Immunoinformatics Patterns and Characteristic of Epitope-Based Peptide Vaccine candidates against COVID-19

Vaccination as defined by the WHO is “the administration of agent-specific, but safe, antigenic components that in vaccinated individuals can induce protective immunity against the corresponding infectious agent”. Regardless of their debated history, the standard vaccine approaches have been unsuccessful in providing vaccines for numerous infectious organisms. In the recent three decades, an enormous amount of immunological data was retrieved from clinical studies  due to the advancement in human genome sequencing. These data are being deposited in databases and numerous scientific literature. The development of several bioinformatics tools to analyze this rapidly increasing immunological databank has given rise to the field of immunoinformatics. This approach allows the selection of immunogenic residues from the pathogen genomes. The ideal residues could be industrialized as vaccine candidates to provide protective immune responses in the hosts. This methodology will significantly decrease the time and cost needed for the vaccine development.  This review focus on  published articles that proposed as vaccine candidates through immunoinformatics analysis. The reviewed  Published immunoinformatics studies provided vaccine peptide candidates against SARS-COV-2, which is based on functional and non functional immunogenic proteins like open reading frame , spike protein, envelope protein and membranous protein .All of which  are designed by unique strategies like reverse vaccinology . Spike protein was the most common used target with different suggeststed B and T cell peptides  due to the difference in methodology between the findings

Cytokine Storm in COVID-19 Patients, their Impact on Organs and the Potential Treatment by QTY Code-Designed Detergent-Free Chemokine Receptors

The novel coronavirus in not only causing respiratory problems, it may also damage the heart, kidneys, liver and other organs; in Wuhan 14 to 30% of COVID-19 patients have lost their kidney function and now require either dialysis or kidney transplants. The novel coronavirus gains entry into humans by targeting ACE2 receptor that found on lung cells, which destroy human lungs through cytokine storms, this leads to hyper-inflammation, forcing the immune cells to destroy healthy cells. This is why some COVID-19 patients need intensive care. The inflammatory chemicals released during COVID-19 infection cause the liver to produce proteins that defend the body from infections. However, these proteins can cause blood clotting, which can clog blood vessels in the heart and other organs; as a result, the organs are deprived from oxygen and nutrients which could ultimately lead to multi-organ failure and subsequent progression to acute lung injury, acute respiratory distress syndrome and often death. However, a novel protein modification tool called the QTY code, that are similar in their structure to antibodies, which could provide a solution to excess cytokines, these synthetic proteins can be injected into the body to blind the excess cytokines generated by the cytokine storm; this will eventually remove the excessive cytokines and inhibit the severe symptoms caused by the COVID-19 infection. In this review we will focuses on cytokine storm in COVID-19 patients, their impact on the organs and the potential treatment by QTY code-designed detergent-free chemokine receptors

Developing recombinant antibodies by phage display technology to neutralize viral infectious diseases

The use of recombinant antibodies developed through phage display technology offers a promising approach for combating viral infectious diseases. By specifically targeting antigens on viral surfaces, these antibodies have the potential to reduce the severity of infections or even prevent them altogether. With the emergence of new and more virulent strains of viruses, it is crucial to develop innovative methods to counteract them. Phage display technology has proven successful in generating recombinant antibodies capable of targeting specific viral antigens, thereby providing a powerful tool to fight viral infections. In this mini-review article, we examine the development of these antibodies using phage display technology, and discuss the associated challenges and opportunities in developing novel treatments for viral infectious diseases. Furthermore, we provide an overview of phage display technology. As these methods continue to evolve and improve, novel and sophisticated tools based on phage display and peptide display systems are constantly emerging, offering exciting prospects for solving scientific, medical, and technological problems related to viral infectious diseases in the near future

Development of Recombinant Antibody by Yeast Surface Display Technology

Recombinant antibodies have emerged as powerful tools in various fields, including therapeutics, diagnostics, and research applications. The selection of high-affinity antibodies with desired specificity is a crucial step in the development of recombinant antibody-based products. In recent years, yeast surface display technology has gained significant attention as a robust and versatile platform for antibody selection. This graphical review provides an overview of the yeast surface display technology and its applications in recombinant antibody selection. We discuss the key components involved in the construction of yeast surface display libraries, including the antibody gene libraries, yeast host strains, and display vectors. Furthermore, we highlight the strategies employed for affinity maturation and optimization of recombinant antibodies using yeast surface display. Finally, we discuss the advantages and limitations of this technology compared to other antibody selection methods. Overall, yeast surface display technology offers a powerful and efficient approach for the selection of recombinant antibodies, enabling the rapid generation of high-affinity antibodies for various applications

