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1.
Front Immunol ; 12: 646972, 2021.
Article in English | MEDLINE | ID: covidwho-1438415

ABSTRACT

Background: Immune system conditions of the patient is a key factor in COVID-19 infection survival. A growing number of studies have focused on immunological determinants to develop better biomarkers for therapies. Aim: Studies of the insurgence of immunity is at the core of both SARS-CoV-2 vaccine development and therapies. This paper attempts to describe the insurgence (and the span) of immunity in COVID-19 at the population level by developing an in-silico model. We simulate the immune response to SARS-CoV-2 and analyze the impact of infecting viral load, affinity to the ACE2 receptor, and age in an artificially infected population on the course of the disease. Methods: We use a stochastic agent-based immune simulation platform to construct a virtual cohort of infected individuals with age-dependent varying degrees of immune competence. We use a parameter set to reproduce known inter-patient variability and general epidemiological statistics. Results: By assuming the viremia at day 30 of the infection to be the proxy for lethality, we reproduce in-silico several clinical observations and identify critical factors in the statistical evolution of the infection. In particular, we evidence the importance of the humoral response over the cytotoxic response and find that the antibody titers measured after day 25 from the infection are a prognostic factor for determining the clinical outcome of the infection. Our modeling framework uses COVID-19 infection to demonstrate the actionable effectiveness of modeling the immune response at individual and population levels. The model developed can explain and interpret observed patterns of infection and makes verifiable temporal predictions. Within the limitations imposed by the simulated environment, this work proposes quantitatively that the great variability observed in the patient outcomes in real life can be the mere result of subtle variability in the infecting viral load and immune competence in the population. In this work, we exemplify how computational modeling of immune response provides an important view to discuss hypothesis and design new experiments, in particular paving the way to further investigations about the duration of vaccine-elicited immunity especially in the view of the blundering effect of immunosenescence.


Subject(s)
COVID-19/immunology , Models, Immunological , SARS-CoV-2/physiology , Antibodies, Viral/blood , COVID-19/epidemiology , Cohort Studies , Computer Simulation , Cytokine Release Syndrome/immunology , Cytokines/blood , Humans , Immunity, Humoral , Immunosenescence , Prognosis , SARS-CoV-2/immunology , Severity of Illness Index , Viral Load
2.
Sci Rep ; 10(1): 10895, 2020 07 02.
Article in English | MEDLINE | ID: covidwho-629396

ABSTRACT

In the past two decades, 7 coronaviruses have infected the human population, with two major outbreaks caused by SARS-CoV and MERS-CoV in the year 2002 and 2012, respectively. Currently, the entire world is facing a pandemic of another coronavirus, SARS-CoV-2, with a high fatality rate. The spike glycoprotein of SARS-CoV-2 mediates entry of virus into the host cell and is one of the most important antigenic determinants, making it a potential candidate for a vaccine. In this study, we have computationally designed a multi-epitope vaccine using spike glycoprotein of SARS-CoV-2. The overall quality of the candidate vaccine was validated in silico and Molecular Dynamics Simulation confirmed the stability of the designed vaccine. Docking studies revealed stable interactions of the vaccine with Toll-Like Receptors and MHC Receptors. The in silico cloning and codon optimization supported the proficient expression of the designed vaccine in E. coli expression system. The efficiency of the candidate vaccine to trigger an effective immune response was assessed by an in silico immune simulation. The computational analyses suggest that the designed multi-epitope vaccine is structurally stable which can induce specific immune responses and thus, can be a potential vaccine candidate against SARS-CoV-2.


Subject(s)
Betacoronavirus/immunology , Coronavirus Infections/prevention & control , Epitopes, B-Lymphocyte/immunology , Epitopes, T-Lymphocyte/immunology , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Spike Glycoprotein, Coronavirus/immunology , Viral Vaccines/immunology , Angiotensin-Converting Enzyme 2 , Antibody Affinity/immunology , Betacoronavirus/chemistry , Betacoronavirus/genetics , COVID-19 , Coronavirus Infections/virology , Histocompatibility Antigens/immunology , Humans , Molecular Docking Simulation , Molecular Dynamics Simulation , Peptidyl-Dipeptidase A/metabolism , Phylogeny , Pneumonia, Viral/virology , Protein Structure, Tertiary , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/metabolism , Toll-Like Receptor 2/immunology , Toll-Like Receptor 2/metabolism , Toll-Like Receptor 4/immunology , Toll-Like Receptor 4/metabolism , Viral Vaccines/metabolism
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