Multiepitope Subunit Vaccine Design against COVID-19 Based on the Spike Protein of SARS-CoV-2: An In Silico Analysis

Comprehensive bioinformatics-based annotation and functional characterization of bovine chymosin protein revealed novel biological insights

Chymosin, an aspartic protease present in the stomachs of young ruminants like cows (bovine), causes milk coagulation and cheese production through the breakdown of κ-casein peptide bonds at the Met105-Phe106 site. Bovine chymosin is first synthesized as a pre-prochymosin that is cleaved to produce the mature chymosin protein. Despite significant strides in research, our understanding of this crucial enzyme remains incomplete. The purpose of this work was to perform in silico evolutionary and functional analysis and to gain unique insights into the structure of this protein. For this, the sequence of Bos taurus chymosin from UniProt database was subjected to various bioinformatics analyses. We found that bovine chymosin is a low molecular weight and hydrophilic protein that has homologs in other Bovidae species. Two active sites of aspartic peptidases, along with a functional domain, were identified. Gene Ontology analysis further confirmed chymosin's involvement in proteolysis and aspartic endopeptidase activity. Potential disordered residues and post-translational modification sites were also uncovered. It was revealed that the secondary structure of bovine chymosin is comprised of beta strands (44.27%), coils (43.65%), and alpha helices (12.07%). A highly optimized 3D structure was also obtained. Moreover, crucial protein-protein interactions were unveiled. Altogether, these findings provide valuable insights that could guide future research on bovine chymosin and its biological roles.

Recombinant multiepitope proteins expressed in Escherichia coli cells and their potential for immunodiagnosis

Recombinant multiepitope proteins (RMPs) are a promising alternative for application in diagnostic tests and, given their wide application in the most diverse diseases, this review article aims to survey the use of these antigens for diagnosis, as well as discuss the main points surrounding these antigens. RMPs usually consisting of linear, immunodominant, and phylogenetically conserved epitopes, has been applied in the experimental diagnosis of various human and animal diseases, such as leishmaniasis, brucellosis, cysticercosis, Chagas disease, hepatitis, leptospirosis, leprosy, filariasis, schistosomiasis, dengue, and COVID-19. The synthetic genes for these epitopes are joined to code a single RMP, either with spacers or fused, with different biochemical properties. The epitopes' high density within the RMPs contributes to a high degree of sensitivity and specificity. The RMPs can also sidestep the need for multiple peptide synthesis or multiple recombinant proteins, reducing costs and enhancing the standardization conditions for immunoassays. Methods such as bioinformatics and circular dichroism have been widely applied in the development of new RMPs, helping to guide their construction and better understand their structure. Several RMPs have been expressed, mainly using the Escherichia coli expression system, highlighting the importance of these cells in the biotechnological field. In fact, technological advances in this area, offering a wide range of different strains to be used, make these cells the most widely used expression platform. RMPs have been experimentally used to diagnose a broad range of illnesses in the laboratory, suggesting they could also be useful for accurate diagnoses commercially. On this point, the RMP method offers a tempting substitute for the production of promising antigens used to assemble commercial diagnostic kits.

Protein subunit vaccines: Promising frontiers against COVID-19

The emergence of COVID-19 has posed an unprecedented global health crisis, challenging the healthcare systems worldwide. Amidst the rapid development of several vaccine formulations, protein subunit vaccines have emerged as a promising approach. This article provides an in-depth evaluation of the role of protein subunit vaccines in the management of COVID-19. Leveraging viral protein fragments, particularly the spike protein from SARS-CoV-2, these vaccines elicit a targeted immune response without the risk of inducing disease. Notably, the robust safety profile of protein subunit vaccines makes them a compelling candidate in the management of COVID-19. Various innovative approaches, including reverse vaccinology, virus like particles, and recombinant modifications are incorporated to develop protein subunit vaccines. In addition, the utilization of advanced manufacturing techniques facilitates large-scale production, ensuring widespread distribution. Despite these advancements, challenges persist, such as the requirement for cold-chain storage and the necessity for booster doses. This article evaluates the formulation and applications of protein subunit vaccines, providing a comprehensive overview of their clinical development and approvals in the context of COVID-19. By addressing the current status and challenges, this review aims to contribute to the ongoing discourse on optimizing protein subunit vaccines for effective pandemic control.

