Exploiting glycan topography for computational design of Env glycoprotein antigenicity

Broadly neutralizing antibodies for HIV prevention: a comprehensive review and future perspectives

SUMMARYThe human immunodeficiency virus (HIV) epidemic remains a formidable global health concern, with 39 million people living with the virus and 1.3 million new infections reported in 2022. Despite anti-retroviral therapy's effectiveness in pre-exposure prophylaxis, its global adoption is limited. Broadly neutralizing antibodies (bNAbs) offer an alternative strategy for HIV prevention through passive immunization. Historically, passive immunization has been efficacious in the treatment of various diseases ranging from oncology to infectious diseases. Early clinical trials suggest bNAbs are safe, tolerable, and capable of reducing HIV RNA levels. Although challenges such as bNAb resistance have been noted in phase I trials, ongoing research aims to assess the additive or synergistic benefits of combining multiple bNAbs. Researchers are exploring bispecific and trispecific antibodies, and fragment crystallizable region modifications to augment antibody efficacy and half-life. Moreover, the potential of other antibody isotypes like IgG3 and IgA is under investigation. While promising, the application of bNAbs faces economic and logistical barriers. High manufacturing costs, particularly in resource-limited settings, and logistical challenges like cold-chain requirements pose obstacles. Preliminary studies suggest cost-effectiveness, although this is contingent on various factors like efficacy and distribution. Technological advancements and strategic partnerships may mitigate some challenges, but issues like molecular aggregation remain. The World Health Organization has provided preferred product characteristics for bNAbs, focusing on optimizing their efficacy, safety, and accessibility. The integration of bNAbs in HIV prophylaxis necessitates a multi-faceted approach, considering economic, logistical, and scientific variables. This review comprehensively covers the historical context, current advancements, and future avenues of bNAbs in HIV prevention.

Decoding glycosylation potential from protein structure across human glycoproteins with a multi-view recurrent neural network

Glycosylation is described as a non-templated biosynthesis. Yet, the template-free premise is antithetical to the observation that different N-glycans are consistently placed at specific sites. It has been proposed that glycosite-proximal protein structures could constrain glycosylation and explain the observed microheterogeneity. Using site-specific glycosylation data, we trained a hybrid neural network to parse glycosites (recurrent neural network) and match them to feasible N-glycosylation events (graph neural network). From glycosite-flanking sequences, the algorithm predicts most human N-glycosylation events documented in the GlyConnect database and proposed structures corresponding to observed monosaccharide composition of the glycans at these sites. The algorithm also recapitulated glycosylation in Enhanced Aromatic Sequons, SARS-CoV-2 spike, and IgG3 variants, thus demonstrating the ability of the algorithm to predict both glycan structure and abundance. Thus, protein structure constrains glycosylation, and the neural network enables predictive in silico glycosylation of uncharacterized or novel protein sequences and genetic variants.

ppmFixer: a mass error adjustment for pGlyco3.0 to correct near-isobaric mismatches

Modern glycoproteomics experiments require the use of search engines due to the generation of countless spectra. While these tools are valuable, manual validation of search engine results is often required for detailed analysis of glycopeptides as false-discovery rates are often not reliable for glycopeptide data. Near-isobaric mismatches are a common source of misidentifications for the popular glycopeptide-focused search engine pGlyco3.0, and in this technical note we share a strategy and script that improves the accuracy of the search utilizing two manually validated datasets of the glycoproteins CD16a and HIV-1 Env as proof-of-principle.

The applications of machine learning in HIV neutralizing antibodies research-A systematic review

Machine learning algorithms play an essential role in bioinformatics and allow exploring the vast and noisy biological data in unrivaled ways. This paper is a systematic review of the applications of machine learning in the study of HIV neutralizing antibodies. This significant and vast research domain can pave the way to novel treatments and to a vaccine. We selected the relevant papers by investigating the available literature from the Web of Science and PubMed databases in the last decade. The computational methods are applied in neutralization potency prediction, neutralization span prediction against multiple viral strains, antibody-virus binding sites detection, enhanced antibodies design, and the study of the antibody-induced immune response. These methods are viewed from multiple angles spanning data processing, model description, feature selection, evaluation, and sometimes paper comparisons. The algorithms are diverse and include supervised, unsupervised, and generative types. Both classical machine learning and modern deep learning were taken into account. The review ends with our ideas regarding future research directions and challenges.

