Next-generation IEDB tools: a platform for epitope prediction and analysis.

The Next-Generation (NG) IEDB Tools website (https://nextgen-tools.iedb.org) provides users with a redesigned interface to many of the algorithms for epitope prediction and analysis that were originally released on the legacy IEDB Tools website. The initial release focuses on consolidation of all tools related to HLA class I epitopes (MHC binding, elution, immunogenicity, and processing), making all of these predictions accessible from a single application and allowing for their simultaneous execution with minimal user inputs. Additionally, the PEPMatch tool for identifying highly similar epitopes in a set of curated proteomes, as well as a tool for epitope clustering, are available on the site. The NG Tools site allows users to build data pipelines by sending the output of one tool as input for the next. Over the next several years, all pre-existing IEDB Tools, and any newly developed tools, will be integrated into this new site. Here we describe the philosophy behind the redesign and demonstrate the utility and productivity enhancements that are enabled by the new interface.

Influence of pH on indole-dependent heterodimeric interactions between Anopheles gambiae odorant-binding proteins OBP1 and OBP4.

Insect Odorant Binding Proteins (OBPs) constitute important components of their olfactory apparatus, as they are essential for odor recognition. OBPs undergo conformational changes upon pH change, altering their interactions with odorants. Moreover, they can form heterodimers with novel binding characteristics. Anopheles gambiae OBP1 and OBP4 were found capable of forming heterodimers possibly involved in the specific perception of the attractant indole. In order to understand how these OBPs interact in the presence of indole and to investigate the likelihood of a pH-dependent heterodimerization mechanism, the crystal structures of OBP4 at pH 4.6 and 8.5 were determined. Structural comparison to each other and with the OBP4-indole complex (3Q8I, pH 6.85) revealed a flexible N-terminus and conformational changes in the α4-loop-α5 region at acidic pH. Fluorescence competition assays showed a weak binding of indole to OBP4 that becomes further impaired at acidic pH. Additional Molecular Dynamic and Differential Scanning Calorimetry studies displayed that the influence of pH on OBP4 stability is significant compared to the modest effect of indole. Furthermore, OBP1-OBP4 heterodimeric models were generated at pH 4.5, 6.5, and 8.5, and compared concerning their interface energy and cross-correlated motions in the absence and presence of indole. The results indicate that the increase in pH may induce the stabilization of OBP4 by increasing its helicity, thereby enabling indole binding at neutral pH that further stabilizes the protein and possibly promotes the creation of a binding site for OBP1. A decrease in interface stability and loss of correlated motions upon transition to acidic pH may provoke the heterodimeric dissociation allowing indole release. Finally, we propose a potential OBP1-OBP4 heterodimer formation/disruption mechanism induced by pH change and indole binding.

IEDB-3D 2.0: Structural data analysis within the Immune Epitope Database.

The Immune Epitope Database (IEDB) catalogs T cell, B cell, and major histocompatibility complex ligand information in the context of infectious disease, allergy, autoimmunity, and transplantation. An important component of this information is three-dimensional structural data on T cell receptors, antibodies, and pairwise residue interactions between immune receptors and antigens, which we refer to as IEDB-3D. Such data is highly valuable for mechanically understanding receptor:ligand interactions. Here, we present IEDB-3D 2.0, which comprises a complete overhaul of how we obtain and present 3D structural data. A new 3D viewer experience that utilizes iCn3D has been implemented to replace outdated java-based technology. In addition, we have designed a new epitope mapping system that matches each epitope available in the IEDB with its antigen structural data. Finally, immunogenicity data retrieved from the IEDB's ImmunomeBrowser can now be used to highlight immunogenic regions of an antigen directly in iCn3D. Overall, the IEDB-3D 2.0 provides an updated tool platform to visualize epitope data cataloged in the IEDB.

Coronavirus Immunotherapeutic Consortium Database.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities. To collect these data in a consistent fashion and make it publicly available, we established the COVIC database (COVIC-DB, https://covicdb.lji.org/). This database enables systematic analysis and interpretation of this large-scale dataset by providing a comprehensive view of various features such as affinity, neutralization, in vivo protection and effector functions for each antibody. Interactive graphs enable direct comparisons of antibodies based on select functional properties. We demonstrate how the COVIC-DB can be utilized to examine relationships among antibody features, thereby guiding the design of therapeutic antibody cocktails. Database URL  https://covicdb.lji.org/.

