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

Overview of SARS-CoV-2 genome-encoded proteins

Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) has spread rapidly throughout the world. SARS-CoV-2 is an enveloped, plus-stranded RNA virus with a single-stranded RNA genome of approximately 30,000 nucleotides. The SARS-CoV-2 genome encodes 29 proteins, including 16 nonstructural, 4 structural and 9 accessory proteins. To date, over 1,228 experimental structures of SARS-CoV-2 proteins have been deposited in the Protein Data Bank (PDB), including 16 protein structures, two functional domain structures of nucleocapsid (N) protein, and scores of complexes. Overall, they exhibit high similarity to SARS-CoV proteins. Here, we summarize the progress of structural and functional research on SARS-CoV-2 proteins. These studies provide structural and functional insights into proteins of SARS-CoV-2, and further elucidate the daedal relationship between different components at the atomic level in the viral life cycle, including attachment to the host cell, viral genome replication and transcription, genome packaging and assembly, and virus release. It is important to understand the structural and functional properties of SARS-CoV-2 proteins as it will facilitate the development of anti-CoV drugs and vaccines to prevent and control the current SARS-CoV-2 pandemic.

Exploring peptide studies related to SARS-CoV to accelerate the development of novel therapeutic and prophylactic solutions against COVID-19

Recent advances in peptide research revolutionized therapeutic discoveries for various infectious diseases. In view of the ongoing threat of the COVID-19 pandemic, there is an urgent need to develop potential therapeutic options. Intense and accomplishing research is being carried out to develop broad-spectrum vaccines and treatment options for corona viruses, due to the risk of recurrent infection by the existing strains or pandemic outbreaks by new mutant strains. Developing a novel medicine is costly and time consuming, which increases the value of repurposing existing therapies. Since, SARS-CoV-2 shares significant genomic homology with SARS-CoV, we have summarized various peptides identified against SARS-CoV using in silico and molecular studies and also the peptides effective against SARS-CoV-2. Dissecting the molecular mechanisms underlying viral infection could yield fundamental insights in the discovery of new antiviral agents, targeting viral proteins or host factors. We postulate that these peptides can serve as effective components for therapeutic options against SARS-CoV-2, supporting clinical scientists globally in selectively identifying and testing the therapeutic and prophylactic agents for COVID-19 treatment. In addition, we also summarized the latest updates on peptide therapeutics against SARS-CoV-2.

Current Perspectives in the Discovery of Newer Medications Against the Outbreak of COVID-19

A rapid and increasing spread of COVID-19 pandemic disease has been perceived worldwide in 2020. The current COVID-19 disease outbreak is due to the spread of SARS-CoV-2. SARS-CoV-2 is a new strain of coronavirus that has spike protein on the envelope. The spike protein of the virus binds with the ACE-2 receptor of the human lungs surface for entering into the host. Therefore, the blocking of viral entry into the host by targeting the spike protein has been suggested to be a valid strategy to treat COVID-19. The patients of COVID-19 were found to be asymptomatic, cold, mild to severe respiratory illness, and leading to death. The severe illness has been noted mainly in old age people, cardiovascular disease patients, and respiratory disease patients. However, the long-term health effects due to COVID-19 are not yet known. Recently, the vaccines were authorized to protect from COVID-19. However, the researchers have put an effort to discover suitable targets and newer medications in the form of small molecules or peptides, based on in-silico methods and synthetic approaches. This manuscript describes the current perspectives of the causative agent, diagnostic procedure, therapeutic targets, treatment, clinical trials, and development of potential clinical candidates of COVID-19. The study will be useful to identify the potential newer medications for the treatment of COVID-19.

New Computational Approach for Peptide Vaccine Design Against SARS-COV-2

The design for vaccines using in silico analysis of genomic data of different viruses has taken many different paths, but lack of any precise computational approach has constrained them to alignment methods and some alignment-free techniques. In this work, a precise computational approach has been established wherein two new mathematical parameters have been suggested to identify the highly conserved and surface-exposed regions which are spread over a large region of the surface protein of the virus so that one can determine possible peptide vaccine candidates from those regions. The first parameter, w, is the sum of the normalized values of the measure of surface accessibility and the normalized measure of conservativeness, and the second parameter is the area of a triangle formed by a mathematical model named 2D Polygon Representation. This method has been, therefore, used to determine possible vaccine targets against SARS-CoV-2 by considering its surface-situated spike glycoprotein. The results of this model have been verified by a parallel analysis using the older approach of manually estimating the graphs describing the variation of conservativeness and surface-exposure across the protein sequence. Furthermore, the working of the method has been tested by applying it to find out peptide vaccine candidates for Zika and Hendra viruses respectively. A satisfactory consistency of the model results with pre-established results for both the test cases shows that this in silico alignment-free analysis proposed by the model is suitable not only to determine vaccine targets against SARS-CoV-2 but also ready to extend against other viruses.

Tracking the pipeline: immunoinformatics and the COVID-19 vaccine design

With the onset of the COVID-19 pandemic, the amount of data on genomic and proteomic sequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stored in various databases has exponentially grown. A large volume of these data has led to the production of equally immense sets of immunological data, which require rigorous computational approaches to sort through and make sense of. Immunoinformatics has emerged in the recent decades as a field capable of offering this approach by bridging experimental and theoretical immunology with state-of-the-art computational tools. Here, we discuss how immunoinformatics can assist in the development of high-performance vaccines and drug discovery needed to curb the spread of SARS-CoV-2. Immunoinformatics can provide a set of computational tools to extract meaningful connections from the large sets of COVID-19 patient data, which can be implemented in the design of effective vaccines. With this in mind, we represent a pipeline to identify the role of immunoinformatics in COVID-19 treatment and vaccine development. In this process, a number of free databases of protein sequences, structures and mutations are introduced, along with docking web servers for assessing the interaction between antibodies and the SARS-CoV-2 spike protein segments as most commonly considered antigens in vaccine design.

Fusion of intelligent learning for COVID-19: A state-of-the-art review and analysis on real medical data

The unprecedented surge of a novel coronavirus in the month of December 2019, named as COVID-19 by the World Health organization has caused a serious impact on the health and socioeconomic activities of the public all over the world. Since its origin, the number of infected and deceased cases has been growing exponentially in almost all the affected countries of the world. The rapid spread of the novel coronavirus across the world results in the scarcity of medical resources and overburdened hospitals. As a result, the researchers and technocrats are continuously working across the world for the inculcation of efficient strategies which may assist the government and healthcare system in controlling and managing the spread of the COVID-19 pandemic. Therefore, this study provides an extensive review of the ongoing strategies such as diagnosis, prediction, drug and vaccine development and preventive measures used in combating the COVID-19 along with technologies used and limitations. Moreover, this review also provides a comparative analysis of the distinct type of data, emerging technologies, approaches used in diagnosis and prediction of COVID-19, statistics of contact tracing apps, vaccine production platforms used in the COVID-19 pandemic. Finally, the study highlights some challenges and pitfalls observed in the systematic review which may assist the researchers to develop more efficient strategies used in controlling and managing the spread of COVID-19.