Immunoinformatics-driven approach for development of potential multi-epitope vaccine against the secreted protein FlaC of Campylobacter jejuni

Campylobacter jejuni causes a leading human gastrointestinal infection which is associated with foodborne diarrhea, stomach cramping, and fever. In the recent years, numerous multidrug-resistant strains of C. jejuni has evolved and is considered in the priority pathogens category. Therefore, an increasing demand exists to develop an effective vaccine against Campylobacteriosis. The T cell and B cell epitopes from the FlaC protein were predicted using comprehensive immunoinformatics tools. The predicted epitopes were chosen based on their antigenicity, allergenicity, and toxicity profiles. Using the bioinformatics approach various physicochemical properties of the constructed vaccine were determined. The molecular docking analysis of the vaccine with the TLRs demonstrated that TLR5 has a higher binding affinity of -1159.0 kcal/mol. Molecular dynamics simulation has confirmed the stable association of the vaccine with TLR5. The immune response of the constructed vaccine was validated using immunostimulation. Based on this study, we recommend the formulation of a multi-epitope vaccine as a promising agent to effectively combat the dreadful campylobacteriosis infection.Communicated by Ramaswamy H. Sarma.

Immunoinformatics-guided approach for designing a pan-proteome multi-epitope subunit vaccine against African swine fever virus

Despite being identified over a hundred years ago, there is still no commercially available vaccine for the highly contagious and deadly African swine fever virus (ASFV). This study used immunoinformatics for the rapid and inexpensive designing of a safe and effective multi-epitope subunit vaccine for ASFV. A total of 18,858 proteins from 100 well-annotated ASFV proteomes were screened using various computational tools to identify potential epitopes, or peptides capable of triggering an immune response in swine. Proteins from genotypes I and II were prioritized for their involvement in the recent global ASFV outbreaks. The screened epitopes exhibited promising qualities that positioned them as effective components of the ASFV vaccine. They demonstrated antigenicity, immunogenicity, and cytokine-inducing properties indicating their ability to induce potent immune responses. They have strong binding affinities to multiple swine allele receptors suggesting a high likelihood of yielding more amplified responses. Moreover, they were non-allergenic and non-toxic, a crucial prerequisite for ensuring safety and minimizing any potential adverse effects when the vaccine is processed within the host. Integrated with an immunogenic 50S ribosomal protein adjuvant and linkers, the epitopes formed a 364-amino acid multi-epitope subunit vaccine. The ASFV vaccine construct exhibited notable immunogenicity in immune simulation and molecular docking analyses, and stable profiles in secondary and tertiary structure assessments. Moreover, this study designed an optimized codon for efficient translation of the ASFV vaccine construct into the Escherichia coli K-12 expression system using the pET28a(+) vector. Overall, both sequence and structural evaluations suggested the potential of the ASFV vaccine construct as a candidate for controlling and eradicating outbreaks caused by the pathogen.

COVID-19 associated Mucormycosis among ICU patients: risk factors, control, and challenges

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic is still difficult to be controlled. The spread of this virus and the emergence of new variants are considered a great challenge worldwide. Disturbance in infection control guidelines implementation, use of steroids, antibiotics, hospital crowdedness, and repeated use of oxygen masks during the management of critically ill COVID-19 patients lead to an increase in the rate of opportunistic infections. So, patients need to fight both the virus with its different variants and opportunistic pathogens including bacteria and fungi especially patients with diabetes mellitus, malignancy, or those who undergo hemodialysis and receive deferoxamine. During the pandemic, many cases of Mucormycosis associated with COVID-19 infection were observed in many countries. In this review, we discuss risk factors that increase the chance of infection by opportunistic pathogens, especially fungal pathogens, recent challenges, and control measures.

