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

Exploring the Power and Promise of In Silico Clinical Trials with Application in COVID-19 Infection

Background: COVID-19 pandemic has dramatically engulfed the world causing catastrophic damage to human society. Several therapeutic and vaccines have been suggested for the disease in the past months, with over 150 clinical trials currently running or under process. Nevertheless, these trials are extremely expensive and require a long time, which presents the need for alternative cost-effective methods to tackle this urgent requirement for validated therapeutics and vaccines. Bearing this in mind, here we assess the use of in silico clinical trials as a significant development in the field of clinical research, which holds the possibility to reduce the time and cost needed for clinical trials on COVID-19 and other diseases. Methods: Using the PubMed database, we analyzed six relevant scientific articles regarding the possible application of in silico clinical trials in testing the therapeutic and investigational methods of managing different diseases. Results: Successful use of in silico trials was observed in many of the reviewed evidence. Conclusion: In silico clinical trials can be used in refining clinical trials for COVID-19 infection. Keywords: in silico, clinical trials, COVID-19, SARS-CoV-2, vaccine Ho

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

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

Exploring the Power and Promise of In Silico Clinical Trials with Application in COVID-19 Infection

Background: COVID-19 pandemic has dramatically engulfed the world causing catastrophic damage to human society. Several therapeutic and vaccines have been suggested for the disease in the past months, with over 150 clinical trials currently running or under process. Nevertheless, these trials are extremely expensive and require a long time, which presents the need for alternative cost-effective methods to tackle this urgent requirement for validated therapeutics and vaccines. Bearing this in mind, here we assess the use of in silico clinical trials as a significant development in the field of clinical research, which holds the possibility to reduce the time and cost needed for clinical trials on COVID-19 and other diseases.Methods: Using the PubMed database, we analyzed six relevant scientific articles regarding the possible application of in silico clinical trials in testing the therapeutic and investigational methods of managing different diseases.Results: Successful use of in silico trials was observed in many of the reviewed evidence.Conclusion: In silico clinical trials can be used in refining clinical trials for COVID-19 infection

Exploring the Power and Promise of in Silico Clinical Trials with Application in COVID-19 Infection

Background: COVID-19 pandemic has dramatically engulfed the world causing catastrophic damage to human society. Several therapeutic and vaccines have been suggested for the disease in the past months, with over 150 clinical trials currently running or under process. Nevertheless, these trials are extremely expensive and require a long time, which presents the need for alternative cost-effective methods to tackle this urgent requirement for validated therapeutics and vaccines. Bearing this in mind, here we assess the use of in silico clinical trials as a significant development in the field of clinical research, which holds the possibility to reduce the time and cost needed for clinical trials on COVID-19 and other diseases. Methods: Using the PubMed database, we analyzed six relevant scientific articles regarding the possible application of in silico clinical trials in testing the therapeutic and investigational methods of managing different diseases. Results: Successful use of in silico trials was observed in many of the reviewed evidence. Conclusion: In silico clinical trials can be used in refining clinical trials for COVID-19 infection. Keywords: in silico, clinical trials, COVID-19, SARS-CoV-2, vaccine Ho

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

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