaccine.

IMPORTANCE Vivax malaria is the second leading cause of malaria worldwide and the major cause of non-African malaria. Unfortunately, efforts to develop antimalarial vaccines specifically targeting Plasmodium vivax have been largely neglected, and few candidates have progressed into clinical trials. The Duffy binding protein is considered a leading blood-stage vaccine candidate because this ligand’s recognition of the Duffy blood group reticulocyte surface receptor is considered essential for infection. This study identifies a new target epitope on the ligand’s surface that may serve as the target of vaccine-induced binding-inhibitory antibody (BIAb). Understanding the potential targets of vaccine protection will be important for development of an effective vaccine.