Bioinformatic HLA Studies in the Context of SARS-CoV-2 Pandemic and Review on Association of HLA Alleles with Preexisting Medical Conditions

After the announcement of a new coronavirus in China in December 2019, which was then called SARS-CoV-2, this virus changed to a global concern and it was then declared as a pandemic by WHO. Human leukocyte antigen (HLA) alleles, which are one of the most polymorphic genes, play a pivotal role in both resistance and vulnerability of the body against viruses and other infections as well as chronic diseases. The association between HLA alleles and preexisting medical conditions such as cardiovascular diseases and diabetes mellitus is reported in various studies. In this review, we focused on the bioinformatic HLA studies to summarize the HLA alleles which responded to SARS-CoV-2 peptides and have been used to design vaccines. We also reviewed HLA alleles that are associated with comorbidities and might be related to the high mortality rate among COVID-19 patients. Since both genes and patients' medical conditions play a key role in both severity of the disease and the mortality rate in COVID-19 patients, a better understanding of the connection between HLA alleles and SARS-CoV-2 can provide a wider perspective on the behavior of the virus. Such understanding can help scientists, especially in terms of protecting healthcare workers and designing effective vaccines.

Nano-Enabled COVID-19 Vaccines: Meeting the Challenges of Durable Antibody Plus Cellular Immunity and Immune Escape

At the time of preparing this Perspective, large-scale vaccination for COVID-19 is in progress, aiming to bring the pandemic under control through vaccine-induced herd immunity. Not only does this vaccination effort represent an unprecedented scientific and technological breakthrough, moving us from the rapid analysis of viral genomes to design, manufacture, clinical trial testing, and use authorization within the time frame of less than a year, but it also highlights rapid progress in the implementation of nanotechnology to assist vaccine development. These advances enable us to deliver nucleic acid and conformation-stabilized subunit vaccines to regional lymph nodes, with the ability to trigger effective humoral and cellular immunity that prevents viral infection or controls disease severity. In addition to a brief description of the design features of unique cationic lipid and virus-mimicking nanoparticles for accomplishing spike protein delivery and presentation by the cognate immune system, we also discuss the importance of adjuvancy and design features to promote cooperative B- and T-cell interactions in lymph node germinal centers, including the use of epitope-based vaccines. Although current vaccine efforts have demonstrated short-term efficacy and vaccine safety, key issues are now vaccine durability and adaptability against viral variants. We present a forward-looking perspective of how vaccine design can be adapted to improve durability of the immune response and vaccine adaptation to overcome immune escape by viral variants. Finally, we consider the impact of nano-enabled approaches in the development of COVID-19 vaccines for improved vaccine design against other infectious agents, including pathogens that may lead to future pandemics.

Bioinformatics and immunoinformatics to support COVID-19 vaccine development

Severe acute respiratory syndrome coronavirus 2 has infected over 109 000 000 people with 2 423 443 deaths as of February 17, 2021. Currently, there are no approved or consistently effective treatments, and conventional vaccines may take several years for development and testing. In silico methods of bioinformatics, vaccinogenomics, immunoinformatics, structural biology, and molecular simulations can be used for more rapid and precise vaccine design. This paper highlights two major immunoinformatics strategies that are used in designing novel and effective vaccines and therapeutics: reverse vaccinology and structural vaccinology.

Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to computationally design an effective peptide-based multi-epitope vaccine (MEV) against SARS-CoV-2. The overall model quality of the vaccine candidate, immunogenicity, allergenicity, and physiochemical analysis have been conducted and validated. Molecular dynamics studies confirmed the stability of the candidate vaccine. The docked complexes during the simulation revealed a strong and stable binding interactions of MEV with human and mice toll-like receptors (TLR), TLR3 and TLR4. Finally, candidate vaccine codons have been optimized for their in silico cloning in E. coli expression system, to confirm increased expression. The proposed MEV can be a potential candidate against SARS-CoV-2, but experimental validation is needed to ensure its safety and immunogenicity status.

In-silico design of a multivalent epitope-based vaccine against Candida auris

Candida auris is a rapidly emerging human pathogenic fungus with a high mortality rate. Recent report suggests that the new clinical isolates are showing resistance to the major classes of antifungal drugs. Due to the emergence of drug resistance, it becomes imperative to seek novel therapies for the treatment of C. auris. The potent vaccine could be one of the promising strategies for recalcitrant and multidrug-resistant pathogens. Using in silico approach we designed a novel multivalent vaccine against C. auris. We have selected the agglutinin-like sequence-3 (Als3) an adhesion protein, involved in virulence. The Als3p protein of C. auris was targeted to predict T cell and B cell epitopes. Epitopes which were found to be non-toxic, non-allergenic, highly conserved, and antigenic and could induce interferon-γ synthesis were selected for vaccine design. The selected epitopes were linked with suitable adjuvants to construct the final vaccine. The vaccine construct was predicted to be stable, soluble, antigenic, non-allergic with desirable physicochemical properties. We also constructed the 3D model of the vaccine and validated it with the Ramachandran plot. The ability of the vaccine construct to interact with Toll-like receptor (TLR) and major histocompatibility complex (MHC) was determined by molecular docking experiments. The binding energy of the vaccine construct with the TLR and MHC were found to be stable as predicted by molecular dynamics simulation. Further, in-silico cloning analysis showed that the vaccine construct can be successfully cloned and expressed in E. coli. Based on the results, we surmise that our candidate vaccine can be used as an alternative therapy for the treatment of C. auris. However, the efficacy and the safety of the vaccine model need to be determined by performing in vivo studies.

In silico T cell epitope identification for SARS-CoV-2: Progress and perspectives

Growing evidence suggests that T cells may play a critical role in combating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, COVID-19 vaccines that can elicit a robust T cell response may be particularly important. The design, development and experimental evaluation of such vaccines is aided by an understanding of the landscape of T cell epitopes of SARS-CoV-2, which is largely unknown. Due to the challenges of identifying epitopes experimentally, many studies have proposed the use of in silico methods. Here, we present a review of the in silico methods that have been used for the prediction of SARS-CoV-2 T cell epitopes. These methods employ a diverse set of technical approaches, often rooted in machine learning. A performance comparison is provided based on the ability to identify a specific set of immunogenic epitopes that have been determined experimentally to be targeted by T cells in convalescent COVID-19 patients, shedding light on the relative performance merits of the different approaches adopted by the in silico studies. The review also puts forward perspectives for future research directions.

Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.

Prediction of putative epitope-based vaccine against all corona virus strains for the Chinese population: Approach toward development of vaccine

Currently, the whole world is facing the coronavirus disease-19 pandemic. As of now, approximately 0.15 million people around the globe are infected with the novel coronavirus. In the last decade, two strains of the coronavirus family, severe acute respiratory syndrome-related coronavirus and Middle East respiratory syndrome coronavirus, also resulted in epidemics in south Asian and the Middle Eastern countries with high mortality rate. This scenario demands the development of a putative vaccine which may provide immunity against all current and new evolving coronavirus strains. In this study, we designed an epitope-based vaccine using an immunoinformatic approach. This vaccine may protect against all coronavirus strains. The vaccine is developed by considering the geographical distribution of coronavirus strains and host genetics (Chinese population). Nine experimentally validated epitopes sequences from coronavirus strains were used to derive the variants considering the conservancy in all strains. Further, the binding affinities of all derived variants were checked with most abundant human leukocyte antigen alleles in the Chinese population. Three major histocompatibility complex (MHC) Class I epitopes from spike glycoprotein and nucleoprotein showed sufficient binding while one MHC Class II epitope from spike glycoprotein was found to be an effective binder. A cocktail of these epitopes gave more than 95% population coverage in the Chinese population. Moreover, molecular dynamics simulation supported the aforementioned predictions. Further, in vivo studies are needed to confirm the immunogenic potential of these vaccines.

