Immunoinformatics-aided design of a new multi-epitope vaccine adjuvanted with domain 4 of pneumolysin against Streptococcus pneumoniae strains.

BACKGROUND: Streptococcus pneumoniae (Pneumococcus) has remained a leading cause of fatal infections such as pneumonia, meningitis, and sepsis. Moreover, this pathogen plays a major role in bacterial co-infection in patients with life-threatening respiratory virus diseases such as influenza and COVID-19. High morbidity and mortality in over one million cases, especially in very young children and the elderly, are the main motivations for pneumococcal vaccine development. Due to the limitations of the currently marketed polysaccharide-based vaccines, non-serotype-specific protein-based vaccines have received wide research interest in recent years. One step further is to identify high antigenic regions within multiple highly-conserved proteins in order to develop peptide vaccines that can affect various stages of pneumococcal infection, providing broader serotype coverage and more effective protection. In this study, immunoinformatics tools were used to design an effective multi-epitope vaccine in order to elicit neutralizing antibodies against multiple strains of pneumococcus. RESULTS: The B- and T-cell epitopes from highly protective antigens PspA (clades 1-5) and PhtD were predicted and immunodominant peptides were linked to each other with proper linkers. The domain 4 of Ply, as a potential TLR4 agonist adjuvant candidate, was attached to the end of the construct to enhance the immunogenicity of the epitope vaccine. The evaluation of the physicochemical and immunological properties showed that the final construct was stable, soluble, antigenic, and non-allergenic. Furthermore, the protein was found to be acidic and hydrophilic in nature. The protein 3D-structure was built and refined, and the Ramachandran plot, ProSA-web, ERRAT, and Verify3D validated the quality of the final model. Molecular docking analysis showed that the designed construct via Ply domain 4 had a strong interaction with TLR4. The structural stability of the docked complex was confirmed by molecular dynamics. Finally, codon optimization was performed for gene expression in E. coli, followed by in silico cloning in the pET28a(+) vector. CONCLUSION: The computational analysis of the construct showed acceptable results, however, the suggested vaccine needs to be experimentally verified in laboratory to ensure its safety and immunogenicity.

Expression, purification, and study on the efficiency of a new potent recombinant scFv antibody against the SARS-CoV-2 spike RBD in E. coli BL21.

Many efforts have been made around the world to combat SARS-CoV-2. Among these are recombinant antibodies considered to be suitable as an alternative for some diagnostics/therapeutics. Based on their importance, this study aimed to investigate the expression, purification, and efficiency of a new potent recombinant scFv in the E. coli BL21 (DE3) system. The expression studies were performed after confirming the scFv cloning into the pET28a vector using specific PCRs. After comprehensive expression studies, a suitable strategy was adopted to extract and purify periplasmic proteins using Ni2+-NTA resin. Besides the purified scFv, the crude bacterial lysate was also used to develop a sandwich ELISA (S-ELISA) for the detection of SARS-CoV-2. The use of PCR, E. coli expression system, western blotting (WB), and S-ELISA confirmed the functionality of this potent scFv. Moreover, the crude bacterial lysate also showed good potential for detecting SARS-CoV-2. This could be decreasing the costs and ease its utilization for large-scale applications. The production of high-quality recombinant proteins is essential for humankind. Moreover, with attention to the more aggressive nature of SARS-CoV-2 than other coronaviruses, the development of an effective detection method is urgent. Based on our knowledge, this study is one of the limited investigations in two fields: (1) The production of anti-SARS-CoV-2 scFv using E. coli [as a cheap heterologous host] in relatively high amounts and with good stability, and (2) Designing a sensitive S-ELISA for its detection. It may also be utilized as potent therapeutics after further investigations.

Association of Clinical Features with Spike Glycoprotein Mutations in Iranian COVID-19 Patients.

BACKGROUND: Mutations in spike glycoprotein, a critical protein of SARS-CoV-2, could directly impact pathogenicity and virulence. The D614G mutation, a non-synonymous mutation at position 614 of the spike glycoprotein, is a predominant variant circulating worldwide. This study investigated the occurrence of mutations in the crucial zone of the spike gene and the association of clinical symptoms with spike mutations in isolated viruses from Iranian patients infected with SARS-CoV-2 during the second and third waves of the COVID-19 epidemic in Isfahan, the third-largest city in Iran. METHODS: The extracted RNA from 60 nasopharyngeal samples of COVID-19 patients were subjected to cDNA synthesis and RT-PCR (in three overlapping fragments). Each patient's reverse transcriptase polymerase chain reaction (RT-PCR) products were assembled and sequenced. Information and clinical features of all sixty patients were collected, summarized, and analyzed using the GENMOD procedure of SAS 9.4. RESULTS: Analysis of 60 assembled sequences identified nine nonsynonymous mutations. The D614G mutation has the highest frequency among the amino acid changes. In our study, in 31 patients (51.66%), D614G mutation was determined. For all the studied symptoms, no significant relationship was observed with the incidence of D614G mutation. CONCLUSIONS: D614G, a common mutation among several of the variants of SARS-CoV-2, had the highest frequency among the studied sequences and its frequency increased significantly in the samples of the third wave compared to the samples of the second wave of the disease.