Design of multi-epitope based vaccine against Mycobacterium tuberculosis: a subtractive proteomics and reverse vaccinology based immunoinformatics approach

Tuberculosis is an airborne transmissible disease caused by Mycobacterium tuberculosis that infects millions of lives worldwide. There is still no single comprehensive therapy or preventative available for the lethal illness. Currently, the available vaccine, BCG is ineffectual in preventing the prophylactic adult pulmonary TB and reactivation of latent tuberculosis. Therefore, this investigation was intended to design a new multi-epitope vaccine that can address the existing problems. The subtractive proteomics approach was implemented to prioritize essential, virulence, druggable, and antigenic proteins as suitable vaccine candidates. Furthermore, a reverse vaccinology-based immunoinformatics technique was employed to identify potential B-cell, helper T lymphocytes (HTL), and cytotoxic T lymphocytes (CTL) epitopes from the target proteins. Immune-stimulating adjuvant, linkers, and PADRE (Pan HLA-DR epitopes) amino acid sequences along with the selected epitopes were used to construct a chimeric multi-epitope vaccine. The molecular docking and normal mode analysis (NMA) were carried out to evaluate the binding mode of the designed vaccine with different immunogenic receptors (MHC-I, MHC-II, and Tlr4). In addition, the MD simulation, followed by essential dynamics study and MMPBSA analysis, was carried out to understand the dynamics and stability of the complexes. In-silico cloning was accomplished using E.coli as an expression system to express the designed vaccine successfully. Finally, the immune simulation study has foreseen that our designed vaccine could induce a significant immune response by elevation of different immunoglobulins in the host. However, there is an imperative need for the experimental validation of the designed vaccine in animal models to confer effectiveness and safety.HIGHLIGHTSMulti-epitope based vaccine was designed against Mycobacterium tuberculosis using subtractive proteomics and Immunoinformatics approach.The vaccine was found to be antigenic, non-allergenic, immunogenic, and stable based on in-silico prediction.Population coverage analysis of the proposed vaccine predicts an effective response in the world population.The molecular docking, MD simulation, and MM-PBSA study confirm the stable interaction of the vaccine with immunogenic receptors.In silico cloning and immune simulation of the vaccine demonstrated its successful expression in E.coli and induction of immune response in the host. Communicated by Ramaswamy H. Sarma.

A study on the design of an in silico self-amplifying mRNA vaccine against Nipah virus using immunoinformatics

The scientific community continues to be impressed with RNA-based vaccines with great efficacy, quick synthesis and speed-to-market. The traditional vaccine may require large doses or repeat injections to achieve an expression for protection against the virus; the self-amplifying mRNA vaccine addresses this limitation. Therefore, a thorough examination of the most antigenic component of the Nipah virus was carried out to design the coding sequence of an antigen, which will provoke a virus-specific immune response. After that, we predicted and evaluated epitopes from NiV G-protein. We employed 8 HTL, 2 CTL and 3 B-cell epitopes. The study of structural compatibility was done by performing docking between HLA alleles and epitopes to get insights into the immune response of epitopes. The entire peptide coding sequence of an antigen was linked using a linker to design the structure of the vaccine. Physicochemical parameters of the designed vaccine constructs were assessed using a protparam server. Later, the vaccine sequence was converted into cDNA. We inserted a gene-expressing replicase at the start of a coding sequence for self-amplification. Next, to formulate the final version of vaccine signal sequences were added. Based on these findings, this mRNA vaccine appears to be a promising option against the Nipah virus.Communicated by Ramaswamy H. Sarma.

Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review

Reverse vaccinology (RV) is a promising alternative to traditional vaccinology. RV focuses on in silico methods to identify antigens or potential vaccine candidates (PVCs) from a pathogen's proteome. Researchers use VaxiJen, the most well-known RV tool, to predict PVCs for various pathogens. The purpose of this scoping review is to provide an overview of PVCs predicted by VaxiJen for different viruses between 2017 and 2021 using Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) guidelines. We used the term 'vaxijen' to search PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic. The protocol was registered at the Open Science Framework (OSF). We identified articles on this topic, charted them, and discussed the key findings. The database searches yielded 1033 articles, of which 275 were eligible. Most studies focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), published between 2020 and 2021. Only a few articles (8/275; 2.9%) conducted experimental validations to confirm the predictions as vaccine candidates, with 2.2% (6/275) articles mentioning recombinant protein expression. Researchers commonly targeted parts of the SARS-CoV-2 spike (S) protein, with the frequently predicted epitopes as PVCs being major histocompatibility complex (MHC) class I T cell epitopes WTAGAAAYY, RQIAPGQTG, IAIVMVTIM, and B cell epitope IAPGQTGKIADY, among others. The findings of this review are promising for the development of novel vaccines. We recommend that vaccinologists use these findings as a guide to performing experimental validation for various viruses, with SARS-CoV-2 as a priority, because better vaccines are needed, especially to stay ahead of the emergence of new variants. If successful, these vaccines could provide broader protection than traditional vaccines.

Designing a novel chimeric multi-epitope vaccine against Burkholderia pseudomallei, a causative agent of melioidosis

Burkholderia pseudomallei, a gram-negative soil-dwelling bacterium, is primarily considered a causative agent of melioidosis infection in both animals and humans. Despite the severity of the disease, there is currently no licensed vaccine on the market. The development of an effective vaccine against B. pseudomallei could help prevent the spread of infection. The purpose of this study was to develop a multi-epitope-based vaccine against B. pseudomallei using advanced bacterial pan-genome analysis. A total of four proteins were prioritized for epitope prediction by using multiple subtractive proteomics filters. Following that, a multi-epitopes based chimeric vaccine construct was modeled and joined with an adjuvant to improve the potency of the designed vaccine construct. The structure of the construct was predicted and analyzed for flexibility. A population coverage analysis was performed to evaluate the broad-spectrum applicability of B. pseudomallei. The computed combined world population coverage was 99.74%. Molecular docking analysis was applied further to evaluate the binding efficacy of the designed vaccine construct with the human toll-like receptors-5 (TLR-5). Furthermore, the dynamic behavior and stability of the docked complexes were investigated using molecular dynamics simulation, and the binding free energy determined for Vaccine-TLR-5 was delta total -168.3588. The docking result revealed that the vaccine construct may elicit a suitable immunological response within the host body. Hence, we believe that the designed in-silico vaccine could be helpful for experimentalists in the formulation of a highly effective vaccine for B. pseudomallei.

A novel vaccine based on SARS-CoV-2 CD4+ and CD8+ T cell conserved epitopes from variants Alpha to Omicron

COVID-19 caused, as of September, 1rst, 2022, 599,825,400 confirmed cases, including 6,469,458 deaths. Currently used vaccines reduced severity and mortality but not virus transmission or reinfection by different strains. They are based on the Spike protein of the Wuhan reference virus, which although highly antigenic suffered many mutations in SARS-CoV-2 variants, escaping vaccine-generated immune responses. Multiepitope vaccines based on 100% conserved epitopes of multiple proteins of all SARS-CoV-2 variants, rather than a single highly mutating antigen, could offer more long-lasting protection. In this study, a multiepitope multivariant vaccine was designed using immunoinformatics and in silico approaches. It is composed of highly promiscuous and strong HLA binding CD4⁺ and CD8⁺ T cell epitopes of the S, M, N, E, ORF1ab, ORF 6 and ORF8 proteins. Based on the analysis of one genome per WHO clade, the epitopes were 100% conserved among the Wuhan-Hu1, Alpha, Beta, Gamma, Delta, Omicron, Mµ, Zeta, Lambda and R1 variants. An extended epitope-conservancy analysis performed using GISAID metadata of 3,630,666 SARS-CoV-2 genomes of these variants and the additional genomes of the Epsilon, Lota, Theta, Eta, Kappa and GH490 R clades, confirmed the high conservancy of the epitopes. All but one of the CD4 peptides showed a level of conservation greater than 97% among all genomes. All but one of the CD8 epitopes showed a level of conservation greater than 96% among all genomes, with the vast majority greater than 99%. A multiepitope and multivariant recombinant vaccine was designed and it was stable, mildly hydrophobic and non-toxic. The vaccine has good molecular docking with TLR4 and promoted, without adjuvant, strong B and Th1 memory immune responses and secretion of high levels of IL-2, IFN-γ, lower levels of IL-12, TGF-β and IL-10, and no IL-6. Experimental in vivo studies should validate the vaccine’s further use as preventive tool with cross-protective properties.