The Relevance of Bioinformatics Applications in the Discovery of Vaccine Candidates and Potential Drugs for COVID-19 Treatment

The application of bioinformatics to vaccine research and drug discovery has never been so essential in the fight against infectious diseases. The greatest combat of the 21st century against a debilitating disease agent SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus discovered in Wuhan, China, December 2019, has piqued an unprecedented usage of bioinformatics tools in deciphering the molecular characterizations of infectious pathogens. With the viral genome data of SARS-COV-2 been made available barely weeks after the reported outbreak, bioinformatics platforms have become an all-time critical tool to gain time in the fight against the disease pandemic. Before the outbreak, different platforms have been developed to explore antigenic epitopes, predict peptide-protein docking and antibody structures, and simulate antigen-antibody reactions and lots more. However, the advent of the pandemic witnessed an upsurge in the application of these pipelines with the development of newer ones such as the Coronavirus Explorer in the development of efficacious vaccines, drug repurposing, and/or discovery. In this review, we have explored the various pipelines available for use, their relevance, and limitations in the timely development of useful therapeutic candidates from genomic data knowledge to clinical therapy.

SARS-CoV-2-mediated immune system activation and potential application in immunotherapy

Although novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-mediated pulmonary inflammation has recently attracted great attention, its pathology and pathogenesis are not clear. Notably, due to both its high infective and pathogenicity, SARS-CoV-2 infection may cause a severe sometimes fatal respiratory disease. A specific vaccine, which relies on the analysis of SARS-CoV-2 structural protein-derived antigenic peptides, is indispensable for restraining the spread and reducing the mortality of SARS-CoV-2. SARS-CoV-2 infections activate cytototxic, myeloid-derived suppressor cells, dendritic cells, macrophages, as well as natural killer, B, helper T, and regulatory T cells, thus further stimulating innate and antigen-specific immune responses. Nevertheless, many immune effector cells cause hyperinflammation and pulmonary immunopathology by releasing proinflammatory cytokines and chemokines, including interferon (IFN)-α, IFN-β, IFN-γ, monocyte chemoattractant protein-1, macrophage inflammatory protein (MIP)-1A, MIP1B, interleukin (IL)-1, IL-2, IL-4, IL-6, IL-7, IL-8, IL-9, IL-12, IL-17, and IL-18, platelet-derived growth factor, fibroblast growth factor, tumor necrosis factor-α, and induced protein 10. Interestingly, related products derived from SARS-CoV-2 are likely to trigger immune evasion. Therefore, investigating SARS-CoV-2-specific vaccines, blocking immunopathology, and prohibiting immune evasion are urgently required for treating SARS-CoV-2 infection. In this review, we emphatically illuminated the development of a SARS-CoV-2-specific vaccine based on the analysis of epitopes, also expounding the molecular mechanisms of SARS-CoV-2-mediated cytokine release syndrome. Furthermore, we comprehensively discussed SARS-CoV-2-associated immune evasion and lung immunopathology. Lastly, potential therapeutic strategies against SARS-CoV-2 were explored.

The find of COVID-19 vaccine: Challenges and opportunities

Severe acute respiratory syndrome coronavirus (SARS-CoV-2), a novel corona virus, causing COVID-19 with Flu-like symptoms is the first alarming pandemic of the third millennium. SARS-CoV-2 belongs to beta coronavirus as Middle East respiratory syndrome coronavirus (MERS-CoV). Pandemic COVID-19 owes devastating mortality and destructively exceptional consequences on Socio-Economics life around the world. Therefore, the current review is redirected to the scientific community to owe comprehensive visualization about SARS-CoV-2 to tackle the current pandemic. As systematically shown through the current review, it indexes unmet medical problem of COVID-19 in view of public health and vaccination discovery for the infectious SARS-CoV-2; it is currently under-investigational therapeutic protocols, and next possible vaccines. Furthermore, the review extensively reports the precautionary measures to achieve" COVID-19/Flatten the curve". It is concluded that vaccines formulation within exceptional no time in this pandemic is highly recommended, via following the same protocols of previous pandemics; MERS-CoV and SARS-CoV, and excluding some initial steps of vaccination development process.

Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening

BACKGROUND

Coronaviruses (CoVs) are enveloped positive-strand RNA viruses which have club-like spikes at the surface with a unique replication process. Coronaviruses are categorized as major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Nowadays, a new strain of coronaviruses is identified and named as SARS-CoV-2. Multiple cases of SARS-CoV-2 attacks are being reported all over the world. SARS-CoV-2 showed high death rate; however, no specific treatment is available against SARS-CoV-2.

METHODS

In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against SARS-CoV-2 for the development of the coronavirus vaccine. Cytotoxic T-lymphocyte and B-cell epitopes were predicted for SARS-CoV-2 coronavirus protein. Multiple sequence alignment of three genomes (SARS-CoV, MERS-CoV, and SARS-CoV-2) was used to conserved binding domain analysis.

RESULTS

The docking complexes of 4 CTL epitopes with antigenic sites were analyzed followed by binding affinity and binding interaction analyses of top-ranked predicted peptides with MHC-I HLA molecule. The molecular docking (Food and Drug Regulatory Authority library) was performed, and four compounds exhibiting least binding energy were identified. The designed epitopes lead to the molecular docking against MHC-I, and interactional analyses of the selected docked complexes were investigated. In conclusion, four CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, and QTFSVLACY) and four FDA-scrutinized compounds exhibited potential targets as peptide vaccines and potential biomolecules against deadly SARS-CoV-2, respectively. A multiepitope vaccine was also designed from different epitopes of coronavirus proteins joined by linkers and led by an adjuvant.

CONCLUSION

Our investigations predicted epitopes and the reported molecules that may have the potential to inhibit the SARS-CoV-2 virus. These findings can be a step towards the development of a peptide-based vaccine or natural compound drug target against SARS-CoV-2.

Non-viral COVID-19 vaccine delivery systems

The novel corona virus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread throughout the globe at a formidable speed, causing tens of millions of cases and more than one million deaths in less than a year of its report in December 2019. Since then, companies and research institutions have raced to develop SARS-CoV-2 vaccines, ranging from conventional viral and protein-based vaccines to those that are more cutting edge, including DNA- and mRNA-based vaccines. Each vaccine exhibits a different potency and duration of efficacy, as determined by the antigen design, adjuvant molecules, vaccine delivery platforms, and immunization method. In this review, we will introduce a few of the leading non-viral vaccines that are under clinical stage development and discuss delivery strategies to improve vaccine efficacy, duration of protection, safety, and mass vaccination.