Computational epitope binning reveals functional equivalence of sequence-divergent paratopes.

The therapeutic efficacy of a protein binder largely depends on two factors: its binding site and its binding affinity. Advances in in vitro library display screening and next-generation sequencing have enabled accelerated development of strong binders, yet identifying their binding sites still remains a major challenge. The differentiation, or "binning", of binders into different groups that recognize distinct binding sites on their target is a promising approach that facilitates high-throughput screening of binders that may show different biological activity. Here we study the extent to which the information contained in the amino acid sequences comprising a set of target-specific binders can be leveraged to bin them, inferring functional equivalence of their binding regions, or paratopes, based directly on comparison of the sequences, their modeled structures, or their modeled interactions. Using a leucine-rich repeat binding scaffold known as a "repebody" as the source of diversity in recognition against interleukin-6 (IL-6), we show that the "Epibin" approach introduced here effectively utilized structural modelling and docking to extract specificity information encoded in the repebody amino acid sequences and thereby successfully recapitulate IL-6 binding competition observed in immunoassays. Furthermore, our computational binning provided a basis for designing in vitro mutagenesis experiments to pinpoint specificity-determining residues. Finally, we demonstrate that the Epibin approach can extend to antibodies, retrospectively comparing its predictions to results from antigen-specific antibody competition studies. The study thus demonstrates the utility of modeling structure and binding from the amino acid sequences of different binders against the same target, and paves the way for larger-scale binning and analysis of entire repertoires.

Lack of evidence of significant homology of SARS-CoV-2 spike sequences to myocarditis-associated antigens.

BACKGROUND: COVID-19 mRNA vaccines have proven to be highly safe and effective. Myocarditis is an adverse event associated with mRNA vaccination, especially in young male subjects. These events are rare and, in the majority of cases, resolve quickly. As myocarditis can be driven by autoimmune responses, we wanted to determine if the SARS-CoV-2 spike protein antigen encoded in the mRNA COVID vaccines had potential cross-reactivity with auto-antigens previously associated with myocarditis. METHODS: We performed a sequence identity comparison between SARS-CoV-2 spike protein-derived peptides and myocarditis-associated antigens. We also performed a structural analysis of these antigens and the SARS-CoV-2 spike protein to identify potential discontinuous 3-D epitope similarities. FINDINGS: We found no significant enrichment in the frequency of spike-derived peptides similar to myocarditis-associated antigens as compared to several controls. INTERPRETATION: Our results do not support the notion that increased occurrence of myocarditis after SARS-CoV-2-spike vaccination is mediated by a cross-reactive adaptive immune response.

A knowledge-driven protocol for prediction of proteins of interest with an emphasis on biosynthetic pathways.

This protocol describes a stepwise process to identify proteins of interest from a query proteome derived from NGS data. We implemented this protocol on Moringa oleifera transcriptome to identify proteins involved in secondary metabolite and vitamin biosynthesis and ion transport. This knowledge-driven protocol identifies proteins using an integrated approach involving sensitive sequence search and evolutionary relationships. We make use of functionally important residues (FIR) specific for the query protein family identified through its homologous sequences and literature. We screen protein hits based on the clustering with true homologues through phylogenetic tree reconstruction complemented with the FIR mapping. The protocol was validated for the protein hits through qRT-PCR and transcriptome quantification. Our protocol demonstrated a higher specificity as compared to other methods, particularly in distinguishing cross-family hits. This protocol was effective in transcriptome data analysis of M. oleifera as described in Pasha et al.•Knowledge-driven protocol to identify secondary metabolite synthesizing protein in a highly specific manner.•Use of functionally important residues for screening of true hits.•Beneficial for metabolite pathway reconstruction in any (species, metagenomics) NGS data.

Dataset for the combined transcriptome assembly of M. oleifera and functional annotation.

In this paper, we present the data acquired during transcriptome analysis of the plant Moringa oleifera [1] from five different tissues (root, stem, leaf, flower and seed) by RNA sequencing. A total of 271 million reads were assembled with an N50 of 2094 bp. The combined transcriptome was assessed for transcript abundance across five tissues. The protein coding genes identified from the transcripts were annotated and used for orthology analysis. Further, enzymes involved in the biosynthesis of select medicinally important secondary metabolites, vitamins and ion transporters were identified and their expression levels across tissues were examined. The data generated by RNA sequencing has been deposited to NCBI public repository under the accession number PRJNA394193 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA394193).