Prediction of HIV sensitivity to monoclonal antibodies using aminoacid sequences and deep learning

MOTIVATION

Knowing the sensitivity of a viral strain versus a monoclonal antibody is of interest for HIV vaccine development and therapy. The HIV strains vary in their resistance to antibodies, and the accurate prediction of virus-antibody sensitivity can be used to find potent antibody combinations that broadly neutralize multiple and diverse HIV strains. Sensitivity prediction can be combined with other methods such as generative algorithms to design novel antibodies in silico or with feature selection to uncover the sites of interest in the sequence. However, these tools are limited in the absence of in silico accurate prediction methods.

RESULTS

Our method leverages the CATNAP dataset, probably the most comprehensive collection of HIV-antibodies assays, and predicts the antibody-virus sensitivity in the form of binary classification. The methods proposed by others focus primarily on analyzing the virus sequences. However, our article demonstrates the advantages gained by modeling the antibody-virus sensitivity as a function of both virus and antibody sequences. The input is formed by the virus envelope and the antibody variable region aminoacid sequences. No structural features are required, which makes our system very practical, given that sequence data is more common than structures. We compare with two other state-of-the-art methods that leverage the same dataset and use sequence data only. Our approach, based on neuronal networks and transfer learning, measures increased predictive performance as measured on a set of 31 specific broadly neutralizing antibodies.

AVAILABILITY AND IMPLEMENTATION

https://github.com/vlad-danaila/deep_hiv_ab_pred/tree/fc-att-fix.

Analysis of Viral Spike Protein N-Glycosylation Using Ultraviolet Photodissociation Mass Spectrometry

Characterization of protein glycosylation by tandem mass spectrometry remains challenging owing to the vast diversity of oligosaccharides bound to proteins, the variation in monosaccharide linkage patterns, and the lability of the linkage between the glycan and protein. Here, we have adapted an HCD-triggered-ultraviolet photodissociation (UVPD) approach for the simultaneous localization of glycosites and full characterization of both glycan compositions and intersaccharide linkages, the latter provided by extensive cross-ring cleavages enabled by UVPD. The method is applied to study glycan compositions based on analysis of glycopeptides from proteolytic digestion of recombinant human coronaviruse spike proteins from SARS-CoV-2 and HKU1. UVPD reveals unique intersaccharide linkage information and is leveraged to localize N-linked glycoforms with confidence.

Post-Immune Antibodies in HIV-1 Infection in the Context of Vaccine Development: A Variety of Biological Functions and Catalytic Activities

Unlike many other viruses, HIV-1 is highly variable. The structure of the viral envelope changes as the infection progresses and is one of the biggest obstacles in developing an HIV-1 vaccine. HIV-1 infection can cause the production of various natural autoantibodies, including catalytic antibodies hydrolyzing DNA, myelin basic protein, histones, HIV-integrase, HIV-reverse transcriptase, β-casein, serum albumin, and some other natural substrates. Currently, there are various directions for the development of HIV-1 vaccines: stimulation of the immune response on the mucous membranes; induction of cytotoxic T cells, which lyse infected cells and hold back HIV-infection; immunization with recombinant Env proteins or vectors encoding Env; mRNA-based vaccines and some others. However, despite many attempts to develop an HIV-1 vaccine, none have been successful. Here we review the entire spectrum of antibodies found in HIV-infected patients, including neutralizing antibodies specific to various viral epitopes, as well as antibodies formed against various autoantigens, catalytic antibodies against autoantigens, and some viral proteins. We consider various promising targets for developing a vaccine that will not produce unwanted antibodies in vaccinated patients. In addition, we review common problems in the development of a vaccine against HIV-1.

Engineering well-expressed, V2-immunofocusing HIV-1 envelope glycoprotein membrane trimers for use in heterologous prime-boost vaccine regimens