Targets and strategies for vaccine development against SARS-CoV-2

The SARS-CoV-2, previously called a novel coronavirus, that broke out in the Wuhan city of China caused a significant number of morbidity and mortality in the world. It is spreading at peak levels since the first case reported and the need for vaccines is in immense demand globally. Numerous treatment and vaccination strategies that were previously employed for other pathogens including coronaviruses are now being been adopted to guide the formulation of new SARS-CoV-2 vaccines. Several vaccine targets can be utilized for the development of the SARS-CoV-2 vaccine. In this review, we highlighted the potential of various antigenic targets and other modes for formulating an effective vaccine against SARS-CoV-2. There are a varying number of challenges encountered during developing the most effective vaccines, and measures for tackling such challenges will assist in fast pace development of vaccines. This review will give a concise overview of various aspects of the vaccine development process against SARS-CoV-2, including 1) potential antigen targets 2) different vaccination strategies from conventional to novel platforms, 3) ongoing clinical trials, 4) varying challenges encountered during developing the most effective vaccine and the futuristic approaches.

Could Dermaseptin Analogue be a Competitive Inhibitor for ACE2 Towards Binding with Viral Spike Protein Causing COVID19?: Computational Investigation

Initial phase of COVID-19 infection is associated with the binding of viral spike protein S1 receptor binding domain (RBD) with the host cell surface receptor, ACE2. Peptide inhibitors typically interact with spike proteins in order to block its interaction with ACE2, and this knowledge would promote the use of such peptides as therapeutic scaffolds. The present study examined the competitive inhibitor activity of a broad spectrum antimicrobial peptide, Dermaseptin-S4 (S4) and its analogues. Three structural S4 analogues viz., S4 (K₄), S4 (K₂₀) and S4 (K₄K₂₀) were modelled by substituting charged lysine for non-polar residues in S4 and subsequently, docked with S1. Further, the comparative analysis of inter-residue contacts and non-covalent intermolecular interactions among S1–S4 (K₄), S1–S4 (K₄K₂₀) and S1–ACE2 complexes were carried out to explore their mode of binding with S1. Interestingly, S1–S4 (K₄) established more inter-molecular interactions compared to S4 (K₄K₂₀) and S1–ACE2. In order to substantiate this study, the normal mode analysis (NMA) was conducted to show how the structural stability of the flexible loop region in S1 is affected by atomic displacements in unbound S1 and docked complexes. Markedly, the strong interactions consistently maintained by S1–S4 (K₄) complex revealed their conformational transition over the harmonic motion period. Moreover, S1–S4 (K₄) peptide complex showed a higher energy deformation profile compared to S1–S4 (K₄K₂₀), where the higher energy deformation suggests the rigidity of the docked complex and thus it’s harder deformability, which is also substantiated by molecular dynamics simulation. In conclusion, S1–S4 (K₄) complex has definitely exhibited a functionally significant dynamics compared to S1–ACE2 complex; this peptide inhibitor, S4 (K₄) will need to be considered as the best therapeutic scaffold to block SARS-CoV-2 infection.

Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review

BACKGROUND

SARS-CoV-2, the novel coronavirus responsible for COVID-19, has caused havoc worldwide, with patients presenting a spectrum of complications that have pushed health care experts to explore new technological solutions and treatment plans. Artificial Intelligence (AI)-based technologies have played a substantial role in solving complex problems, and several organizations have been swift to adopt and customize these technologies in response to the challenges posed by the COVID-19 pandemic.

OBJECTIVE

The objective of this study was to conduct a systematic review of the literature on the role of AI as a comprehensive and decisive technology to fight the COVID-19 crisis in the fields of epidemiology, diagnosis, and disease progression.

METHODS

A systematic search of PubMed, Web of Science, and CINAHL databases was performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify all potentially relevant studies published and made available online between December 1, 2019, and June 27, 2020. The search syntax was built using keywords specific to COVID-19 and AI.

RESULTS

The search strategy resulted in 419 articles published and made available online during the aforementioned period. Of these, 130 publications were selected for further analyses. These publications were classified into 3 themes based on AI applications employed to combat the COVID-19 crisis: Computational Epidemiology, Early Detection and Diagnosis, and Disease Progression. Of the 130 studies, 71 (54.6%) focused on predicting the COVID-19 outbreak, the impact of containment policies, and potential drug discoveries, which were classified under the Computational Epidemiology theme. Next, 40 of 130 (30.8%) studies that applied AI techniques to detect COVID-19 by using patients' radiological images or laboratory test results were classified under the Early Detection and Diagnosis theme. Finally, 19 of the 130 studies (14.6%) that focused on predicting disease progression, outcomes (ie, recovery and mortality), length of hospital stay, and number of days spent in the intensive care unit for patients with COVID-19 were classified under the Disease Progression theme.

CONCLUSIONS

In this systematic review, we assembled studies in the current COVID-19 literature that utilized AI-based methods to provide insights into different COVID-19 themes. Our findings highlight important variables, data types, and available COVID-19 resources that can assist in facilitating clinical and translational research.

Development of an in silico multi-epitope vaccine against SARS-COV-2 by précised immune-informatics approaches

The coronavirus family has been infecting the human population for the past two decades, but the ongoing coronavirus called SARS-CoV-2 has posed an enigmatic challenge to global public health security. Since last year, the mutagenic quality of this virus is causing changes to its genetic material. To prevent those situations, the FDA approved some emergency vaccines but there is no assurance that these will function properly in the complex human body system. In point of view, a short but efficient effort has made in this study to develop an immune epitope-based therapy for the rapid exploitation of SARS-CoV-2 by applying in silico structural biology and advancing immune information strategies. The antigenic epitopes were screened from the Surface, Membrane, Envelope proteins of SARS-CoV-2 and passed through several immunological filters to determine the best possible one. According to this, 7CD4+, 10CD8+ and 5 B-cell epitopes were found to be prominent, antigenic, immunogenic, and most importantly, highly conserved among 128 Bangladeshi and 110 other infected countries SARS-CoV-2 variants. After that, the selected epitopes and adjuvant were linked to finalize the multi-epitope vaccine by appropriate linkers. The immune simulation disclosed that the engineered vaccine could activate both humoral and innate immune responses. For the prediction of an effective binding, molecular docking was carried out between the vaccine and immunological receptors (TLRs). Strong binding affinity and good docking scores clarified the stringency of the vaccines. Furthermore, MD simulation was performed within the highest binding affinity complex to observe the stability. Codon optimization and other physicochemical properties revealed that the vaccine would be suitable for a higher expression at cloning level. So, monitoring the overall in silico assessment, we anticipated that our engineered vaccine would be a plausible prevention against COVID-19.

COVID-19 vaccine: where are we now and where should we go?

INTRODUCTION

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has currently caused the pandemic with a high progressive speed and has been considered as the global public health crisis in 2020. This new member of the coronavirus family has created a potentially fatal disease, called coronavirus disease-2019 (COVID-19). Despite the continuous efforts of researchers to find effective vaccines and drugs for COVID-19, there is still no success in this matter.