Cytokine Storm in COVID-19 Patients, Its Impact on Organs and Potential Treatment by QTY Code-Designed Detergent-Free Chemokine Receptors

The novel coronavirus is not only causing respiratory problems, but it may also damage the heart, kidneys, liver, and other organs; in Wuhan, 14 to 30% of COVID-19 patients have lost their kidney function and now require either dialysis or kidney transplants. The novel coronavirus gains entry into humans by targeting the ACE2 receptor that found on lung cells, which destroy human lungs through cytokine storms, and this leads to hyperinflammation, forcing the immune cells to destroy healthy cells. This is why some COVID-19 patients need intensive care. The inflammatory chemicals released during COVID-19 infection cause the liver to produce proteins that defend the body from infections. However, these proteins can cause blood clotting, which can clog blood vessels in the heart and other organs; as a result, the organs are deprived of oxygen and nutrients which could ultimately lead to multiorgan failure and consequent progression to acute lung injury, acute respiratory distress syndrome, and often death. However, there are novel protein modification tools called the QTY code, which are similar in their structure to antibodies, which could provide a solution to excess cytokines. These synthetic proteins can be injected into the body to bind the excess cytokines created by the cytokine storm; this will eventually remove the excessive cytokines and inhibit the severe symptoms caused by the COVID-19 infection. In this review, we will focus on cytokine storm in COVID-19 patients, their impact on the body organs, and the potential treatment by QTY code-designed detergent-free chemokine receptors

Extensive In Silico Analysis of ATL1 Gene : Discovered Five Mutations That May Cause Hereditary Spastic Paraplegia Type 3A

Background. Hereditary spastic paraplegia type 3A (SPG3A) is a neurodegenerative disease inherited type of Hereditary spastic paraplegia (HSP). It is the second most frequent type of HSP which is characterized by progressive bilateral and mostly symmetric spasticity and weakness of the legs. SPG3A gene mutations and the phenotype-genotype correlations have not yet been recognized. The aim of this work was to categorize the most damaging SNPs in ATL1 gene and to predict their impact on the functional and structural levels by several computational analysis tools. Methods. The raw data of ATL1 gene were retrieved from dbSNP database and then run into numerous computational analysis tools. Additionally; we submitted the common six deleterious outcomes from the previous functional analysis tools to I-mutant 3.0 and MUPro, respectively, to investigate their effect on the structural level. The 3D structure of ATL1 was predicted by RaptorX and modeled using UCSF Chimera to compare the differences between the native and the mutant amino acids. Results. Five nsSNPs out of 249 were classified as the most deleterious (rs746927118, rs979765709, rs119476049, rs864622269, and rs1242753115). Conclusions. In this study, the impact of nsSNPs in the ATL1 gene was investigated by various in silico tools that revealed five nsSNPs (V67F, T120I, R217Q, R495W, and G504E) are deleterious SNPs, which have a functional impact on ATL1 protein and, therefore, can be used as genomic biomarkers specifically before 4 years of age; also, it may play a key role in pharmacogenomics by evaluating drug response for this disabling disease

Identification of Novel Key Biomarkers in Simpson-Golabi-Behmel Syndrome (SGBS): Evidence from Bioinformatics Analysis

The Simpson-Golabi-Behmel Syndrome (SGBS) or overgrowth Syndrome is an uncommon genetic X-linked disorder highlighted by macrosomia, renal defects, cardiac weaknesses and skeletal abnormalities. The purpose of the work was to classify the functional nsSNPs of GPC3 to serve as genetic biomarkers for overgrowth syndrome. The raw data of GPC3 gene were retrieved from dbSNP database and used to examine the most damaging effect using eight functional analysis tools, while we used I-mutant and MUPro to examine the effect of SNPs on GPC3 protein structure; The 3D structure of GPC3 protein is not found in the PDB, so RaptorX was used to create a 3D structural prototype to visualize the amino acids alterations by UCSF Chimera; For biophysical validation we used project HOPE; Lastly we run conservational analysis by BioEdit and Consurf web server respectively. Our results revealed three novel missense mutations (rs1460413167, rs1295603457 and rs757475450) that are that are more likely to be responsible for disturbance in the function and structure of GPC3. This work provides new insight into the molecular basis of overgrowth Syndrome by evidence from bioinformatics analysis. Three novel missense mutations (rs757475450, rs1295603457 and rs1460413167) are more likely to be responsible for disturbance in the function and structure of GPC3; therefore, they may be assisting as genetic biomarkers for overgrowth syndrome. As well as these SNPs can be used for the larger population-based studies of overgrowth syndrome