Design of a Multiepitope Vaccine against Chicken Anemia Virus Disease

Chicken anemia virus (CAV) causes severe clinical and sub-clinical infection in poultry globally and thus leads to economic losses. The drawbacks of the commercially available vaccines against CAV disease signal the need for a novel, safe, and effective vaccine design. In this study, a multiepitope vaccine (MEV) consisting of T-cell and B-cell epitopes from CAV viral proteins (VP1 and VP2) was computationally constructed with the help of linkers and adjuvant. The 3D model of the MEV construct was refined and validated by different online bioinformatics tools. Molecular docking showed stable interaction of the MEV construct with TLR3, and this was confirmed by Molecular Dynamics Simulation. Codon optimization and in silico cloning of the vaccine in pET-28a (+) vector also showed its potential expression in the E. coli K12 system. The immune simulation also indicated the ability of this vaccine to induce an effective immune response against this virus. Although the vaccine in this study was computationally constructed and still requires further in vivo study to confirm its effectiveness, this study marks a very important step towards designing a potential vaccine against CAV disease.

Prevalence and Predictors of Persistent Symptoms After Clearance of SARS-CoV-2 Infection: A Multicenter Study from Egypt

Background and Aim

Little is known about the persistence of symptoms after clearance of SARS-CoV-2 infection. Our study aimed to assess persistent symptoms in COVID-19 patients after clearance of SARS-CoV-2 infection.

Methodology

A multi-center survey was conducted on first wave COVID-19 patients with confirmed SARS-CoV-2 infection. Sociodemographic and clinical characteristics, including presenting symptoms and persistent symptoms after viral clearance and possible factors contributing to persistence of such symptoms, were collected using an online multicomponent questionnaire. Descriptive and inferential statistical analysis was performed to detect the most persisting symptoms and factors contributing to their persistence.

Results

Overall, 538 patients were enrolled. Mean age was 41.17 (±SD 14.84), 54.1% were males, and 18.6% were smokers. Hypertension and diabetes were the most reported co-morbidities. Mild symptoms were reported in 61.3% of patients, 51.3% were admitted to hospital and 6.5% were admitted to the intensive care unit. Our study identified 49 types of persisting symptoms. Fatigue (59.1%), sense of fever (46.5%), anorexia (24.3%) and diarrhea (24.3%) were the most commonly reported persisting symptoms followed by loss of taste and smell (22.3%), headache (21.4%), cough (20.8) and dyspnea (21%). The use of hydroxychloroquine, azithromycin and multivitamins were significantly associated with persistence of symptoms (OR = 8.03, 8.89 and 10.12, respectively).

Conclusion

Our study revealed that in COVID-19 recovered patients, many patients reported persistence of at least one symptom, particularly fatigue and sense of fever. Follow-up of patients after discharge from hospital is recommended until complete resolution of symptoms.

