Predicting the immune escape of SARS-CoV-2 neutralizing antibodies upon mutation.

COVID-19 has resulted in millions of deaths and severe impact on economies worldwide. Moreover, the emergence of SARS-CoV-2 variants presented significant challenges in controlling the pandemic, particularly their potential to avoid the immune system and evade vaccine immunity. This has led to a growing need for research to predict how mutations in SARS-CoV-2 reduces the ability of antibodies to neutralize the virus. In this study, we assembled a set of 1813 mutations from the interface of SARS-CoV-2 spike protein's receptor binding domain (RBD) and neutralizing antibody complexes and developed a machine learning model to classify high or low escape mutations using interaction energy, inter-residue contacts and predicted binding free energy change. Our approach achieved an Area under the Receiver Operating Characteristics (ROC) Curve (AUC) of 0.91 using the Random Forest classifier on the test dataset with 217 mutations. The model was further utilized to predict the escape mutations on a dataset of 29,165 mutations located at the interface of 83 RBD-neutralizing antibody complexes. A small subset of this dataset was also validated based on available experimental data. We found that top 10 % high escape mutations were dominated by charged to nonpolar mutations whereas low escape mutations were dominated by polar to nonpolar mutations. We believe that the present method will allow prioritization of high/low escape mutations in the context of neutralizing antibodies targeting SARS-CoV-2 RBD region and assist antibody design for current and emerging variants.

Secretory protein Rv1987, a 'probable chitinase' from Mycobacterium tuberculosis is a novel chitin and cellulose binding protein lacking enzymatic function.

Bacterial chitinases serve to hydrolyse chitin as food source or as defence mechanism. Given that chitin is not produced by mammals, it is intriguing that Mycobacterium tuberculosis, an exclusively human pathogen harbours Rv1987, a probable chitinase and secretes it. Interestingly genes annotated as chitinases are widely distributed among Mycobacterium tuberculosis complex species, clinical isolates and other human pathogens M. abscessus and M. ulcerans. However, Mycobacterial chitinases are not characterized and hence the functions remain unknown. In the present study, we show that Rv1987 is a chitin and cellulose binding protein lacking enzymatic activity in contrary to its current annotation. Further, we show Rv1987 has moon lighting functions in M. tuberculosis pathobiology signifying roles of bacterial cellulose binding clusters in infections.

Ab-CoV: a curated database for binding affinity and neutralization profiles of coronavirus-related antibodies.

SUMMARY: We have developed a database, Ab-CoV, which contains manually curated experimental interaction profiles of 1780 coronavirus-related neutralizing antibodies. It contains more than 3200 datapoints on half maximal inhibitory concentration (IC50), half maximal effective concentration (EC50) and binding affinity (KD). Each data with experimentally known three-dimensional structures are complemented with predicted change in stability and affinity of all possible point mutations of interface residues. Ab-CoV also includes information on epitopes and paratopes, structural features of viral proteins, sequentially similar therapeutic antibodies and Collier de Perles plots. It has the feasibility for structure visualization and options to search, display and download the data. AVAILABILITY AND IMPLEMENTATION: Ab-CoV database is freely available at https://web.iitm.ac.in/bioinfo2/ab-cov/home. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mutations in spike protein T cell epitopes of SARS-COV-2 variants: Plausible influence on vaccine efficacy.