AREAS COVERED

Here, the literature regarding the COVID-19 vaccine candidates currently in the clinical trials, as well as main candidates in pre-clinical stages for development and research, were reviewed. These candidates have been developed under five different major platforms, including live-attenuated vaccine, mRNA-based vaccine, DNA vaccines, inactivated virus, and viral-vector-based vaccine.

EXPERT OPINION

There are several limitations in the field of the rapid vaccine development against SARS-CoV-2, and other members of the coronavirus family such as SARS-CoV and MERS-CoV. The key challenges of designing an effective vaccine within a short time include finding the virulence ability of an emerging virus and potential antigen, choosing suitable experimental models and efficient route of administration, the immune-response study, designing the clinical trials, and determining the safety, as well as efficacy.

Microstructure, pathophysiology, and potential therapeutics of COVID-19: A comprehensive review

There have been over seven million cases and almost 413 372 deaths globally due to the novel coronavirus (2019-nCoV) associated disease COVID-19, as of 11 June 2020. Phylogenetic analysis suggests that there is a common source for these infections. The overall sequence similarities between the spike protein of 2019-nCoV and that of SARS-CoV are known to be around 76% to 78% and 73% to 76% for the whole protein and receptor-binding domain (RBD), respectively. Thus, they have the potential to serve as the drug and/or vaccine candidate. However, the individual response against 2019-nCoV differs due to genetic variations in the human population. Understanding the variations in angiotensin-converting enzyme 2 (ACE2) and human leukocyte antigen (HLA) that may affect the severity of 2019-nCoV infection could help in identifying individuals at a higher risk from the COVID-19. A number of potential drugs/vaccines as well as antibody/cytokine-based therapeutics are in various developmental stages of preclinical/clinical trials against SARS-CoV, MERS-CoV, and 2019-nCoV with substantial cross-reactivity, and may be used against COVID-19. For diagnosis, the reverse-transcription polymerase chain reaction is the gold standard test for initial diagnosis of COVID-19. A kit based on serological tests are also recommended for investigating the spread of COVID-19 but this is challenging due to the antibodies cross-reactivity. This review comprehensively summarizes the recent reports available regarding the host-pathogen interaction, morphological and genomic structure of the virus, and the diagnostic techniques as well as the available potential therapeutics against COVID-19.

Interpretative immune targets and contemporary position for vaccine development against SARS-CoV-2: A systematic review

The year 2020 started with the emergence of novel coronavirus, severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2), which causes COVID‐19 infection. Soon after the first evidence was reported in Wuhan, China, the World Health Organization declared global public health emergency and imminent need to understand the pathogenicity of the virus was required in limited time. Once the genome sequence of the virus was delineated, scientists across the world started working on the development of vaccines. Although, some laboratories have been using previously developed vaccine platforms from severe acute respiratory syndrome coronavirus (SARS) and middle east respiratory syndrome‐related coronavirus and apply them in COVID‐19 vaccines due to genetic similarities between coronaviruses. We have conducted a literature review to assess the background and current status of COVID‐19 vaccines. The worldwide implementation and strategies for COVID‐19 vaccine development are summarized from studies reported in years 2015–2020. While discussing the vaccine candidates, we have also explained interpretative immune responses of SARS‐CoV‐2 infection. There are several vaccine candidates at preclinical and clinical stages; however, only 42 vaccines are under clinical trials. Therefore, more industry collaborations and financial supports to COVID‐19 studies are needed for mass‐scale vaccine development. To develop effective vaccine platforms against SARS‐CoV‐2, the genetic resemblance with other coronaviruses are being evaluated which may further promote fast‐track trials on previously developed SARS‐CoV vaccines.

Perspectives in Peptide-Based Vaccination Strategies for Syndrome Coronavirus 2 Pandemic

At the end of December 2019, an epidemic form of respiratory tract infection now named COVID-19 emerged in Wuhan, China. It is caused by a newly identified viral pathogen, the severe acute respiratory syndrome coronavirus (SARS-CoV-2), which can cause severe pneumonia and acute respiratory distress syndrome. On January 30, 2020, due to the rapid spread of infection, COVID-19 was declared as a global health emergency by the World Health Organization. Coronaviruses are enveloped RNA viruses belonging to the family of Coronaviridae, which are able to infect birds, humans and other mammals. The majority of human coronavirus infections are mild although already in 2003 and in 2012, the epidemics of SARS-CoV and Middle East Respiratory Syndrome coronavirus (MERS-CoV), respectively, were characterized by a high mortality rate. In this regard, many efforts have been made to develop therapeutic strategies against human CoV infections but, unfortunately, drug candidates have shown efficacy only into in vitro studies, limiting their use against COVID-19 infection. Actually, no treatment has been approved in humans against SARS-CoV-2, and therefore there is an urgent need of a suitable vaccine to tackle this health issue. However, the puzzled scenario of biological features of the virus and its interaction with human immune response, represent a challenge for vaccine development. As expected, in hundreds of research laboratories there is a running out of breath to explore different strategies to obtain a safe and quickly spreadable vaccine; and among others, the peptide-based approach represents a turning point as peptides have demonstrated unique features of selectivity and specificity toward specific targets. Peptide-based vaccines imply the identification of different epitopes both on human cells and virus capsid and the design of peptide/peptidomimetics able to counteract the primary host-pathogen interaction, in order to induce a specific host immune response. SARS-CoV-2 immunogenic regions are mainly distributed, as well as for other coronaviruses, across structural areas such as spike, envelope, membrane or nucleocapsid proteins. Herein, we aim to highlight the molecular basis of the infection and recent peptide-based vaccines strategies to fight the COVID-19 pandemic including their delivery systems.

An Immunoinformatics Study to Predict Epitopes in the Envelope Protein of SARS-CoV-2

COVID-19 is a new viral emergent disease caused by a novel strain of coronavirus. This virus has caused a huge problem in the world as millions of people are affected by this disease. We aimed at designing a peptide vaccine for COVID-19 particularly for the envelope protein using computational methods to predict epitopes inducing the immune system. The envelope protein sequence of SARS-CoV-2 has been retrieved from the NCBI database. The bioinformatics analysis was carried out by using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. The predicted HTL and CTL epitopes were docked with HLA alleles and binding energies were evaluated. The allergenicity of predicted epitopes was analyzed, the conservancy analysis was performed, and the population coverage was determined throughout the world. Some overlapped CTL, HTL, and B-cell epitopes were suggested to become a universal candidate for peptide-based vaccine against COVID-19. This vaccine peptide could simultaneously elicit humoral and cell-mediated immune responses. We hope to confirm our findings by adding complementary steps of both in vitro and in vivo studies to support this new universal predicted candidate.

Recombinant vaccines for COVID-19

SARS-CoV-2, the causative agent of COVID-19, has imposed a major public health threat, which needs effective therapeutics and vaccination strategies. Several potential candidate vaccines being rapidly developed are in clinical evaluation. Considering the crucial role of SARS-CoV-2 spike (S) glycoprotein in virus attachment, entry, and induction of neutralizing antibodies, S protein is being widely used as a target for vaccine development. Based on advances in techniques for vaccine design, inactivated, live-vectored, nucleic acid, and recombinant COVID-19 vaccines are being developed and tested for their efficacy. Phase3 clinical trials are underway or will soon begin for several of these vaccines. Assuming that clinical efficacy is shown for one or more vaccines, safety is a major aspect to be considered before deploying such vaccines to the public. The current review focuses on the recent advances in recombinant COVID-19 vaccine research and development and associated issues.

Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools

The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cells via the HLA complex. SARS-CoV-2 is a large RNA virus and testing of all of its overlapping peptides in vitro to deconvolute an immune response is not feasible. Therefore HLA-binding prediction tools are often used to narrow down the number of peptides to test. We tested NetMHC suite tools' predictions by using an in vitro peptide-MHC stability assay. We assessed 777 peptides that were predicted to be good binders across 11 MHC alleles in a complex-stability assay and tested a selection of 19 epitope-HLA-binding prediction tools against the assay. In this investigation of potential SARS-CoV-2 epitopes we found that current prediction tools vary in performance when assessing binding stability, and they are highly dependent on the MHC allele in question. Designing a COVID-19 vaccine where only a few epitope targets are included is therefore a very challenging task. Here, we present 174 SARS-CoV-2 epitopes with high prediction binding scores, validated to bind stably to 11 HLA alleles. Our findings may contribute to the design of an efficacious vaccine against COVID-19.

Computational Immune Proteomics Approach to Target COVID-19

Progress of the omics platforms widens their application to diverse fields, including immunology. This enables a deeper level of knowledge and the provision of a huge amount of data for which management and fruitful integration with the past evidence requires a steadily growing computational effort. In light of this, immunoinformatics emerges as a new discipline placed in between the traditional lab-based investigations and the computational analysis of the biological data. Immunoinformatics make use of tailored bioinformatics tools and data repositories to facilitate the analysis of data from a plurality of disciplines and help drive novel research hypotheses and in silico screening investigations in a fast, reliable, and cost-effective manner. Such computational immunoproteomics studies may as well prepare and guide lab-based investigations, representing valuable technology for the investigation of novel pathogens, to tentatively evaluate specificity of diagnostic products, to forecast on potential adverse effects of vaccines and to reduce the use of animal models. The present manuscript provides an overview of the COVID-19 pandemic and reviews the state of the art of the omics technologies employed in fighting SARS-CoV-2 infections. A comprehensive description of the immunoinformatics approaches and its potential role in contrasting COVID-19 pandemics is provided.

Genome based evolutionary lineage of SARS-CoV-2 towards the development of novel chimeric vaccine

The present study aimed to predict a novel chimeric vaccine by simultaneously targeting four major structural proteins via the establishment of ancestral relationship among different strains of coronaviruses. Conserved regions from the homologous protein sets of spike glycoprotein, membrane protein, envelope protein and nucleocapsid protein were identified through multiple sequence alignment. The phylogeny analyses of whole genome stated that four proteins reflected the close ancestral relation of SARS-CoV-2 to SARS-COV-1 and bat coronavirus. Numerous immunogenic epitopes (both T cell and B cell) were generated from the common fragments which were further ranked on the basis of antigenicity, transmembrane topology, conservancy level, toxicity and allergenicity pattern and population coverage analysis. Top putative epitopes were combined with appropriate adjuvants and linkers to construct a novel multiepitope subunit vaccine against COVID-19. The designed constructs were characterized based on physicochemical properties, allergenicity, antigenicity and solubility which revealed the superiority of construct V3 in terms safety and efficacy. Essential molecular dynamics and normal mode analysis confirmed minimal deformability of the refined model at molecular level. In addition, disulfide engineering was investigated to accelerate the stability of the protein. Molecular docking study ensured high binding affinity between construct V3 and HLA cells, as well as with different host receptors. Microbial expression and translational efficacy of the constructs were checked using pET28a(+) vector of E. coli strain K12. However, the in vivo and in vitro validation of suggested vaccine molecule might be ensured with wet lab trials using model animals for the implementation of the presented data.

Determine the Potential Epitope Based Peptide Vaccine Against Novel SARS-CoV-2 Targeting Structural Proteins Using Immunoinformatics Approaches

Coronaviruses (CoVs) belong to the Coronaviridae-family. The genus Beta-coronaviruses, are enveloped positive strand RNA viruses with club-like spikes at the surface with a unique replication process and a large RNA genome (∼25 kb). CoVs are known as one of the major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Recently, a new strain of coronavirus has been identified and named as SARS-CoV-2. A large number of COVID-19 (disease caused by SARS-CoV-2) cases are being diagnosed all over the World especially in China (Wuhan). COVID-19 showed high mortality rate exponentially, however, not even a single effective cure is being introduced yet against COVID-19. In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against COVID-19 for the development of a coronavirus peptide vaccine. Cytotoxic T-lymphocyte (CTL) and B-cell epitopes were predicted for SARS-CoV-2 coronavirus structural proteins (Spikes, Membrane, Envelope, and Nucleocapsid). The docking complexes of the top 10 epitopes having antigenic sites were analyzed led by binding affinity and binding interactional analyses of top ranked predicted peptides with the MHC-I HLA molecule. The predicted peptides may have potential to be used as peptide vaccine against COVID-19.

SARS-CoV-2 Vaccine Development: An Overview and Perspectives

Coronavirus disease 2019, abbreviated as COVID-19, is caused by a new strain of coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It started in late December 2019 in Wuhan, China, and by mid-March 2020, the disease had spread globally. As of July 17, 2020, this pandemic virus has infected 13.9 million people and claimed the life of approximately 593 000 people globally, and the numbers continue to climb. An unprecedented effort is underway to develop therapeutic and prophylactic strategies against this disease. Various drugs and vaccines are undergoing rapid development, and some of these are already in phase III clinical trials. Although Russia was the first to release a vaccine by skipping phase III clinical trials, there is no evidence of large-scale clinical trials, and the safety and efficacy of the vaccine are still a concern. Nevertheless, critical lessons can be learned and data garnered for developing promising vaccines against this rapidly emerging virus or other similar pathogens in the future. In this overview, we cover the available information on the various vaccine development initiatives by different companies, the potential strategies adopted for vaccine design, and the challenges and clinical impact expected from these vaccines. We also briefly discuss the possible role of these vaccines and the specific concerns for their use in patients with pre-existing disease conditions such as cardiovascular, lung, kidney, and liver diseases, cancer patients who are receiving immunosuppressive medications, including anticancer chemotherapies, and many other sensitive populations, such as children and the elderly.

