DGraph Clusters Flaviviruses and β-Coronaviruses According to Their Hosts, Disease Type, and Human Cell Receptors

Beyond mutations: Accounting for quantitative changes in the analysis of protein evolution

Molecular phylogenetic research has relied on the analysis of the coding sequences by genes or of the amino acid sequences by the encoded proteins. Enumerating the numbers of mismatches, being indicators of mutation, has been central to pertinent algorithms. Specific amino acids possess quantifiable characteristics that enable the conversion from "words" (strings of letters denoting amino acids or bases) to "waves" (strings of quantitative values representing the physico-chemical properties) or to matrices (coordinates representing the positions in a comprehensive property space). The application of such numerical representations to evolutionary analysis takes into account not only the occurrence of mutations but also their properties as influences that drive speciation, because selective pressures favor certain mutations over others, and this predilection is represented in the characteristics of the incorporated amino acids (it is not born out solely by the mismatches). Besides being more discriminating sources for tree-generating algorithms than match/mismatch, the number strings can be examined for overall similarity with average mutual information, autocorrelation, and fractal dimension. Bivariate wavelet analysis aids in distinguishing hypermutable versus conserved domains of the protein. The matrix depiction is readily subjected to comparisons of distances, and it allows the generation of heat maps or graphs. This analysis preserves the accepted taxa order where tree construction with standard approaches yields conflicting results (for the protein S100A6). It also aids hypothesis generation about the origin of mitochondrial proteins. These analytical algorithms have been automated in R and are applicable to various processes that are describable in matrix format.

Displaying alphavirus physicochemical consensus antigens on immunogenic liposomes enhances antibody elicitation in mice

Cobalt-porphyrin phospholipid displays recombinant protein antigens on liposome surfaces via antigen polyhistidine-tag (His-tag), and when combined with monophosphorylated lipid A and QS-21 yields the "CPQ" vaccine adjuvant system. In this proof of principle study, CPQ was used to generate vaccine prototypes that elicited antibodies for two different alphaviruses (AV). Mice were immunized with computationally designed, His-tagged, physicochemical property consensus (PCPcon) protein antigens representing the variable B-domain of the envelope protein 2 (E2) from the serotype specific Venezuelan Equine Encephalitis Virus (VEEVcon) or a broad-spectrum AV-antigen termed EVCcon. The CPQ adjuvant enhanced the antigenicity of both proteins without eliciting detectable anti-His-tag antibodies. Antibodies elicited from mice immunized with antigens admixed with CPQ showed orders-of-magnitude higher levels of antigen-specific IgG compared to alternative control adjuvants. The ELISA results correlated with antiviral activity against VEEV strain TC83 and more weakly to Chikungunya virus 118/25. Thus, display of E.coli-produced His-tagged E2 protein segments on the surface of immunogenic liposomes elicits high levels of antigen-specific and AV neutralizing antibodies in mice with vaccination, while facilitating vaccine preparation and providing dose-sparing potential.

Identifying Similar Allergens and Potentially Cross-Reacting Areas Using Structural Database of Allergenic Proteins (SDAP) Tools and D-Graph

The Structural Database of Allergenic Proteins (SDAP) provides rapid search tools to identify similarities among allergens, their IgE epitopes, and to determine the potential allergenicity of any novel protein. Many labs have identified IgE-binding proteins and their antibody binding or T cell epitopes using dotspots or microarrays. This chapter describes how to determine the relationship of these proteins and peptides to known allergens using the tools implemented in SDAP. One can also search with these smaller peptide similarity search tool implemented in SDAP to find similar sequences with low property distance (PD) values in the over 1500 sequences of allergens. The sequences can be compared by mapping on the surface of the protein structures provided for nearly all the allergens in SDAP. Once the user has a unique list of similar sequences, they can be graphed in 2D according to interpeptide PD values calculated automatically by the D-graph program. This chapter provides a step-by-step description of how to do this, starting from a protein similar to the Ole e 1 (olive pollen) allergen family.

The updated Structural Database of Allergenic Proteins (SDAP 2.0) provides 3D models for allergens and incorporated bioinformatics tools

Background

Allergenic proteins can cause IgE-mediated adverse reactions in sensitized individuals. Although the sequences of many allergenic proteins have been identified, bioinformatics data analysis with advanced computational methods and modeling is needed to identify the basis for IgE binding and cross-reactivity.