In silico designing of a novel epitope-based candidate vaccine against Streptococcus pneumoniae with introduction of a new domain of PepO as adjuvant.

BACKGROUND: Streptococcus pneumoniae is the leading reason for invasive diseases including pneumonia and meningitis, and also secondary infections following viral respiratory diseases such as flu and COVID-19. Currently, serotype-dependent vaccines, which have several insufficiency and limitations, are the only way to prevent pneumococcal infections. Hence, it is plain to need an alternative effective strategy for prevention of this organism. Protein-based vaccine involving conserved pneumococcal protein antigens with different roles in virulence could provide an eligible alternative to existing vaccines. METHODS: In this study, PspC, PhtD and PsaA antigens from pneumococcus were taken to account to predict B-cell and helper T-cell epitopes, and epitope-rich regions were chosen to build the construct. To enhance the immunogenicity of the epitope-based vaccine, a truncated N-terminal fragment of pneumococcal endopeptidase O (PepO) was used as a potential TLR2/4 agonist which was identified by molecular docking studies. The ultimate construct was consisted of the chosen epitope-rich regions, along with the adjuvant role (truncated N-PepO) and suitable linkers. RESULTS: The epitope-based vaccine was assessed as regards physicochemical properties, allergenicity, antigenicity, and toxicity. The 3D structure of the engineered construct was modeled, refined, and validated. Molecular docking and simulation of molecular dynamics (MD) indicated the proper and stable interactions between the vaccine and TLR2/4 throughout the simulation periods. CONCLUSIONS: For the first time this work presents a novel vaccine consisting of epitopes of PspC, PhtD, and PsaA antigens which is adjuvanted with a new truncated domain of PepO. The computational outcomes revealed that the suggested vaccine could be deemed an efficient therapeutic vaccine for S. pneumoniae; nevertheless, in vitro and in vivo examinations should be performed to prove the potency of the candidate vaccine.

Mesenchymal Stem Cells in the Treatment of New Coronavirus Pandemic: A Novel Promising Therapeutic Approach.

After severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) outbreaks, coronavirus disease 2019 (COVID-19) is the third coronavirus epidemic that soon turned into a pandemic. This virus causes acute respiratory syndrome in infected people. The mortality rate of SARS-CoV-2 infection will probably rise unless efficient treatments or vaccines are developed. The global funding and medical communities have started performing more than five hundred clinical examinations on a broad spectrum of repurposed drugs to acquire effective treatments. Besides, other novel treatment approaches have also recently emerged, including cellular host-directed therapies. They counteract the unwanted responses of the host immune system that led to the severe pathogenesis of SARS-CoV-2. This brief review focuses on mesenchymal stem cell (MSC) principles in treating the COVID-19. The US clinical trials database and the world health organization database for clinical trials have reported 82 clinical trials (altogether) exploring the effects of MSCs in COVID-19 treatment. MSCs also had better be tried for treating other pathogens worldwide. MSC treatment may have the potential to end the high mortality rate of COVID-19. Besides, it also limits the long-term inability of survivors.

In-silico design of a multi-epitope for developing sero-diagnosis detection of SARS-CoV-2 using spike glycoprotein and nucleocapsid antigens.

COVID-19 is a pandemic disease caused by novel corona virus, SARS-CoV-2, initially originated from China. In response to this serious life-threatening disease, designing and developing more accurate and sensitive tests are crucial. The aim of this study is designing a multi-epitope of spike and nucleocapsid antigens of COVID-19 virus by bioinformatics methods. The sequences of nucleotides obtained from the NCBI Nucleotide Database. Transmembrane structures of proteins were predicted by TMHMM Server and the prediction of signal peptide of proteins was performed by Signal P Server. B-cell epitopes' prediction was performed by the online prediction server of IEDB server. Beta turn structure of linear epitopes was also performed using the IEDB server. Conformational epitope prediction was performed using the CBTOPE and eventually, eight antigenic epitopes with high physicochemical properties were selected, and then, all eight epitopes were blasted using the NCBI website. The analyses revealed that α-helices, extended strands, ß-turns, and random coils were 28.59%, 23.25%, 3.38%, and 44.78% for S protein, 21.24%, 16.71%, 6.92%, and 55.13% for N Protein, respectively. The S and N protein three-dimensional structure was predicted using the prediction I-TASSER server. In the current study, bioinformatics tools were used to design a multi-epitope peptide based on the type of antigen and its physiochemical properties and SVM method (Machine Learning) to design multi-epitopes that have a high avidity against SARS-CoV-2 antibodies to detect infections by COVID-19.