Exploring the out of sight antigens of SARS-CoV-2 to design a candidate multi-epitope vaccine by utilizing immunoinformatics approaches

SARS-CoV-2 causes a severe respiratory disease called COVID-19. Currently, global health is facing its devastating outbreak. However, there is no vaccine available against this virus up to now. In this study, a novel multi-epitope vaccine against SARS-CoV-2 was designed to provoke both innate and adaptive immune responses. The immunodominant regions of six non-structural proteins (nsp7, nsp8, nsp9, nsp10, nsp12 and nsp14) of SARS-CoV-2 were selected by multiple immunoinformatic tools to provoke T cell immune response. Also, immunodominant fragment of the functional region of SARS-CoV-2 spike (400-510 residues) protein was selected for inducing neutralizing antibodies production. The selected regions' sequences were connected to each other by furin-sensitive linker (RVRR). Moreover, the functional region of β-defensin as a well-known agonist for the TLR-4/MD complex was added at the N-terminus of the vaccine using (EAAAK)3 linker. Also, a CD4 + T-helper epitope, PADRE, was used at the C-terminal of the vaccine by GPGPG and A(EAAAK)2A linkers to form the final vaccine construct. The physicochemical properties, allergenicity, antigenicity, functionality and population coverage of the final vaccine construct were analyzed. The final vaccine construct was an immunogenic, non-allergen and unfunctional protein which contained multiple CD8 + and CD4 + overlapping epitopes, IFN-γ inducing epitopes, linear and conformational B cell epitopes. It could form stable and significant interactions with TLR-4/MD according to molecular docking and dynamics simulations. Global population coverage of the vaccine for HLA-I and II were estimated 96.2% and 97.1%, respectively. At last, the final vaccine construct was reverse translated to design the DNA vaccine. Although the designed vaccine exhibited high efficacy in silico, further experimental validation is necessary.

Designing a multi-epitope peptide based vaccine against SARS-CoV-2

COVID-19 pandemic has resulted in 16,114,449 cases with 646,641 deaths from the 217 countries, or territories as on July 27th 2020. Due to multifaceted issues and challenges in the implementation of the safety and preventive measures, inconsistent coordination between societies-governments and most importantly lack of specific vaccine to SARS-CoV-2, the spread of the virus that initially emerged at Wuhan is still uprising after taking a heavy toll on human life. In the present study, we mapped immunogenic epitopes present on the four structural proteins of SARS-CoV-2 and we designed a multi-epitope peptide based vaccine that, demonstrated a high immunogenic response with a vast application on world’s human population. On codon optimization and in-silico cloning, we found that candidate vaccine showed high expression in E. coli and immune simulation resulted in inducing a high level of both B-cell and T-cell mediated immunity. The results predicted that exposure of vaccine by administrating three injections significantly subsidized the antigen growth in the system. The proposed candidate vaccine found promising by yielding desired results and hence, should be validated by practical experimentations for its functioning and efficacy to neutralize SARS-CoV-2.

Design and optimization of a subunit vaccine targeting COVID-19 molecular shreds using an immunoinformatics framework

COVID-19 has been declared as a global health emergency and exposed the world to a deadly virus, which has dramatically changed the lives of humans for an unknown period of time. In the battleground with the virus, we have employed an immunoinformatics framework to design a robust vaccine as an insurance plan for the future. The pathogenic sequence with cryptic epitope taken from patients in Wuhan, China, was harnessed to design a promiscuous cytotoxic T-lymphocyte, helper T-lymphocyte, and B-cell epitope based subunit vaccine, engineered with adjuvants and conformational linkers. The reported vaccine has high antigenicity and immunogenicity profiles with potential TAP affinity, which ensures elevated antigen processing capability. It has strong binding with major histocompatibility complex (MHC) receptors (MHC-1 and MHC-2) and virus-specific membrane receptor TLR-2, with scores of -1010.7, -1035.7, and -1076.3 kcal mol-1, respectively. Molecular dynamics simulation analysis was used to assess the stable binding with TLR-2 with minimal atomic motions through a deformation plot, covariance matrix, and elastic network. Importantly, an in silico immunization assay showed the reliable elicitation of key players in terms of immune cells together with memory cells to evoke adaptive immune responses upon administration of the construct. In view of favorable outcomes, we also propose a plausible vaccine mechanism to elicit an immune response to fight coronavirus.

Peptides: Prospects for Use in the Treatment of COVID-19

There is a vast practice of using antimalarial drugs, RAS inhibitors, serine protease inhibitors, inhibitors of the RNA-dependent RNA polymerase of the virus and immunosuppressants for the treatment of the severe form of COVID-19, which often occurs in patients with chronic diseases and older persons. Currently, the clinical efficacy of these drugs for COVID-19 has not been proven yet. Side effects of antimalarial drugs can worsen the condition of patients and increase the likelihood of death. Peptides, given their physiological mechanism of action, have virtually no side effects. Many of them are geroprotectors and can be used in patients with chronic diseases. Peptides may be able to prevent the development of the pathological process during COVID-19 by inhibiting SARS-CoV-2 virus proteins, thereby having immuno- and bronchoprotective effects on lung cells, and normalizing the state of the hemostasis system. Immunomodulators (RKDVY, EW, KE, AEDG), possessing a physiological mechanism of action at low concentrations, appear to be the most promising group among the peptides. They normalize the cytokines' synthesis and have an anti-inflammatory effect, thereby preventing the development of disseminated intravascular coagulation, acute respiratory distress syndrome and multiple organ failure.

Reverse vaccinology assisted designing of multiepitope-based subunit vaccine against SARS-CoV-2

BACKGROUND

Coronavirus disease 2019 (COVID-19) linked with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause severe illness and life-threatening pneumonia in humans. The current COVID-19 pandemic demands an effective vaccine to acquire protection against the infection. Therefore, the present study was aimed to design a multiepitope-based subunit vaccine (MESV) against COVID-19.

METHODS

Structural proteins (Surface glycoprotein, Envelope protein, and Membrane glycoprotein) of SARS-CoV-2 are responsible for its prime functions. Sequences of proteins were downloaded from GenBank and several immunoinformatics coupled with computational approaches were employed to forecast B- and T- cell epitopes from the SARS-CoV-2 highly antigenic structural proteins to design an effective MESV.

RESULTS

Predicted epitopes suggested high antigenicity, conserveness, substantial interactions with the human leukocyte antigen (HLA) binding alleles, and collective global population coverage of 88.40%. Taken together, 276 amino acids long MESV was designed by connecting 3 cytotoxic T lymphocytes (CTL), 6 helper T lymphocyte (HTL) and 4 B-cell epitopes with suitable adjuvant and linkers. The MESV construct was non-allergenic, stable, and highly antigenic. Molecular docking showed a stable and high binding affinity of MESV with human pathogenic toll-like receptors-3 (TLR3). Furthermore, in silico immune simulation revealed significant immunogenic response of MESV. Finally, MEV codons were optimized for its in silico cloning into the Escherichia coli K-12 system, to ensure its increased expression.

CONCLUSION

The MESV developed in this study is capable of generating immune response against COVID-19. Therefore, if designed MESV further investigated experimentally, it would be an effective vaccine candidate against SARS-CoV-2 to control and prevent COVID-19.

Coronavirus Disease (COVID-19): Current Status and Prospects for Drug and Vaccine Development

The Coronavirus disease 2019 (COVID-19) pandemic has spread to almost all nooks and corners of the world. There are numerous potential approaches to pharmacologically fight COVID-19: small-molecule drugs, interferon therapies, vaccines, oligonucleotides, peptides, and monoclonal antibodies. Medications are being developed to target the spike, membrane, nucleocapsid or envelope proteins. The spike protein is also a critical target for vaccine development. Immunoinformatic approaches are being used for the identification of B cell and cytotoxic T lymphocyte (CTL) epitopes in the SARS-CoV-2 spike protein. Different vaccine vectors are also being developed. Chemical and physical methods such as formaldehyde, UV light or β-propiolactone are being deployed for the preparation of inactivated virus vaccine. Currently, there are many vaccines undergoing clinical trials. Even though mRNA and DNA vaccines are being designed and moved into clinical trials, these types of vaccines are yet to be approved by regulatory bodies for human use. This review focuses on the drugs and vaccines being developed against the COVID-19.