HIV-1 vaccine immunofocusing strategies may be able to induce broadly-reactive neutralizing antibodies (NAbs). Here, we engineered a panel of diverse, membrane-resident native HIV-1 trimers vulnerable to two broad targets-the V2 apex and fusion peptide (FP). Selection criteria included i) high expression and ii) infectious function, so that trimer neutralization sensitivity can be profiled in pseudovirus (PV) assays. Initially, we boosted the expression of 17 candidate trimers by truncating gp41 and introducing a gp120-gp41 SOS disulfide to prevent gp120 shedding. "Repairs" were made to fill glycan holes and eliminate other strain-specific aberrations. A new neutralization assay allowed PV infection when our standard assay was insufficient. Trimers with exposed V3 loops, a target of non-NAbs, were discarded. To try to increase V2-sensitivity, we removed clashing glycans and modified the C-strand. Notably, a D167N mutation improved V2-sensitivity in several cases. Glycopeptide analysis of JR-FL trimers revealed near complete sequon occupation and that filling the N197 glycan hole was well-tolerated. In contrast, sequon optimization and inserting/removing glycans at other positions frequently had global "ripple" effects on glycan maturation and sequon occupation throughout the gp120 outer domain and gp41. V2 MAb CH01 selectively bound to trimers with small high mannose glycans near the base of the V1 loop, thereby avoiding clashes. Knocking in a rare N49 glycan was found to perturb gp41 glycans, increasing FP NAb sensitivity-and sometimes improving expression. Finally, a biophysical analysis of VLPs revealed that i) ~25% of particles bear Env spikes, ii) spontaneous particle budding is high and only increases 4-fold upon Gag transfection, and iii) Env+ particles express ~30-40 spikes. Taken together, we identified 7 diverse trimers with a range of sensitivities to two targets to allow rigorous testing of immunofocusing vaccine concepts.

Major Scientific Hurdles in HIV Vaccine Development: Historical Perspective and Future Directions

Following the discovery of HIV as a causative agent of AIDS, the expectation was to rapidly develop a vaccine; but thirty years later, we still do not have a licensed vaccine. Progress has been hindered by the extensive genetic variability of HIV and our limited understanding of immune responses required to protect against HIV acquisition. Nonetheless, valuable knowledge accrued from numerous basic and translational science research studies and vaccine trials has provided insight into the structural biology of the virus, immunogen design and novel vaccine delivery systems that will likely constitute an effective vaccine. Furthermore, stakeholders now appreciate the daunting scientific challenges of developing an effective HIV vaccine, hence the increased advocacy for collaborative efforts among academic research scientists, governments, pharmaceutical industry, philanthropy, and regulatory entities. In this review, we highlight the history of HIV vaccine development efforts, highlighting major challenges and future directions.

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

The SARS-CoV-2 betacoronavirus uses its highly glycosylated trimeric Spike protein to bind to the cell surface receptor angiotensin converting enzyme 2 (ACE2) glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer Spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatics analyses of natural variants and with existing 3D structures of both glycoproteins to generate molecular dynamics simulations of each glycoprotein both alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation. Taken together, these data can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

The current COVID-19 pandemic is caused by the SARS-CoV-2 betacoronavirus, which utilizes its highly glycosylated trimeric Spike protein to bind to the cell surface receptor ACE2 glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer Spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatic analyses of natural variants and with existing 3D-structures of both glycoproteins to generate molecular dynamics simulations of each glycoprotein alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation that, taken together, can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.

Glycomics and glycoproteomics of viruses: Mass spectrometry applications and insights toward structure-function relationships

The advancement of viral glycomics has paralleled that of the mass spectrometry glycomics toolbox. In some regard the glycoproteins studied have provided the impetus for this advancement. Viral proteins are often highly glycosylated, especially those targeted by the host immune system. Glycosylation tends to be dynamic over time as viruses propagate in host populations leading to increased number of and/or "movement" of glycosylation sites in response to the immune system and other pressures. This relationship can lead to highly glycosylated, difficult to analyze glycoproteins that challenge the capabilities of modern mass spectrometry. In this review, we briefly discuss five general areas where glycosylation is important in the viral niche and how mass spectrometry has been used to reveal key information regarding structure-function relationships between viral glycoproteins and host cells. We describe the recent past and current glycomics toolbox used in these analyses and give examples of how the requirement to analyze these complex glycoproteins has provided the incentive for some advances seen in glycomics mass spectrometry. A general overview of viral glycomics, special cases, mass spectrometry methods and work-flows, informatics and complementary chemical techniques currently used are discussed. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.

Vulnerabilities in coronavirus glycan shields despite extensive glycosylation

Severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronaviruses (CoVs) are zoonotic pathogens with high fatality rates and pandemic potential. Vaccine development focuses on the principal target of the neutralizing humoral immune response, the spike (S) glycoprotein. Coronavirus S proteins are extensively glycosylated, encoding around 66-87 N-linked glycosylation sites per trimeric spike. Here, we reveal a specific area of high glycan density on MERS S that results in the formation of oligomannose-type glycan clusters, which were absent on SARS and HKU1 CoVs. We provide a comparison of the global glycan density of coronavirus spikes with other viral proteins including HIV-1 envelope, Lassa virus glycoprotein complex, and influenza hemagglutinin, where glycosylation plays a known role in shielding immunogenic epitopes. Overall, our data reveal how organisation of glycosylation across class I viral fusion proteins influence not only individual glycan compositions but also the immunological pressure across the protein surface.