Vaccine design and delivery approaches for COVID-19.

COVID-19 is still a deadly disease that remains yet a major challenge for humans. In recent times, many large pharmaceutical and non-pharmaceutical companies have invested a lot of time and cost in fighting this disease. In this regard, today's scientific knowledge shows that designing and producing an effective vaccine is the best possible way to diminish the disease burden and dissemination or even eradicate the disease. Due to the urgent need, many vaccines are now available earlier than scheduled. New technologies have also helped to produce much more effective vaccines, although the potential side effects must be taken into account. Thus, in this review, the types of vaccines and vaccine designs made against COVID-19, the vaccination programs, as well as the delivery methods and molecules that have been used to deliver some vaccines that need a carrier will be described.

Stability of SARS-CoV-2 as consequence of heating and microwave processing in meat products and bread.

The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that was first found in 2019 in Wuhan, China, caused coronavirus disease 2019 (COVID-19). It then spread worldwide rapidly, causing the 2019-2020 coronavirus pandemic. To date, it has been indicated that various transmission ways might be participated in outbreaks of COVID-19. Among these, food products, whether raw or processed, might be carriers for SARS-CoV-2. Therefore, this study was aimed to evaluate the effect of cooking and microwave process of meat products and bread on the stability of SARS-CoV-2. In this regard, sausages and hamburger as meat products and toast bread were inoculated with a viral load of 5.70 log fifty percent tissue culture infective dose (TCID50)/mL in order to create a simulated cross-contamination condition. The results showed that frying of hamburger at 225ºC for about either 6 or 10 min resulted in complete inactivation of SARS-CoV-2. Furthermore, a 5-log decrease in SARS-CoV-2 load was observed in sausages as a consequence of cooking process at 78ºC for either 20 or 30 min. Additionally, the effect of microwave oven at power of 630 watt on stability of SARS-CoV-2 showed that exposing toast bread for either 30 s or 1 min in this power led to a 5-log decrease in SARS-CoV-2 load in the toast bread.

Stability of severe acute respiratory syndrome coronavirus 2 in dairy products.

The present investigation was performed to determine the stability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) under several industrial processing situations in dairies, including pasteurization, freezing, and storage in acidic conditions. Ten treatments were selected, including high-temperature short-time (HTST)-pasteurized low-fat milk, low-temperature long-time-pasteurized low-fat milk, extended shelf life (ESL)-pasteurized low-fat milk, HTST-pasteurized full-fat milk, LTLT-pasteurized full-fat milk, ESL-pasteurized full-fat milk, pasteurized cream, ice cream frozen and stored at -20 or -80°C, and Doogh (as a fermented milk drink with initial pH < 3.5) refrigerated for 28 days. The viral particles were quantified by RT-PCR methodology. Besides, the virus infectivity was assessed through fifty-percent tissue culture infective dose (TCID50) assay. These products were seeded with a viral load of 5.65 log TCID50/mL as a simulated cross-contamination condition. Pasteurization techniques were sufficient for complete inactivation of the SARS-CoV-2 in the most dairy products, and 1.85 log TCID50/mL virus reduction in full-fat milk (fat content = 3.22%). Freezing (either -20°C or -80°C) did not result in a virally safe product within 60 days of storage. Storage at high acidic conditions (initial pH < 3.5) completely hampered the viral load at the end of 28 days of refrigerated storage. This research represents an important practical achievement that the routine HTST pasteurization in dairies was inadequate to completely inactivate the viral load in full-fat milk, probably due to the protective effect of fat content. Furthermore, freezing retain the virus infectivity in food products, and therefore, relevant contaminated foods may act as carriers for SARS-CoV-2.

Computational Design of a Potential Therapeutic Peptide Against Spike Protein of SARS-CoV-2