The transcriptome enables the identification of candidate genes behind medicinal value of Drumstick tree (Moringa oleifera).

Moringa oleifera is a plant well-known for its nutrition value, drought resistance and medicinal properties. cDNA libraries from five different tissues (leaf, root, stem, seed and flower) of M. oleifera cultivar Bhagya were generated and sequenced. We developed a bioinformatics pipeline to assemble transcriptome, along with the previously published M. oleifera genome, to predict 17,148 gene models. Few candidate genes related to biosynthesis of secondary metabolites, vitamins and ion transporters were identified. Expressions were further confirmed by real-time quantitative PCR experiments for few promising leads. Quantitative estimation of metabolites, as well as elemental analysis, was also carried out to support our observations. Enzymes in the biosynthesis of vitamins and metabolites like quercetin and kaempferol are highly expressed in leaves, flowers and seeds. The expression of iron transporters and calcium storage proteins were observed in root and leaves. In general, leaves retain the highest amount of small molecules of interest.

Vaccination and immunization strategies to design Aedes aegypti salivary protein based subunit vaccine tackling Flavivirus infection.

Flavivirus causes arthropod-borne severe diseases that sometimes lead to the death. The Flavivirus species including Dengue virus, Zika virus and yellow fever virus are transmitted by the bite of Aedes mosquitoes. All these viral species target the people living in their respective endemic zone causing a high mortality rate. Recent studies show that immune factors present in the Ae. aegypti saliva is the hidden culprit promoting blood meal collection, suppressing host immune molecules and promoting disease establishment. This study was designed to develop a subunit vaccine using Aedes mosquito salivary proteins targeting the aforementioned Flaviviruses. Subunit vaccine was designed very precisely by combining the immunogenic B-cell epitope with CTL and HTL epitopes and also suitable adjuvant and linkers. Immunogenicity, allergenicity and physiochemical characterization were also performed for scientific validation. Molecular docking and molecular dynamics simulations studies were carried out to confirm the stable affinity between the vaccine protein (3D) and TLR3 receptor. At last, in silico cloning was executed to get the subunit vaccine restriction clone into pET28a vectro to express it in microbial expression system. Additionally, this study warrants the experimental evaluation for the validation purposes.

Investigating the effect of key mutations on the conformational dynamics of toll-like receptor dimers through molecular dynamics simulations and protein structure networks.

The Toll-like receptors (TLRs) are critical components of the innate immune system due to their ability to detect conserved pathogen-associated molecular patterns, present in bacteria, viruses, and other microorganisms. Ligand detection by TLRs leads to a signaling cascade, mediated by interactions among TIR domains present in the receptors, the bridging adaptors and sorting adaptors. The BB loop is a highly conserved region present in the TIR domain and is crucial for mediating interactions among TIR domain-containing proteins. Mutations in the BB loop of the Toll-like receptors, such as the A795P mutation in TLR3 and the P712H mutation (Lpsd mutation) in TLR4, have been reported to disrupt or alter downstream signaling. While the phenotypic effect of these mutations is known, the underlying effect of these mutations on the structure, dynamics and interactions with other TIR domain-containing proteins is not well understood. Here, we have attempted to investigate the effect of the BB loop mutations on the dimer form of TLRs, using TLR2 and TLR3 as case studies. Our results based on molecular dynamics simulations, protein-protein interaction analyses and protein structure network analyses highlight significant differences between the dimer interfaces of the wild-type and mutant forms and provide a logical reasoning for the effect of these mutations on adaptor binding to TLRs. Furthermore, it also leads us to propose a hypothesis for the differential requirement of signaling and bridging adaptors by TLRs. This could aid in further understanding of the mechanisms governing such signaling pathways.

Probing subtle conformational changes induced by phosphorylation and point mutations in the TIR domains of TLR2 and TLR3.