Glycopeptide epitope facilitates HIV-1 envelope specific humoral immune responses by eliciting T cell help

The inherent molecular complexity of human pathogens requires that mammals evolved an adaptive immune system equipped to handle presentation of non-conventional MHC ligands derived from disease-causing agents, such as HIV-1 envelope (Env) glycoprotein. Here, we report that a CD4⁺ T cell repertoire recognizes a glycopeptide epitope on gp120 presented by MHCII pathway. This glycopeptide is strongly immunogenic in eliciting glycan-dependent cellular and humoral immune responses. The glycopeptide specific CD4⁺ T cells display a prominent feature of Th2 and Th17 differentiation and exert high efficacy and potency to help Env trimer humoral immune responses. Glycopeptide-induced CD4⁺ T cell response prior to Env trimer immunization elicits neutralizing antibody development and production of antibodies facilitating uptake of immunogens by antigen-presenting cells. Our identification of gp120 glycopeptide–induced, T cell–specific immune responses offers a foundation for developing future knowledge-based vaccines that elicit strong and long-lasting protective immune responses against HIV-1 infection.

T cells recognize peptide antigens presented in the context of MHC but can additionally recognize non-conventional ligands. Here the authors show T cells specific for a HIV-1 associated glycopeptide antigen presented by MHC class II help envelope (Env) trimer induced humoral immune responses.

Proteomics-based screening of the endothelial heparan sulfate interactome reveals that C-type lectin 14a (CLEC14A) is a heparin-binding protein

Animal cells express heparan sulfate proteoglycans that perform many important cellular functions by way of heparan sulfate-protein interactions. The identification of membrane heparan sulfate-binding proteins is challenging because of their low abundance and the need for extensive enrichment. Here, we report a proteomics workflow for the identification and characterization of membrane-anchored and extracellular proteins that bind heparan sulfate. The technique is based on limited proteolysis of live cells in the absence of denaturation and fixation, heparin-affinity chromatography, and high-resolution LC-MS/MS, and we designate it LPHAMS. Application of LPHAMS to U937 monocytic and primary murine and human endothelial cells identified 55 plasma membrane, extracellular matrix, and soluble secreted proteins, including many previously unidentified heparin-binding proteins. The method also facilitated the mapping of the heparin-binding domains, making it possible to predict the location of the heparin-binding site. To validate the discovery feature of LPHAMS, we characterized one of the newly-discovered heparin-binding proteins, C-type lectin 14a (CLEC14A), a member of the C-type lectin family that modulates angiogenesis. We found that the C-type lectin domain of CLEC14A binds one-to-one to heparin with nanomolar affinity, and using molecular modeling and mutagenesis, we mapped its heparin-binding site. CLEC14A physically interacted with other glycosaminoglycans, including endothelial heparan sulfate and chondroitin sulfate E, but not with neutral or sialylated oligosaccharides. The LPHAMS technique should be applicable to other cells and glycans and provides a way to expand the repertoire of glycan-binding proteins for further study.

Predicting the broadly neutralizing antibody susceptibility of the HIV reservoir

Broadly neutralizing antibodies (bNAbs) against HIV-1 are under evaluation for both prevention and therapy. HIV-1 sequence diversity observed in most HIV-infected individuals and archived variations in critical bNAb epitopes present a major challenge for the clinical application of bNAbs, as preexistent resistant viral strains can emerge, resulting in bNAb failure to control HIV. In order to identify viral resistance in patients prior to antibody therapy and to guide the selection of effective bNAb combination regimens, we developed what we believe to be a novel Bayesian machine-learning model that uses HIV-1 envelope protein sequences and foremost approximated glycan occupancy information as variables to quantitatively predict the half-maximal inhibitory concentrations (IC50) of 126 neutralizing antibodies against a variety of cross clade viruses. We then applied this model to peripheral blood mononuclear cell-derived proviral Env sequences from 25 HIV-1-infected individuals mapping the landscape of neutralization resistance within each individual's reservoir and determined the predicted ideal bNAb combination to achieve 100% neutralization at IC50 values <1 μg/ml. Furthermore, predicted cellular viral reservoir neutralization signatures of individuals before an analytical antiretroviral treatment interruption were consistent with the measured neutralization susceptibilities of the respective plasma rebound viruses, validating our model as a potentially novel tool to facilitate the advancement of bNAbs into the clinic.