With emerging SARS-CoV-2 variants, vaccines approved so far are under scrutiny for long term effectiveness against the circulating strains. There is a prevalent obsession with humoral immunity as in vitro studies have indicated diminished effects of vaccine-induced neutralizing antibodies. However, this need not clinically translate to vaccine resistance as immune response against all forms of present vaccine preparations is T dependent unlike that against native viral particles which can induce T independent immune responses. Thus, we focused on this major correlate of protection against infections, T cell response. Using bioinformatics tools, we analyzed SARS-CoV-2 Spike protein T cell epitopes and their diversity across Delta plus/B.1.617.2.1, Gamma/P.1 (variant of concern), B.1.1.429, Zeta/P.2 and Mink cluster 5/B.1.1.298 variants as well as Omicron/B.1.1.529 (variant of concern). We also compared HLA restriction profiles of the mutant epitopes with that of the native epitopes (from Wuhan_hu_1 strain, used in vaccine formulations). Our observations show ~90% conservation of CD4+ and CD8+ epitopes across Delta plus/B.1.617.2.1, Gamma/P.1 (variant of concern), B.1.1.429, Zeta/P.2 and Mink cluster 5/B.1.1.298. For the Omicron/B.1.1.529 variant, ~75% of CD4+ and ~ 87% CD8+ epitopes were conserved. Majority of the mutated CD4+ and CD8+ epitopes of this variant were predicted to retain the HLA restriction pattern as their native epitopes. The results of our bioinformatics analysis suggest largely conserved T cell responses across the studied variants, ability of T cells to tackle new SARS-CoV-2 variants and aid in protection from COVID-19 post vaccination. In conclusion, the results suggest that current vaccines may not be rendered completely ineffective against new variants.

Elucidating important structural features for the binding affinity of spike - SARS-CoV-2 neutralizing antibody complexes.

The coronavirus disease 2019 (COVID-19) has affected the lives of millions of people around the world. In an effort to develop therapeutic interventions and control the pandemic, scientists have isolated several neutralizing antibodies against SARS-CoV-2 from the vaccinated and convalescent individuals. These antibodies can be explored further to understand SARS-CoV-2 specific antigen-antibody interactions and biophysical parameters related to binding affinity, which can be utilized to engineer more potent antibodies for current and emerging SARS-CoV-2 variants. In the present study, we have analyzed the interface between spike protein of SARS-CoV-2 and neutralizing antibodies in terms of amino acid residue propensity, pair preference, and atomic interaction energy. We observed that Tyr residues containing contacts are highly preferred and energetically favorable at the interface of spike protein-antibody complexes. We have also developed a regression model to relate the experimental binding affinity for antibodies using structural features, which showed a correlation of 0.93. Moreover, several mutations at the spike protein-antibody interface were identified, which may lead to immune escape (epitope residues) and improved affinity (paratope residues) in current/emerging variants. Overall, the work provides insights into spike protein-antibody interactions, structural parameters related to binding affinity and mutational effects on binding affinity change, which can be helpful to develop better therapeutics against COVID-19.

Untangling COVID-19 and autoimmunity: Identification of plausible targets suggests multi organ involvement.

Underlying mechanisms of multi-organ manifestations and exacerbated inflammation in COVID-19 are yet to be delineated. The hypothesis of SARS-CoV-2 triggering autoimmunity is gaining attention and, in the present study, we have identified 28 human proteins harbouring regions homologous to SARS-CoV-2 peptides that could possibly be acting as autoantigens in COVID-19 patients displaying autoimmune conditions. Interestingly, these conserved regions are amongst the experimentally validated B cell epitopes of SARS-CoV-2 proteins. The reported human proteins have demonstrated presence of autoantibodies against them in typical autoimmune conditions which may explain the frequent occurrence of autoimmune conditions following SARS-CoV-2 infection. Moreover, the proposed autoantigens' widespread tissue distribution is suggestive of their involvement in multi-organ manifestations via molecular mimicry. We opine that our report may aid in directing subsequent necessary antigen-specific studies, results of which would be of long-term relevance in management of extrapulmonary symptoms of COVID-19.

Exploring antibody repurposing for COVID-19: beyond presumed roles of therapeutic antibodies.

The urgent need for a treatment of COVID-19 has left researchers with limited choice of either developing an effective vaccine or identifying approved/investigational drugs developed for other medical conditions for potential repurposing, thus bypassing long clinical trials. In this work, we compared the sequences of experimentally verified SARS-CoV-2 neutralizing antibodies and sequentially/structurally similar commercialized therapeutic monoclonal antibodies. We have identified three therapeutic antibodies, Tremelimumab, Ipilimumab and Afasevikumab. Interestingly, these antibodies target CTLA4 and IL17A, levels of which have been shown to be elevated during severe SARS-CoV-2 infection. The candidate antibodies were evaluated further for epitope restriction, interaction energy and interaction surface to gauge their repurposability to tackle SARS-CoV-2 infection. Our work provides candidate antibody scaffolds with dual activities of plausible viral neutralization and immunosuppression. Further, these candidate antibodies can also be explored in diagnostic test kits for SARS-CoV-2 infection. We opine that this in silico workflow to screen and analyze antibodies for repurposing would have widespread applications.

