Immunoinformatic prediction of potential immunodominant epitopes from cagW in order to investigate protection against Helicobacter pylori infection based on experimental consequences.

Helicobacter pylori is a leading cause of stomach cancer and peptic ulcers. Thus, identifying epitopes in H. pylori antigens is important for disease etiology, immunological surveillance, enhancing early detection tests, and developing optimal epitope-based vaccines. We used immunoinformatic and computational methods to create a potential CagW epitope candidate for H. pylori protection. The cagW gene of H. pylori was amplified and cloned into pcDNA3.1 (+) for injection into the muscles of healthy BALB/c mice to assess the impact of the DNA vaccine on interleukin levels. The results will be compared to a control group of mice that received PBS or cagW-pcDNA3.1 (+) vaccinations. An analysis of CagW protein antigens revealed 8 CTL and 7 HTL epitopes linked with AYY and GPGPG, which were enhanced by adding B-defensins to the N-terminus. The vaccine's immunogenicity, allergenicity, and physiochemistry were validated, and its strong activation of TLRs (1, 2, 3, 4, and 10) suggests it is antigenic. An in-silico cloning and immune response model confirmed the vaccine's expression efficiency and predicted its impact on the immune system. An immunofluorescence experiment showed stable and bioactive cagW gene expression in HDF cells after cloning the whole genome into pcDNA3.1 (+). In vivo vaccination showed that pcDNA3.1 (+)-cagW-immunized mice had stronger immune responses and a longer plasmid DNA release window than control-plasmid-immunized mice. After that, bioinformatics methods predicted, developed, and validated the three-dimensional structure. Many online services docked it with Toll-like receptors. The vaccine was refined using allergenicity, antigenicity, solubility, physicochemical properties, and molecular docking scores. Virtual-reality immune system simulations showed an impressive reaction. Codon optimization and in-silico cloning produced E. coli-expressed vaccines. This study suggests a CagW epitopes-protected H. pylori infection. These studies show that the proposed immunization may elicit particular immune responses against H. pylori, but laboratory confirmation is needed to verify its safety and immunogenicity.

SARS-CoV-2: Origin, Intermediate Host and Allergenicity Features and Hypotheses.

The goal of this study is to investigate the probable intermediate hosts and the allergenicity of the notorious virus SARS-CoV-2 to understand how this virus emerged. The phylogenetic analysis of the virus spike proteins indicates that SARS-CoV-2 falls into various small subclades that include a bat coronavirus RaTG13, suggesting bats as a likely natural origin. Refined alignment of the spike protein in NCBI found several fragments that are specific to SARS-CoV-2 and/or SARS-CoV are specific to Rattus norvegicus and/or Mus musculus, suggesting that rodents are the intermediate reservoir of SARS-CoV-2 and SARS-CoV. To evaluate the allergenicity values, the binding affinities of human leukocyte antigen (HLA) class I or II molecules with the spike proteins were calculated, and the results showed that both SARS-CoV-2 and SARS-CoV are predicted to bind to fourteen HLA class I and II molecules with super-high HLA allele-peptide affinities. The infection rate of individuals who have HLA alleles with very high binding affinities who might become infected and develop into refractory patients if there were no medical or non-medical interventions is about 7.36% and 4.78% of Chinese and Americans, respectively. Extremely high temperature and exceptionally low precipitation, the common climate factors between the outbreak sites of COVID-19 in Wuhan in 2019 and SARS in Guangdong in 2002, might have promoted coronavirus evolution into more virulent forms. Our hypothesis suggests that early immunization with an allergenically-engineered virus, in combination with continued surveillance of meteorological factors and viral mutations, may be one of the most powerful prophylactic modalities to fight this virus.

Markov state modeling reveals alternative unbinding pathways for peptide-MHC complexes.

Peptide binding to major histocompatibility complexes (MHCs) is a central component of the immune system, and understanding the mechanism behind stable peptide-MHC binding will aid the development of immunotherapies. While MHC binding is mostly influenced by the identity of the so-called anchor positions of the peptide, secondary interactions from nonanchor positions are known to play a role in complex stability. However, current MHC-binding prediction methods lack an analysis of the major conformational states and might underestimate the impact of secondary interactions. In this work, we present an atomically detailed analysis of peptide-MHC binding that can reveal the contributions of any interaction toward stability. We propose a simulation framework that uses both umbrella sampling and adaptive sampling to generate a Markov state model (MSM) for a coronavirus-derived peptide (QFKDNVILL), bound to one of the most prevalent MHC receptors in humans (HLA-A24:02). While our model reaffirms the importance of the anchor positions of the peptide in establishing stable interactions, our model also reveals the underestimated importance of position 4 (p4), a nonanchor position. We confirmed our results by simulating the impact of specific peptide mutations and validated these predictions through competitive binding assays. By comparing the MSM of the wild-type system with those of the D4A and D4P mutations, our modeling reveals stark differences in unbinding pathways. The analysis presented here can be applied to any peptide-MHC complex of interest with a structural model as input, representing an important step toward comprehensive modeling of the MHC class I pathway.

Mortality in COVID-19 disease patients: Correlating the association of major histocompatibility complex (MHC) with severe acute respiratory syndrome 2 (SARS-CoV-2) variants.

Genetic factors such as the HLA type of patients may play a role in regard to disease severity and clinical outcome of patients with COVID-19. Taking the data deposited in the GISAID database, we made predictions using the IEDB analysis resource (TepiTool) to gauge how variants in the SARS-CoV-2 genome may change peptide binding to the most frequent MHC-class I and -II alleles in Africa, Asia and Europe. We caracterized how a single mutation in the wildtype sequence of of SARS-CoV-2 could influence the peptide binding of SARS-CoV-2 variants to MHC class II, but not to MHC class I alleles. Assuming the ORF8 (L84S) mutation is biologically significant, selective pressure from MHC class II alleles may select for viral varients and subsequently shape the quality and quantity of cellular immune responses aginast SARS-CoV-2. MHC 4-digit typing along with viral sequence analysis should be considered in studies examining clinical outcomes in patients with COVID-19.