Probing the Immune System Dynamics of the COVID-19 Disease for Vaccine Designing and Drug Repurposing Using Bioinformatics Tools

The pathogenesis of COVID-19 is complicated by immune dysfunction. The impact of immune-based therapy in COVID-19 patients has been well documented, with some notable studies on the use of anti-cytokine medicines. However, the complexity of disease phenotypes, patient heterogeneity and the varying quality of evidence from immunotherapy studies provide problems in clinical decision-making. This review seeks to aid therapeutic decision-making by giving an overview of the immunological responses against COVID-19 disease that may contribute to the severity of the disease. We have extensively discussed theranostic methods for COVID-19 detection. With advancements in technology, bioinformatics has taken studies to a higher level. The paper also discusses the application of bioinformatics and machine learning tools for the diagnosis, vaccine design and drug repurposing against SARS-CoV-2.

A contemporary review on the important role of in silico approaches for managing different aspects of COVID-19 crisis

In the last century, the emergence of in silico tools has improved the quality of healthcare studies by providing high quality predictions. In the case of COVID-19, these tools have been advantageous for bioinformatics analysis of SARS-CoV-2 structures, studying potential drugs and introducing drug targets, investigating the efficacy of potential natural product components at suppressing COVID-19 infection, designing peptide-mimetic and optimizing their structure to provide a better clinical outcome, and repurposing of the previously known therapeutics. These methods have also helped medical biotechnologists to design various vaccines; such as multi-epitope vaccines using reverse vaccinology and immunoinformatics methods, among which some of them have showed promising results through in vitro, in vivo and clinical trial studies. Moreover, emergence of artificial intelligence and machine learning algorithms have helped to classify the previously known data and use them to provide precise predictions and make plan for future of the pandemic condition. At this contemporary review, by collecting related information from the collected literature on valuable data sources; such as PubMed, Scopus, and Web of Science, we tried to provide a brief outlook regarding the importance of in silico tools in managing different aspects of COVID-19 pandemic infection and how these methods have been helpful to biomedical researchers.

SARS-CoV-2 subunit vaccine adjuvants and their signaling pathways

INTRODUCTION

Vaccines are the agreed upon weapon against the COVID-19 pandemic. This review discusses about COVID-19 subunit vaccines adjuvants and their signaling pathways, which could provide a glimpse into the selection of appropriate adjuvants for prospective vaccine development studies.

AREAS COVERED

In the introduction, a brief background about the SARS-CoV-2 pandemic, the vaccine development race and classes of vaccine adjuvants were provided. . The antigen, trial stage, and types of adjuvants were extracted from the included articles and thun assimilated. Finally, the pattern recognition receptors (PRRs), their classes, cognate adjuvants, and potential signaling pathways were comprehended.

EXPERT OPINION

Adjuvants are unsung heroes of subunit vaccines. The in silico studies are very vital in avoiding several costly trial errors and save much work times. The majority of the (pre)clinical studies are promising. It is encouraging that most of the selected adjuvants are novel. Much emphasis must be paid to the optimal paring of antigen-adjuvant-PRRs for obtaining the desired vaccine effect. A good subunit vaccine/adjuvant is one that has high efficacy, safety, dose sparing, and rapid seroconversion rate and broad spectrum of immune response. In the years to come, COVID-19 adjuvanted subunit vaccines are expected to have superior utility than any other vaccines for various reasons.

Expression of SARS-CoV-2 Spike Protein Receptor Binding Domain on Recombinant B. subtilis on Spore Surface: A Potential COVID-19 Oral Vaccine Candidate

Various types of vaccines, such as mRNA, adenovirus, and inactivated virus by injection, have been developed to prevent SARS-CoV-2 infection. Although some of them have already been approved under the COVID-19 pandemic, various drawbacks, including severe side effects and the requirement for sub-zero temperature storage, may hinder their applications. Bacillus subtilis (B. subtilis) is generally recognized as a safe and endotoxin-free Gram-positive bacterium that has been extensively employed as a host for the expression of recombinant proteins. Its dormant spores are extraordinarily resistant to the harsh environment in the gastrointestinal tract. This feature makes it an ideal carrier for oral administration in resisting this acidic environment and for release in the intestine. In this study, an engineered B. subtilis spore expressing the SARS-CoV-2 spike protein receptor binding domain (sRBD) on the spore surface was developed. In a pilot test, no adverse health event was observed in either mice or healthy human volunteers after three oral courses of B. subtilis spores. Significant increases in neutralizing antibody against sRBD, in both mice and human volunteers, after oral administration were also found. These findings may enable the further clinical developments of B. subtilis spores as an oral vaccine candidate against COVID-19 in the future.

