ABSTRACT
The N501Y mutation in Covid-19 arise many question but a small amount of data are currently available. An urgent understanding of N501Y mechanism of action at molecular level is highly required. Here, we present the preliminary results of our Free energy perturbation (FEP) and Molecular dynamics (MD) calculations for the interaction of the spike S1 receptor binding domain (RBD) with both the ACE2 receptor and an antibody, STE90-C11, derived from COVID-19 patients. The results shown that the S1 RBD-ACE2 interaction was increased whereas those with the STE90-C11 antibody significantly decreased (over about 160 times). This may explain the observed in UK more spread of the virus but also emerge an important question about the possible human immune response and already available vaccines. Indeed, the latter may still act well but our data indicate some possible reduction of their effect. Further studies of N501Y mutation are need.
Subject(s)
COVID-19ABSTRACT
As the mechanistic basis of adaptive cellular antigen recognition, T cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages antigen-enriched repertoires to form meta-clonotypes -- groups of biochemically similar TCRs -- that can be used to robustly quantify functionally similar TCRs in bulk repertoires. We apply the framework to TCR data from COVID-19 patients, generating 1,915 public TCR meta-clonotypes from the 18 SARS-CoV-2 antigen-enriched repertoires with the strongest evidence of HLA-restriction. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 44% (845/1915) were significantly enriched among COVID-19 patients that expressed the putative restricting HLA allele, demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, tcrdist3, that implements this framework and facilitates workflows for distance-based TCR repertoire analysis.
Subject(s)
COVID-19ABSTRACT
Development of effective adaptive immune responses after coronavirus disease 2019 (COVID-19) and after vaccination against SARS-CoV-2 is predicated on recognition of viral peptides, presented in the context of HLA class II molecules, by CD4+ T-cells. We capitalised on extensive high resolution HLA data deposited in the National Marrow Donor Program registry to obtain detailed information on human HLA haplotype frequencies of twenty five human populations and used a bioinformatics approach to investigate the role of HLA polymorphism on SARS-CoV-2 immunogenicity at the population and at the individual level. Within populations, we identify wide inter-individual variability in predicted CD4+ T-cell reactivity against structural, non-structural and accessory SARS-CoV-2 proteins, according to expressed HLA genotype. However, we find similar potential for anti-SARS-CoV-2 cellular immunity at the population level, across all ethnic groups examined, suggesting that HLA polymorphism is unlikely to account for observed disparities in clinical outcomes after COVID-19 among different race and ethnic groups. We predict robust immune reactivity against SARS-CoV-2 Spike protein, the basis for the majority of current vaccination efforts, both at the population and individual level, despite significant variation in Spike-derived peptide presentation by individual HLA genotypes. Finally, we provide comprehensive maps of SARS-CoV-2 proteome immunogenicity accounting for population coverage in major ethnic groups. Our findings provide important insight on the potential role of HLA polymorphism on development of protective immunity after SARS-CoV-2 infection and after vaccination and a firm basis for further experimental studies in this field.
Subject(s)
COVID-19 , Severe Acute Respiratory SyndromeABSTRACT
Background Retrospective observational studies suggest that interleukin-6 (IL-6), C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, lymphocytes, monocytes, neutrophils, D-dimer, and platelets are associated with disease progression, treatment outcomes, or both, in patients with COVID-19 pneumonia. We explored these candidate prognostic and predictive biomarkers with efficacy outcomes after treatment with tocilizumab, an anti-IL-6 receptor antibody using data from the COVACTA trial for patients hospitalised with severe COVID-19 pneumonia. Methods Candidate biomarkers were measured in 295 patients in the tocilizumab arm and 142 patients in the placebo arm. Efficacy outcomes assessed were clinical status on a seven-category ordinal scale (1, discharge; 7, death), mortality, time to hospital discharge, and mechanical ventilation (if not receiving it at randomisation) through day 28. Prognostic and predictive biomarkers were evaluated continuously with proportional odds, binomial or Fine-Gray models, and additional sensitivity analyses. Findings Modelling in the placebo arm showed all candidate biomarkers except LDH and D-dimer were strongly prognostic for day 28 clinical outcomes of mortality, mechanical ventilation, clinical status, and time to hospital discharge. Modelling in the tocilizumab arm showed a predictive value of ferritin for day 28 clinical outcomes of mortality (predictive interaction p=0.03), mechanical ventilation (predictive interaction p=0.01), and clinical status (predictive interaction p=0.02) compared with placebo. Interpretation Multiple biomarkers prognostic for clinical outcomes were confirmed in COVACTA. Ferritin was identified as a predictive biomarker for the effects of tocilizumab in the COVACTA patient population; high ferritin levels were associated with better clinical outcomes for tocilizumab compared with placebo at day 28.
Subject(s)
COVID-19 , PneumoniaABSTRACT
Many antibody and immune escape variants in SARS-CoV-2 are now documented in literature. The availability of SARS-CoV-2 genome sequences enabled us to investigate the occurrence and genetic epidemiology of the variants globally. Our analysis suggests that a number of genetic variants associated with immune escape have emerged in global populations.
ABSTRACT
Within the last two decades, severe acute respiratory syndrome (SARS) coronaviruses 1 and 2 (SARS-CoV-1 and SARS-CoV-2) have caused two major outbreaks. For reasons yet to be fully understood the COVID-19 outbreak caused by SARS-CoV-2 has been significantly more widespread than the 2003 SARS epidemic caused by SARS-CoV-1, despite striking similarities between the two viruses. One of the most variable genes differentiating SARS-CoV-1 and SARS-CoV-2 is the S gene that encodes the spike glycoprotein. This protein mediates a crucial step in the infection, i.e., host cell recognition and viral entry, which starts with binding to the host cell angiotensin converting enzyme 2 (ACE2) protein for both viruses. Recent structural and functional studies have shed light on the differential binding behavior of the SARS-CoV-1 and SARS-CoV-2 spike proteins. In particular, cryogenic electron microscopy (cryo-EM) studies show that ACE2 binding is preceded by a large-scale conformational change in the spike protein to expose the receptor binding domain (RBD) to its binding partner. Unfortunately, these studies do not provide detailed information on the dynamics of this activation process. Here, we have used an extensive set of unbiased and biased microsecond-timescale all-atom molecular dynamics (MD) simulations of SARS-CoV-1 and SARS-CoV-2 spike protein ectodomains in explicit solvent to determine the differential behavior of spike protein activation in the two viruses. Our results based on nearly 50 microseconds of equilibrium and nonequilibrium MD simulations indicate that the active form of the SARS-CoV-2 spike protein is considerably more stable than the active SARS-CoV-1 spike protein. Unlike the active SARS-CoV-2 spike, the active SARS-CoV-1 spike spontaneously undergoes a large-scale conformational transition to a pseudo-inactive state, which occurs in part due to interactions between the N-terminal domain (NTD) and RBD that are absent in the SARS-CoV-2 spike protein. Steered MD (SMD) simulations indicate that the energy barriers between active and inactive states are comparatively lower for the SARS-CoV-1 spike protein. Based on these results, we hypothesize that the greater propensity of the SARS-CoV-2 spike protein to remain in the active conformation contributes to the higher transmissibility of SARS-CoV-2 in comparison to SARS-CoV-1. These results strongly suggest that the differential binding behavior of the active SARS-CoV-1 and 2 spike proteins is not merely due to differences in their RBDs as other domains of the spike protein such as the NTD could play a crucial role in the effective binding process, which involves the pre-binding activation. Therefore, our hypothesis predicts that mutations in regions such as the NTD, which is not directly involved in binding, may lead to a change in the effective binding behavior of the coronavirus.