Extensive research performed on Toll-like receptor (TLR) signaling has identified residues in the Toll/interleukin-1 receptor (TIR) domains that are essential for its proper functioning. Among these residues, those in BB loop are particularly significant as single amino acid mutations in this region can cause drastic changes in downstream signaling. However, while the effect of these mutations on the function is well studied (like the P681H mutation in TLR2, the A795P mutation in TLR3, and the P714H mutation in TLR4), their influence on the dynamics and inter-residue networks is not well understood. The effects of local perturbations induced by these mutations could propagate throughout the TIR domain, influencing interactions with other TIR domain-containing proteins. The identification of these subtle changes in inter-residue interactions can provide new insights and structural rationale for how single-point mutations cause drastic changes in TIR-TIR interactions. We employed molecular dynamics simulations and protein structure network (PSN) analyses to investigate the structural transitions with special emphasis on TLR2 and TLR3. Our results reveal that phosphorylation of the Tyr 759 residue in the TIR domain of TLR3 introduces rigidity to its BB loop. Subtle differences in the intra BB loop hydrogen bonding network between TLR3 and TLR2 are also observed. The PSN analyses indicate that the TIR domain is highly connected and pinpoints key differences in the inter-residue interactions between the wild-type and mutant TIR domains, suggesting that TIR domain structure is prone to allosteric effects, consistent with the current view of the influence of allostery on TLR signaling.

Integrative modelling of TIR domain-containing adaptor molecule inducing interferon-ß (TRIF) provides insights into its autoinhibited state.

BACKGROUND: TRIF is a key protein in antiviral innate immunity, operating downstream of TLRs. TRIF activation leads to the production of interferon-ß and pro-inflammatory cytokines. There is evidence from experiments to suggest that the N-terminal domain of TRIF binds to its TIR domain to avoid constitutive activation. However, no structure of a complex between the N-terminal domain and the TIR domain exists till date. The disordered nature of the region connecting the N-terminal domain and the TIR domain compounds the issue of elucidating the mechanism of autoinhibition of TRIF. In this study, we have employed an integrative approach consisting of mutual information analysis, docking, molecular dynamics simulations and residue network analysis, in combination with existing experimental data to provide a glimpse of TRIF in its autoinhibited state. RESULTS: Our extensive docking approach reveals that the N-terminal domain binds to the BB loop-B helix region of the TIR domain, consistent with experimental observations. Long length molecular dynamics simulations of 1 microsecond performed on the docked model highlights residues participating in hydrogen bonding and hydrophobic interactions at the interface. A pair of residues present in the vicinity of the interface is also predicted by mutual information analysis, to co-evolve. Residues mediating long-range interactions within the TIR domain of TRIF were identified using residue network analysis. CONCLUSIONS: Based on the results of the modelling and residue network analysis, we propose that the N-terminal domain binds to the BB loop region of the TIR domain, thereby preventing its homodimersation. The binding of TRIF to TLR3 or TRAM could induce a slight conformational change, causing the interactions between the N-terminal domain and TIR domain to disrupt, thereby exposing the BB loop and rendering it amenable for higher-order oligomerisation. REVIEWERS: This article was reviewed by Michael Gromiha, Srikrishna Subramaniam and Peter Bond (nominated by Chandra Verma).

An in silico approach towards the identification of novel inhibitors of the TLR-4 signaling pathway.

Precise functioning and fine-tuning of Toll-like receptor 4 (TLR4) signaling is a critical requirement for the smooth functioning of the innate immune system, since aberrant TLR4 activation causes excessive production of pro-inflammatory cytokines and interferons. This can result in life threatening conditions such as septic shock and other inflammatory disorders. The TRIF-related adaptor molecule (TRAM) adaptor protein is unique to the TLR4 signaling pathway and abrogation of TRAM-mediated TLR4 signaling is a promising strategy for developing therapeutics aimed at disrupting TRAM interactions with other components of the TLR4 signaling complex. The VIPER motif from the vaccinia virus-producing protein, A46 has been reported to disrupt TRAM-TLR4 interactions. We have exploited this information, in combination with homology modeling and docking approaches, to identify a potential binding site on TRAM lined by the BB loop and αC helix. Virtual screening of commercially available small molecules targeting the binding site enabled to short-list 12 small molecules to abrogate TRAM-mediated TLR4 signaling. Molecular dynamics and molecular mechanics calculations have been performed for the analysis of these receptor-ligand interactions.