In Silico Modeling as a Perspective in Developing Potential Vaccine Candidates and Therapeutics for COVID-19

The potential of computational models to identify new therapeutics and repurpose existing drugs has gained significance in recent times. The current ‘COVID-19’ pandemic caused by the new SARS CoV2 virus has affected over 200 million people and caused over 4 million deaths. The enormity and the consequences of this viral infection have fueled the research community to identify drugs or vaccines through a relatively expeditious process. The availability of high-throughput datasets has cultivated new strategies for drug development and can provide the foundation towards effective therapy options. Molecular modeling methods using structure-based or computer-aided virtual screening can potentially be employed as research guides to identify novel antiviral agents. This review focuses on in-silico modeling of the potential therapeutic candidates against SARS CoVs, in addition to strategies for vaccine design. Here, we particularly focus on the recently published SARS CoV main protease (Mpro) active site, the RNA-dependent RNA polymerase (RdRp) of SARS CoV2, and the spike S-protein as potential targets for vaccine development. This review can offer future perspectives for further research and the development of COVID-19 therapies via the design of new drug candidates and multi-epitopic vaccines and through the repurposing of either approved drugs or drugs under clinical trial.

The impact of spike mutated variants of SARS-CoV2 [Alpha, Beta, Gamma, Delta, and Lambda] on the efficacy of subunit recombinant vaccines

Since the first described human infection with SARS-CoV-2 in December of 2019 many subunit protein vaccines have been proposed for use in humans. Subunit vaccines use one or more antigens suitable for eliciting a robust immune response. However, the major concern is the efficacy of subunit vaccines and elicited antibodies to neutralize the variants of SARS-CoV-2 like B.1.1.7 (Alpha), B.1.351 (Beta) and P1 (Gamma), B.1.617 (Delta) and C.37 (Lambda). The Spike protein (S) is a potential fragment for use as an antigen in vaccine development. This protein plays a crucial role in the first step of the infection process, as it binds to Angiotensin-Converting Enzyme 2 (ACE2) receptor and enters the host cell after binding. Immunization-induced specific antibodies against the receptor binding domain (RBD) may block and effectively prevent virus invasion. The focus of this review is the impact of spike mutated variants of SARS-CoV2 (Alpha, Beta, Gamma, Delta, and Lambda) on the efficacy of subunit recombinant vaccines. To date, a low or no significant impact on vaccine efficacy against Alpha and Delta variants has been reported. Such an impact on vaccine efficacy for Beta, Delta, Gamma, and Lambda variants may be even greater compared to the Alpha variant. Nonetheless, more comprehensive analyses are needed to assess the real impact on vaccine efficacy brought about by SARS-CoV-2 variants.

COVID-19 and Diabetes Mellitus: A Complex Interplay

COVID-19 pandemic, which caused by the newly emerged severe acute respiratory syndrome coronavirus-2 (SARS- CoV-2), puts the entire world in an unprecedented crisis, leaving behind huge human losses and serious socio-economical damages. The clinical spectrum of COVID-19 varies from asymptomatic to multi-organ manifestations. Diabetes mellitus (DM) is a chronic inflammatory condition, which associated with metabolic and vascular abnormalities, increases the risk for SARS-CoV-2 infection, severity and mortality. Due to global prevalence, DM effect on COVID-19 outcomes as well as the potential mechanisms by which DM modulates the host-viral interactions and host-immune responses are discussed in this review. This review also highlights the effects of anti-diabetic drugs on treatment of SARS-CoV-2 infection and vice versa.

Current and prospective computational approaches and challenges for developing COVID-19 vaccines

SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses.