SARS-CoV-2 entrance to the host cells is started by the interaction between receptor binding domain (RBD) of the spike (S) protein on the virus with the angiotensin-converting enzyme 2 (ACE2) receptor which is very important in the onset of viral infection. Interference with this interaction can be a promising way to prevent Covid-19 infection. In this study, a novel potential therapeutic peptide was designed in silico based on the key interacting amino acids of ACE2 against SARS-CoV-2 S protein. In our computational analysis, a peptide consisting of residues 19–48 of ACE2 was chosen as the wild-type peptide. Based on this peptide, six mutant peptides (Mu_P1-6) were designed and then assessed in term of interaction with S protein. The result of protein-peptide docking by HADDOCK web server and then immunological analysis by SVMTriP epitope prediction tool leads to choose Mu_P3 as the best mutant. Molecular dynamics simulations of wild-type peptide-S protein complex and Mu_P3-S protein complex, showed Mu_P3 has better interaction with S protein than wild type peptide (interaction energies − 8 9 7. 1 4 vs. − 7 8 4. 1 3 (kJ/mol)) which can be a potential therapeutic peptide for Covid-19 pandemic. The aim of this study was in silico design of a therapeutic peptide against SARS-CoV-2 S protein. Six mutant peptides (Mu_P1-6) were designed and then their interaction potential with S protein was assessed by molecular docking and molecular dynamics which Mu_P3 showed the properties of a potential therapeutic peptide. [ABSTRACT FROM AUTHOR] Copyright of Journal of Computational Biophysics & Chemistry is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Novel and emerging mutations of SARS-CoV-2: Biomedical implications.

Coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The SARS-CoV-2 virus strains has geographical diversity associated with diverse severity, mortality rate, and response to treatment that were characterized using phylogenetic network analysis of SARS-CoV-2 genomes. Although, there is no explicit and integrative explanation for these variations, the genetic arrangement, and stability of SARS-CoV-2 are basic contributing factors to its virulence and pathogenesis. Hence, understanding these features can be used to predict the future transmission dynamics of SARS-CoV-2 infection, drug development, and vaccine. In this review, we discuss the most recent findings on the mutations in the SARS-CoV-2, which provide valuable information on the genetic diversity of SARS-CoV-2, especially for DNA-based diagnosis, antivirals, and vaccine development for COVID-19.

Identification of FDA approved drugs against SARS-CoV-2 RNA dependent RNA polymerase (RdRp) and 3-chymotrypsin-like protease (3CLpro), drug repurposing approach.

The RNA-dependent RNA polymerase (RdRp) and 3C-like protease (3CLpro) from SARS-CoV-2 play crucial roles in the viral life cycle and are considered the most promising targets for drug discovery against SARS-CoV-2. In this study, FDA-approved drugs were screened to identify the probable anti-RdRp and 3CLpro inhibitors by molecular docking approach. The number of ligands selected from the PubChem database of NCBI for screening was 1760. Ligands were energy minimized using Open Babel. The RdRp and 3CLpro protein sequences were retrieved from the NCBI database. For Homology Modeling predictions, we used the Swiss model server. Their structure was then energetically minimized using SPDB viewer software and visualized in the CHIMERA UCSF software. Molecular dockings were performed using AutoDock Vina, and candidate drugs were selected based on binding affinity (∆G). Hydrogen bonding and hydrophobic interactions between ligands and proteins were visualized using Ligplot and the Discovery Studio Visualizer v3.0 software. Our results showed 58 drugs against RdRp, which had binding energy of - 8.5 or less, and 69 drugs to inhibit the 3CLpro enzyme with a binding energy of - 8.1 or less. Six drugs based on binding energy and number of hydrogen bonds were chosen for the next step of molecular dynamics (MD) simulations to investigate drug-protein interactions (including Nilotinib, Imatinib and dihydroergotamine for 3clpro and Lapatinib, Dexasone and Relategravir for RdRp). Except for Lapatinib, other drugs-complexes were stable during MD simulation. Raltegravir, an anti-HIV drug, was observed to be the best compound against RdRp based on docking binding energy (-9.5 kcal/mole) and MD results. According to the MD results and binding energy, dihydroergotamine is a suitable candidate for 3clpro inhibition (-9.6 kcal/mol). These drugs were classified into several categories, including antiviral, antibacterial, anti-inflammatory, anti-allergic, cardiovascular, anticoagulant, BPH and impotence, antipsychotic, antimigraine, anticancer, and so on. The common prescription-indications for some of these medication categories appeared somewhat in line with manifestations of COVID-19. We hope that they can be beneficial for patients with certain specific symptoms of SARS-CoV-2 infection, but they can also probably inhibit viral enzymes. We recommend further experimental evaluations in vitro and in vivo on these FDA-approved drugs to assess their potential antiviral effect on SARS-CoV-2.

Current status of COVID-19 pandemic; characteristics, diagnosis, prevention, and treatment.

Humans have always been encountered to big infectious diseases outbreak throughout the history. In December 2019, novel coronavirus (COVID-19) was first noticed as an agent causing insidious pneumonia in Wuhan, China. COVID-19 was spread rapidly from Wuhan to the rest of the world. Until late June 2020, it infected more than 10,000,000 people and caused more than 500,000 deaths in almost all of countries in the world, creating a global crisis worse than all previous epidemics and pandemics. In the current review, we gathered and summarized the results of various studies on characteristics, diagnosis, treatment, and prevention of this pandemic crisis.