Glycosylation of viral surface proteins probed by mass spectrometry

Glycosylation is a common and biologically significant post-translational modification that is found on numerous virus surface proteins (VSPs). Many of these glycans affect virulence through modulating virus receptor binding, masking antigenic sites, or by stimulating the host immune response. Mass spectrometry (MS) has arisen as a pivotal technique for the characterization of VSP glycosylation. This review will cover how MS-based analyses, such as released glycan profiles, glycan site localization, site-occupancy, and site-specific heterogeneity, are being utilized to map VSP glycosylation. Furthermore, this review will provide information on how MS glycoprofiling data are being used in conjunction with molecular and structural experiments to provide a better understanding of the role of specific glycans in VSP function.

Prediction of VRC01 neutralization sensitivity by HIV-1 gp160 sequence features

The broadly neutralizing antibody (bnAb) VRC01 is being evaluated for its efficacy to prevent HIV-1 infection in the Antibody Mediated Prevention (AMP) trials. A secondary objective of AMP utilizes sieve analysis to investigate how VRC01 prevention efficacy (PE) varies with HIV-1 envelope (Env) amino acid (AA) sequence features. An exhaustive analysis that tests how PE depends on every AA feature with sufficient variation would have low statistical power. To design an adequately powered primary sieve analysis for AMP, we modeled VRC01 neutralization as a function of Env AA sequence features of 611 HIV-1 gp160 pseudoviruses from the CATNAP database, with objectives: (1) to develop models that best predict the neutralization readouts; and (2) to rank AA features by their predictive importance with classification and regression methods. The dataset was split in half, and machine learning algorithms were applied to each half, each analyzed separately using cross-validation and hold-out validation. We selected Super Learner, a nonparametric ensemble-based cross-validated learning method, for advancement to the primary sieve analysis. This method predicted the dichotomous resistance outcome of whether the IC50 neutralization titer of VRC01 for a given Env pseudovirus is right-censored (indicating resistance) with an average validated AUC of 0.868 across the two hold-out datasets. Quantitative log IC50 was predicted with an average validated R2 of 0.355. Features predicting neutralization sensitivity or resistance included 26 surface-accessible residues in the VRC01 and CD4 binding footprints, the length of gp120, the length of Env, the number of cysteines in gp120, the number of cysteines in Env, and 4 potential N-linked glycosylation sites; the top features will be advanced to the primary sieve analysis. This modeling framework may also inform the study of VRC01 in the treatment of HIV-infected persons.

Immune Correlate-Guided HIV Vaccine Design

Although vaccines have been successfully developed against several pathogens, designing an effective vaccine to protect against human immunodeficiency virus (HIV) has remained an intractable challenge. To address this, the research community has looked to human and non-human primate studies to understand the correlates of protective immunity, based on which a targeted vaccine strategy may be designed. Two distinct approaches, focused on different immune correlates of protection, have emerged. The first focuses on structure-based design of HIV envelope immunogens that are able to induce antibodies that neutralize the virus. The second focuses on strategies aimed at driving non-neutralizing polyclonal and polyfunctional antibodies that engage other arms of immunity to clear the virus. Here we review these two different vaccine design strategies and posit that ultimately the convergence of these two efforts will likely be necessary for the development of a globally protective HIV vaccine.

Structural Rearrangements Maintain the Glycan Shield of an HIV-1 Envelope Trimer After the Loss of a Glycan

The HIV-1 envelope (Env) glycoprotein is the primary target of the humoral immune response and a critical vaccine candidate. However, Env is densely glycosylated and thereby substantially protected from neutralisation. Importantly, glycan N301 shields V3 loop and CD4 binding site epitopes from neutralising antibodies. Here, we use molecular dynamics techniques to evaluate the structural rearrangements that maintain the protective qualities of the glycan shield after the loss of glycan N301. We examined a naturally occurring subtype C isolate and its N301A mutant; the mutant not only remained protected against neutralising antibodies targeting underlying epitopes, but also exhibited an increased resistance to the VRC01 class of broadly neutralising antibodies. Analysis of this mutant revealed several glycans that were responsible, independently or through synergy, for the neutralisation resistance of the mutant. These data provide detailed insight into the glycan shield’s ability to compensate for the loss of a glycan, as well as the cascade of glycan movements on a protomer, starting at the point mutation, that affects the integrity of an antibody epitope located at the edge of the diminishing effect. These results present key, previously overlooked, considerations for HIV-1 Env glycan research and related vaccine studies.