Objective

We aim to present the features and use of the updated Structural Database of Allergenic Proteins 2.0 (SDAP 2.0) webserver, a unique, publicly available resource to compare allergens using specially designed computational tools and new high-quality 3-D models for most known allergens.

Methods

Previously developed and novel software tools for identifying cross-reactive allergens using sequence and structure similarity are implemented in SDAP 2.0. A comprehensive set of high-quality 3-D models of most allergens was generated with the state-of-the-art AlphaFold 2 software. A graphics tool enables the interactive visualization of IgE epitopes on experimentally determined and modeled 3-D structures.

Results

A user can search for allergens similar to a given input sequence with the FASTA algorithm or the window-based World Health Organization/International Union of Immunological Societies (WHO/IUIS) guidelines on safety concerns of novel food products. Peptides similar to known IgE epitopes can be identified with the property distance tool and conformational epitopes by the Cross-React method. The updated database contains 1657 manually curated sequences including all allergens from the IUIS database, 334 experimentally determined X-ray or NMR structures, and 1565 3-D models. Each allergen/isoallergen is classified according to its protein family.

Conclusions

SDAP provides access to the steadily increasing information on allergenic structures and epitopes with integrated bioinformatics tools to identify and analyze their similarities. In addition to serving the research and regulatory community, it provides clinicians with tools to identify potential coallergies in a sensitive patient and can help companies to design hypoallergenic foods and immunotherapies.

CrossDome: an interactive R package to predict cross-reactivity risk using immunopeptidomics databases

T-cell-based immunotherapies hold tremendous potential in the fight against cancer, thanks to their capacity to specifically targeting diseased cells. Nevertheless, this potential has been tempered with safety concerns regarding the possible recognition of unknown off-targets displayed by healthy cells. In a notorious example, engineered T-cells specific to MAGEA3 (EVDPIGHLY) also recognized a TITIN-derived peptide (ESDPIVAQY) expressed by cardiac cells, inducing lethal damage in melanoma patients. Such off-target toxicity has been related to T-cell cross-reactivity induced by molecular mimicry. In this context, there is growing interest in developing the means to avoid off-target toxicity, and to provide safer immunotherapy products. To this end, we present CrossDome, a multi-omics suite to predict the off-target toxicity risk of T-cell-based immunotherapies. Our suite provides two alternative protocols, i) a peptide-centered prediction, or ii) a TCR-centered prediction. As proof-of-principle, we evaluate our approach using 16 well-known cross-reactivity cases involving cancer-associated antigens. With CrossDome, the TITIN-derived peptide was predicted at the 99+ percentile rank among 36,000 scored candidates (p-value < 0.001). In addition, off-targets for all the 16 known cases were predicted within the top ranges of relatedness score on a Monte Carlo simulation with over 5 million putative peptide pairs, allowing us to determine a cut-off p-value for off-target toxicity risk. We also implemented a penalty system based on TCR hotspots, named contact map (CM). This TCR-centered approach improved upon the peptide-centered prediction on the MAGEA3-TITIN screening (e.g., from 27th to 6th, out of 36,000 ranked peptides). Next, we used an extended dataset of experimentally-determined cross-reactive peptides to evaluate alternative CrossDome protocols. The level of enrichment of validated cases among top 50 best-scored peptides was 63% for the peptide-centered protocol, and up to 82% for the TCR-centered protocol. Finally, we performed functional characterization of top ranking candidates, by integrating expression data, HLA binding, and immunogenicity predictions. CrossDome was designed as an R package for easy integration with antigen discovery pipelines, and an interactive web interface for users without coding experience. CrossDome is under active development, and it is available at https://github.com/AntunesLab/crossdome.

