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A candidate multi-epitope vaccine against SARS-CoV-2.

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TLDR
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.
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.

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COVID-19 and Toll-Like Receptor 4 (TLR4): SARS-CoV-2 May Bind and Activate TLR4 to Increase ACE2 Expression, Facilitating Entry and Causing Hyperinflammation.

TL;DR: In this article, the authors proposed a model in which the SARS-CoV-2 spike glycoprotein binds TLR4 and activates TLR 4 signalling to increase cell surface expression of ACE2 facilitating entry.
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Non-viral COVID-19 vaccine delivery systems.

TL;DR: A few of the leading non-viral vaccines that are under clinical stage development are introduced and delivery strategies to improve vaccine efficacy, duration of protection, safety, and mass vaccination are discussed.
Journal ArticleDOI

Exploring the out of sight antigens of SARS-CoV-2 to design a candidate multi-epitope vaccine by utilizing immunoinformatics approaches.

TL;DR: A novel multi-epitope vaccine against SARS-CoV-2 was designed to provoke both innate and adaptive immune responses and exhibited high efficacy in silico, although further experimental validation is necessary.
Journal ArticleDOI

GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences.

TL;DR: GESS reveals geographical distributions of SNVs around the world and across the states of USA, while exhibiting time-dependent patterns for SNV occurrences which reflect development of SARS-CoV-2 genomes.
References
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Journal ArticleDOI

MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets

TL;DR: The latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine, has been optimized for use on 64-bit computing systems for analyzing larger datasets.
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A simple method for displaying the hydropathic character of a protein

TL;DR: A computer program that progressively evaluates the hydrophilicity and hydrophobicity of a protein along its amino acid sequence has been devised and its simplicity and its graphic nature make it a very useful tool for the evaluation of protein structures.
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GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

TL;DR: GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules, and provides a rich set of calculation types.
Journal ArticleDOI

Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes

TL;DR: A new membrane protein topology prediction method, TMHMM, based on a hidden Markov model is described and validated, and it is discovered that proteins with N(in)-C(in) topologies are strongly preferred in all examined organisms, except Caenorhabditis elegans, where the large number of 7TM receptors increases the counts for N(out)-C-in topologies.
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