Novel Mutations within PRSS1 Gene that Could Potentially Cause Hereditary Pancreatitis: Using Bioinformatics Approach

Hereditary pancreatitis (HP) is a rare heterogeneous disease with partial penetrance identified by frequent episodes of severe abdominal pain, often showing in young aged children. It is complicating by chronic pancreatitis, and high rate of pancreatic cancer (up to 40-50%). The aim of this work was to classify the most deleterious mutation in PRSS1 gene and to predict their influence on the functional and structural level by a variety of bioinformatics analysis tools. The raw data of PRSS1 gene were recovered from SNP database, and further used to examine a deleterious effect using SIFT, PolyPhen-2, PROVEAN, SNAP2, SNPs&GO, PHD-SNP, PANTHER and P-Mut. The functional analysis predicted that two SNPs “rs1366278558 and rs767036052” have a deleterious effect at functional level. Additionally, we submitted them to I-mutant 3.0, and MUPro respectively to investigate their effect on structural level; the two tools revealed that; two mutations have a dramatic decrease of the protein stability, thus suggesting that the M1R and L4P mutations of PRSS1  gene could destabilize the amino acid interactions causing functional abnormalities of PRSS1 protein. The 3D structure of PRSS1 was predicted by RaptorX and modeled using UCSF Chimera to compare the differences between the native and the mutant amino acids. From the comparative analysis at the functional and structural level, these two SNPs “M1R and L4P” have a deleterious effect and thus could be used as diagnostic markers to predict HP. These findings can be used as a platform to develop large-scale studies in the future

Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach

BACKGROUND: A new endemic disease has spread across Wuhan City, China, in December 2019. Within few weeks, the World Health Organization (WHO) announced a novel coronavirus designated as coronavirus disease 2019 (COVID-19). In late January 2020, WHO declared the outbreak of a “public-health emergency of international concern” due to the rapid and increasing spread of the disease worldwide. Currently, there is no vaccine or approved treatment for this emerging infection; thus, the objective of this study is to design a multiepitope peptide vaccine against COVID-19 using an immunoinformatics approach. METHOD: everal techniques facilitating the combination of the immunoinformatics approach and comparative genomic approach were used in order to determine the potential peptides for designing the T-cell epitope-based peptide vaccine using the envelope protein of 2019-nCoV as a target. RESULTS: Extensive mutations, insertion, and deletion were discovered with comparative sequencing in the COVID-19 strain. Additionally, ten peptides binding to MHC class I and MHC class II were found to be promising candidates for vaccine design with adequate world population coverage of 88.5% and 99.99%, respectively. CONCLUSION: The T-cell epitope-based peptide vaccine was designed for COVID-19 using the envelope protein as an immunogenic target. Nevertheless, the proposed vaccine rapidly needs to be validated clinically in order to ensure its safety and immunogenic profile to help stop this epidemic before it leads to devastating global outbreaks

Convalescent Plasma a Potential Therapy in Covid-19 Patients in Low Resource Setting: Rapid Review

Background: The COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At the time of writing, neither a cure nor a vaccine has been approved by the World health organization (WHO)  for this disease. Given the fact that the severe acute respiratory syndrome coronavirus  (SARS) and Middle East Respiratory Syndrome (MERS) viruses have a genetic sequencing similar to SARS-CoV-2, and since the use of convalescent plasma therapy (CP) has proved its efficacy in SARS and MERS virus infections, researchers are starting to focus more on it as a possible therapy for the COVID-19 disease. The main objective of this rapid review is to report and summarize the published evidence on the role of convalescent plasma therapy in the current COVID-19 pandemic. Method: The PICO method was used to establish the review question. Moreover, papers were gathered from PubMed and Google scholar, critically appraised for the best evidence. Piersons 5-component scheme was used to check the quality of the review papers. Results: After website screening: 10 papers in PubMed and 6 papers from Google scholars were retrieved. There were encouraging reports regarding the uses of CP in the previous viral outbreaks likes SARS and Ebola, yet there is still a doubt on the efficacy of this mode of therapy in the current COVID-19 pandemic. Conclusion: CP is a very promising treatment approach for COVID-19 patients; however, more clinical trials are required to validate the effectiveness of this therapy. Keywords: COVID-19, convalescent plasma therapy, SARS-CoV-2, therapy