PCP consensus protein/peptide alphavirus antigens stimulate broad spectrum neutralizing antibodies

Vaccines based on proteins and peptides may be safer and if calculated based on many sequences, more broad-spectrum than those designed based on single strains. Physicochemical Property Consensus (PCP_con) alphavirus (AV) antigens from the B-domain of the E2 envelope protein were designed, synthesized recombinantly and shown to be immunogenic (i.e. sera after inoculation detected the antigen in dotspots and ELISA). Antibodies in sera after inoculation with B-region antigens based on individual AV species (eastern or Venezuelan equine encephalitis (EEEV_con, VEEV_con), or chikungunya (CHIKV_con) bound only their cognate protein, while those designed against multiple species (Mosaik_con and EVC_con) recognized all three serotype specific antigens. The VEEV_con and EEEV_con sera only showed antiviral activity against their related strains (in plaque reduction neutralization assays (PRNT_50/80). Peptides designed to surface exposed areas of the E2-A-domain of CHIKV_con were added to CHIKV_con inocula to provide anti-CHIKV antibodies. EVC_con, based on three different alphavirus species, combined with E2-A-domain peptides from AllAV_con, a PCPcon of 24 diverse AV, generated broad spectrum, antiviral antibodies against VEEV, EEEV and CHIKV, AV with less than 35% amino acid identity to each other (>65% diversity). This is a promising start to a molecularly defined vaccine against all AV. Further study with these antigens can illuminate what areas are most important for a robust immune response, resistant to mutations in rapidly evolving viruses. The validated computational methods can also be used to design broad spectrum antigens against many other pathogen families.

Still SDAPing Along: 20 Years of the Structural Database of Allergenic Proteins

The introduction of plant extracts to mitigate the symptoms of “hay fever”, about a century ago, led to discoveries beginning sixty years ago on determining the sequences and eventually structures of allergenic proteins. As more proteins were cloned, there was a need to rapidly identify and categorize those with significant similarity to known allergens. The Structural Database of Allergenic Proteins (SDAP) was created at the beginning of the 21st century as the first cross-referenced website to allow rapid overview of the structures and sequences of allergenic proteins. SDAP provides a way to identify sequence and functional similarities between these proteins, despite the complex nomenclature system based on the Latin names of their different sources. A rapid FASTA search simplifies grouping allergens from the same structural or functional family. SDAP also provides an overview of the rapidly expanding literature on the sequence, structure and epitopes of allergenic proteins and a way to estimate the potential allergenicity of novel proteins based on rules provided by the IUIS. Twenty years and a pandemic later, the list of allergenic proteins and their attributes continues to grow. SDAP is expanding and improving to allow rapid access to all this information.

Regional and temporal coordinated mutation patterns in SARS-CoV-2 spike protein revealed by a clustering and network analysis

SARS-CoV-2 has steadily mutated during its spread to > 300 million people throughout the world. The WHO has designated strains with certain mutations, "variants of concern" (VOC), as they may have higher infectivity and/or resist neutralization by antibodies in sera of vaccinated individuals and convalescent patients. Methods to detect regionally emerging VOC are needed to guide treatment and vaccine design. Cluster and network analysis was applied to over 1.2 million sequences of the SARS-CoV-2 spike protein from 36 countries in the GISAID database. While some mutations rapidly spread throughout the world, regionally specific groups of variants were identified. Strains circulating in each country contained different sets of high frequency mutations, many of which were known VOCs. Mutations within clusters increased in frequency simultaneously. Low frequency, but highly correlated mutations detected by the method could signal emerging VOCs, especially if they occur at higher frequency in other regions. An automated version of our method to find high frequency mutations in a set of SARS-COV-2 spike sequences is available online at http://curie.utmb.edu/SAR.html .

Synthetic proteins for COVID-19 diagnostics

There is an urgent need for inexpensive, rapid and specific antigen-based assays to test for vaccine efficacy and detect infection with SARS-CoV-2 and its variants. We have identified a small, synthetic protein (JS7), representing a region of maximum variability within the receptor binding domain (RBD), which binds antibodies in sera from nine patients with PCR-verified COVID-19 of varying severity. Antibodies binding to either JS7 or the SARS-CoV-2 recombinant RBD, as well as those that disrupt binding between a fragment of the ACE2 receptor and the RBD, are proportional to disease severity and clinical outcome. Binding to JS7 was inhibited by linear peptides from the RBD interface with ACE2. Variants of JS7, such as E484K or N501Y, can be quickly synthesized in pure form in large quantities by automated methods. JS7 and related synthetic antigens can provide a basis for specific diagnostics for SARS-CoV-2 infections.