A plasmonic fiberoptic absorbance biosensor for mannose-capped lipoarabinomannan based tuberculosis diagnosis.

Tuberculosis (TB) is a resurgent infectious disease affecting a large number of people in the developing countries. An on-site, affordable diagnostic screening at an early-stage for an immediate anti-TB treatment is known to tremendously minimize the high mortality rates. Lipoarabinomannan (LAM), a surface glycolipid, has been identified as a potential TB biomarker present in urine at ultra-low concentrations of a few fg/mL. Here, we report a plasmonic fiber optic absorbance biosensor (P-FAB) strategy for mannosylated LAM (Man-LAM or Mtb LAM) detection down to attomolar concentrations. It involves a plasmonic sandwich immunoassay on a U-bent fiber optic probe with gold plasmonic (AuNP) labels functionalized with anti-Mtb LAM immunoglobulin M (IgM) and anti-Mtb LAM IgG respectively. The Mtb LAM is quantified in terms of absorption of light passing through the fiber probe using a green LED and a photodetector. The choice of fiber optic probes (fused silica versus polymer), the optimum size (20, 40, 60 and 80 nm) and concentration (2 × , 10 × , and 20 × ) of AuNP labels were investigated to obtain high sensitivity and lower limits of analyte detection (LoD). P-FAB with a simple LED-photodetector pair, 200 µm fused silica U-bent fiber probe and 60 nm (20 × ) AuNP labels gave LoDs down to 1 fg/mL and 10 fg/mL in the buffer and synthetic urine respectively. Moreover, the anti-Mtb LAM IgM bound sensor probes and the AuNP reagent stored at 4 °C were stable up to 45 days. P-FAB based Mtb LAM sensor demonstrates its potential for an on-site TB diagnosis.

A possible role for autoimmunity through molecular mimicry in alphavirus mediated arthritis.

Alphaviral infections are foremost in causing debilitating clinical outcomes in humans characterized by rheumatic arthritis like conditions. Though the presence of virus in joints and associated inflammation has been implicated as one of the reasons for the acute and chronic polyarthritis post alphaviral infections, the basis for rheumatic like outcomes is not clear. Through an in silico analysis, we have investigated the possibility of an autoimmune process mediated through molecular mimicry in alphaviral infection induced pathogenicity. Interestingly, sequence alignment of the structural polyproteins belonging to arthritogenic alphaviruses revealed conserved regions which share homology with human proteins implicated in rheumatoid arthritis (RA). These conserved regions were predicted to exhibit binding to HLA class II alleles, showcasing their potential to incite T cell help. Molecular docking of the viral peptide and the corresponding homologous region in the human protein onto HLA-DRB1 revealed strong similarities in their binding patterns. Linear and conformational B cell epitope prediction analyses showed that these potential mimics have high propensity to elicit an efficient B cell response. We thus propose that the origin of polyarthritis post-arthritogenic alphaviral infections may also be mediated through a hitherto unknown autoimmune response due to the presence of cross-reactive epitopes between viral and human proteins.

Elucidating the biosynthetic pathways of volatile organic compounds in Mycobacterium tuberculosis through a computational approach.

Microbial volatile organic compounds (VOCs) have gained prominence in the recent past for their potential use as disease markers. The discovery of microbial VOCs has benefited 'difficult to detect' diseases such as tuberculosis (TB). Few of the identified VOCs of Mycobacterium tuberculosis (Mtb) are currently being explored for their diagnostic potential. However, very little is known about the biosynthesis of these small lipophilic molecules. Here, we propose putative biosynthetic pathways in Mycobacterium tuberculosis for three VOCs, namely methyl nicotinate, methyl phenylacetate and methyl p-anisate, using computational approaches. In particular, we identify S-adenosyl methionine (SAM) transferases that play a crucial role in esterification of the acids to the final product. Our results provide important insights into the specificity of these pathways to Mtb species.