Background
Coronavirus disease 2019 (COVID-19) linked with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause severe illness and life-threatening pneumonia in humans. The current COVID-19 pandemic demands an effective vaccine to acquire protection against the infection. Therefore, the present study was aimed to design a multiepitope-based subunit vaccine (MESV) against COVID-19.
Methods
Structural proteins (Surface glycoprotein, Envelope protein, and Membrane glycoprotein) of SARS-CoV-2 are responsible for its prime functions. Sequences of proteins were downloaded from GenBank and several immunoinformatics coupled with computational approaches were employed to forecast B- and T- cell epitopes from the SARS-CoV-2 highly antigenic structural proteins to design an effective MESV.
Results
Predicted epitopes suggested high antigenicity, conserveness, substantial interactions with the human leukocyte antigen (HLA) binding alleles, and collective global population coverage of 88.40%. Taken together, 276 amino acids long MESV was designed by connecting 3 cytotoxic T lymphocytes (CTL), 6 helper T lymphocyte (HTL) and 4 B-cell epitopes with suitable adjuvant and linkers. The MESV construct was non-allergenic, stable, and highly antigenic. Molecular docking showed a stable and high binding affinity of MESV with human pathogenic toll-like receptors-3 (TLR3). Furthermore, in silico immune simulation revealed significant immunogenic response of MESV. Finally, MEV codons were optimized for its in silico cloning into the Escherichia coli K-12 system, to ensure its increased expression.
Conclusion
The MESV developed in this study is capable of generating immune response against COVID-19. Therefore, if designed MESV further investigated experimentally, it would be an effective vaccine candidate against SARS-CoV-2 to control and prevent COVID-19.
Background: Coronavirus disease 2019 (COVID-19) caused by Severe Acute RespiratorySyndrome Corona virus 2 (SARS-COV-2) was first diagnosed in December 2019, Wuhan, China. Little is known about this new virus and it has the potential to cause severe illness and pneumonia in some people, therefore the development of an effective vaccine is highly desired.Methods: Immunoinformatics and statistical approaches were used in this study to forecast B-and T-cell epitopes for the SARS-COV-2 structural proteins (Surface glycoprotein, Envelope protein, and Membrane glycoprotein) that may play a key role in eliciting immune response against COVID-19. Different types of B cell epitopes (linear as well as discontinuous) and T cell (MHC class I and MHC class II) were determined.Moreover, their antigenicity and allergenicity were also estimated.
Results:The antigenic B-cell epitopes exposed to the outer surface were screened out and 23 linear B cell epitopes were selected. "SPTKLNDLCFTNVY" had the highest antigenicity score among B cell epitopes. The T-cell epitopes bound to multiple alleles, antigenic, non-allergen, non-toxic, and conserved in the protein sequence were shortlisted. In total, 16 epitopes (9 from MHC class I and 7 from MHC class II) were selected. Among the T-cell epitopes, MHC class I (IPFAMQMAYRFN) and MHC class II (VTLACFVLAAVYRIN) were classified as strongly antigenic. Digestion analysis verified the safety and stability of the peptides predicted during this study. Furthermore, docking analyses of predicted peptides showed significant interactions with the HLA-B7 allele.
BCL2 apoptosis regulator gene encodes Bcl-2 pro-survival protein, which plays an important role to evade apoptosis in various cancers. Moreover, single nucleotide polymorphisms (SNPs) in the BCL2 gene can be nonsynonymous (nsSNPs), which might affect the protein stability and probably its function. Therefore, we implement cutting-edge computational techniques based on the Spherical Polar Fourier and Monte-Carlo algorithms to investigate the impact of these SNPs on the B cell lymphoma-2 (Bcl-2) stability and therapeutic potential of protein-based molecules to inhibit this protein. As a result, we identified two nsSNPs (Q118R and R129C) to be deleterious and highly conserved, having a negative effect on protein stability. Additionally, molecular docking and molecular dynamics simulations confirmed the decreased binding affinity of mutated Bcl-2 variants to bind three-helix bundle protein inhibitor as these mutations occurred in the protein−protein binding site. Overall, this computational approach investigating nsSNPs provides a useful basis for designing novel molecules to inhibit Bcl-2 pro-survival pathway in malignant cells.
Alzheimer’s disease (AD) is considered a chronic and debilitating neurological illness that is increasingly impacting older-age populations. Some proteins, including clusterin (CLU or apolipoprotein J) transporter, can be linked to AD, causing oxidative stress. Therefore, its activity can affect various functions involving complement system inactivation, lipid transport, chaperone activity, neuronal transmission, and cellular survival pathways. This transporter is known to bind to the amyloid beta (Aβ) peptide, which is the major pathogenic factor of AD. On the other hand, this transporter is also active at the blood–brain barrier (BBB), a barrier that prevents harmful substances from entering and exiting the brain. Therefore, in this review, we discuss and emphasize the role of the CLU transporter and CLU-linked molecular mechanisms at the BBB interface in the pathogenesis of AD.
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