Identification of Highly Conserved SARS-CoV-2 Antigenic Epitopes with Wide Coverage Using Reverse Vaccinology Approach

One of the most effective strategies for eliminating new and emerging infectious diseases is effective immunization. The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) warrants the need for a maximum coverage vaccine. Moreover, mutations that arise within the virus have a significant impact on the vaccination strategy. Here, we built a comprehensive in silico workflow pipeline to identify B-cell- and T-cell-stimulating antigens of SARS-CoV-2 viral proteins. Our in silico reverse vaccinology (RV) approach consisted of two parts: (1) analysis of the selected viral proteins based on annotated cellular location, antigenicity, allele coverage, epitope density, and mutation density and (2) analysis of the various aspects of the epitopes, including antigenicity, allele coverage, IFN-γ induction, toxicity, host homology, and site mutational density. After performing a mutation analysis based on the contemporary mutational amino acid substitutions observed in the viral variants, 13 potential epitopes were selected as subunit vaccine candidates. Despite mutational amino acid substitutions, most epitope sequences were predicted to retain immunogenicity without toxicity and host homology. Our RV approach using an in silico pipeline may potentially reduce the time required for effective vaccine development and can be applicable for vaccine development for other pathogenic diseases as well.

BCG Vaccine-Induced Trained Immunity and COVID-19: Protective or Bystander?

In late 2019, a new virulent coronavirus (CoV) emerged in Wuhan, China and was named as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This virus spread rapidly, causing the coronavirus disease-2019 (COVID-19) pandemic. Bacillus Calmette-Guérin (BCG) is a live attenuated tuberculosis (TB) vaccine, associated with induction of non-specific cross-protection against unrelated infections. This protection is a memory-like response in innate immune cells (trained immunity), which is caused by epigenetic reprogramming via histone modification in the regulatory elements of specific genes in monocytes. COVID-19 related epidemiological studies showed an inverse relationship between national BCG vaccination policies and COVID-19 incidence and death, suggesting that BCG may induce trained immunity that could confer some protection against SARS-CoV-2. As this pandemic has put most of Earth's population under quarantine, repurposing of the old, well-characterized BCG may ensure some protection against COVID-19. This review focuses on BCG-related cross-protection and acquisition of trained immunity, as well as the correlation between BCG vaccination and COVID-19 incidence and mortality.

Structure-Based Virtual Screening Identifies Multiple Stable Binding Sites at the RecA Domains of SARS-CoV-2 Helicase Enzyme

With the emergence and global spread of the COVID-19 pandemic, the scientific community worldwide has focused on search for new therapeutic strategies against this disease. One such critical approach is targeting proteins such as helicases that regulate most of the SARS-CoV-2 RNA metabolism. The purpose of the current study was to predict a library of phytochemicals derived from diverse plant families with high binding affinity to SARS-CoV-2 helicase (Nsp13) enzyme. High throughput virtual screening of the Medicinal Plant Database for Drug Design (MPD3) database was performed on SARS-CoV-2 helicase using AutoDock Vina. Nilotinib, with a docking value of -9.6 kcal/mol, was chosen as a reference molecule. A compound (PubChem CID: 110143421, ZINC database ID: ZINC257223845, eMolecules: 43290531) was screened as the best binder (binding energy of -10.2 kcal/mol on average) to the enzyme by using repeated docking runs in the screening process. On inspection, the compound was disclosed to show different binding sites of the triangular pockets collectively formed by Rec1A, Rec2A, and 1B domains and a stalk domain at the base. The molecule is often bound to the ATP binding site (referred to as binding site 2) of the helicase enzyme. The compound was further discovered to fulfill drug-likeness and lead-likeness criteria, have good physicochemical and pharmacokinetics properties, and to be non-toxic. Molecular dynamic simulation analysis of the control/lead compound complexes demonstrated the formation of stable complexes with good intermolecular binding affinity. Lastly, affirmation of the docking simulation studies was accomplished by estimating the binding free energy by MMPB/GBSA technique. Taken together, these findings present further in silco investigation of plant-derived lead compounds to effectively address COVID-19.