Immunoinformatics-guided design of an epitope-based vaccine against severe acute respiratory syndrome coronavirus 2 spike glycoprotein

AIMS

With a large number of fatalities, coronavirus disease-2019 (COVID-19) has greatly affected human health worldwide. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes COVID-19. The World Health Organization has declared a global pandemic of this contagious disease. Researchers across the world are collaborating in a quest for remedies to combat this deadly virus. It has recently been demonstrated that the spike glycoprotein (SGP) of SARS-CoV-2 is the mediator by which the virus enters host cells.

MAIN METHODS

Our group comprehensibly analyzed the SGP of SARS-CoV-2 through multiple sequence analysis and a phylogenetic analysis. We predicted the strongest immunogenic epitopes of the SGP for both B cells and T cells.

KEY FINDINGS

We focused on predicting peptides that would bind major histocompatibility complex class I. Two optimal epitopes were identified, WTAGAAAYY and GAAAYYVGY. They interact with the HLA-B*15:01 allele, which was further validated by molecular docking simulation. This study also found that the selected epitopes are able to be recognized in a large percentage of the world's population. Furthermore, we predicted CD4+ T-cell epitopes and B-cell epitopes.

SIGNIFICANCE

Our study provides a strong basis for designing vaccine candidates against SARS-CoV-2. However, laboratory work is required to validate our theoretical results, which would lay the foundation for the appropriate vaccine manufacturing and testing processes.

Genomic diversity and evolution, diagnosis, prevention, and therapeutics of the pandemic COVID-19 disease

The coronavirus disease 19 (COVID-19) is a highly transmittable and pathogenic viral infection caused by a novel evolutionarily divergent RNA virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus first emerged in Wuhan, China in December 2019, and subsequently spreaded around the world. Genomic analyses revealed that this zoonotic virus may be evolved naturally but not a purposefully manipulated laboratory construct. However, currently available data are not sufficient to precisely conclude the origin of this fearsome virus. Comprehensive annotations of the whole-genomes revealed hundreds of nucleotides, and amino acids mutations, substitutions and/or deletions at different positions of the ever changing SARS-CoV-2 genome. The spike (S) glycoprotein of SARS-CoV-2 possesses a functional polybasic (furin) cleavage site at the S1-S2 boundary through the insertion of 12 nucleotides. It leads to the predicted acquisition of 3-O-linked glycan around the cleavage site. Although real-time RT-PCR methods targeting specific gene(s) have widely been used to diagnose the COVID-19 patients, however, recently developed more convenient, cheap, rapid, and specific diagnostic tools targeting antigens or CRISPR-Cas-mediated method or a newly developed plug and play method should be available for the resource-poor developing countries. A large number of candidate drugs, vaccines and therapies have shown great promise in early trials, however, these candidates of preventive or therapeutic agents have to pass a long path of trials before being released for the practical application against COVID-19. This review updates current knowledge on origin, genomic evolution, development of the diagnostic tools, and the preventive or therapeutic remedies of the COVID-19. We also discussed the future scopes for research, effective management, and surveillance of the newly emerged COVID-19 disease.

Plants Metabolites: Possibility of Natural Therapeutics Against the COVID-19 Pandemic

COVID-19, a disease induced by SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2), has been the cause of a worldwide pandemic. Though extensive research works have been reported in recent days on the development of effective therapeutics against this global health crisis, there is still no approved therapy against SARS-CoV-2. In the present study, plant-synthesized secondary metabolites (PSMs) have been prioritized to make a review focusing on the efficacy of plant-originated therapeutics for the treatment of COVID-19. Plant metabolites are a source of countless medicinal compounds, while the diversity of multidimensional chemical structures has made them superior to treat serious diseases. Some have already been reported as promising alternative medicines and lead compounds for drug repurposing and discovery. The versatility of secondary metabolites may provide novel antibiotics to tackle MDR (Multi-Drug Resistant) microbes too. This review attempted to find out plant metabolites that have the therapeutic potential to treat a wide range of viral pathogens. The study includes the search of remedies belonging to plant families, susceptible viral candidates, antiviral assays, and the mode of therapeutic action; this attempt resulted in the collection of an enormous number of natural therapeutics that might be suggested for the treatment of COVID-19. About 219 plants from 83 families were found to have antiviral activity. Among them, 149 plants from 71 families were screened for the identification of the major plant secondary metabolites (PSMs) that might be effective for this pandemic. Our investigation revealed that the proposed plant metabolites can serve as potential anti- SARS-CoV-2 lead molecules for further optimization and drug development processes to combat COVID-19 and future pandemics caused by viruses. This review will stimulate further analysis by the scientific community and boost antiviral plant-based research followed by novel drug designing.

Epitope-based chimeric peptide vaccine design against S, M and E proteins of SARS-CoV-2, the etiologic agent of COVID-19 pandemic: an in silico approach

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19), a public health emergency of international concerns declared by the World Health Organization (WHO). An immuno-informatics approach along with comparative genomics was applied to design a multi-epitope-based peptide vaccine against SARS-CoV-2 combining the antigenic epitopes of the S, M, and E proteins. The tertiary structure was predicted, refined and validated using advanced bioinformatics tools. The candidate vaccine showed an average of ≥90.0% world population coverage for different ethnic groups. Molecular docking and dynamics simulation of the chimeric vaccine with the immune receptors (TLR3 and TLR4) predicted efficient binding. Immune simulation predicted significant primary immune response with increased IgM and secondary immune response with high levels of both IgG1 and IgG2. It also increased the proliferation of T-helper cells and cytotoxic T-cells along with the increased IFN-γ and IL-2 cytokines. The codon optimization and mRNA secondary structure prediction revealed that the chimera is suitable for high-level expression and cloning. Overall, the constructed recombinant chimeric vaccine candidate demonstrated significant potential and can be considered for clinical validation to fight against this global threat, COVID-19.

Immunoinformatics design of multiepitopes peptide-based universal cancer vaccine using matrix metalloproteinase-9 protein as a target

A new approach toward cancer therapy is the use of cancer vaccine, yet the different molecular bases of cancers, reduce the effectiveness of this approach. In this article, we aim to use matrix metalloproteinase-9 protein (MMP9) which is an essential molecule in the survival and metastasis of all types of cancers as a target for universal cancer vaccine design. The reference sequence of MMP9 protein was obtained from NCBI databases. Furthermore, the B-cell and T cell-related peptides were analyzed using the IEDB website and other related soft wares. The best candidate peptides were then visualized using chimera software. Three peptides were found to be good candidates for interactions with B cells (SLPE, RLYT, and PALPR), while 10 peptides were found as good targets for interactions with MHC1 and another 10 peptides founded suitable for interactions with MHC2 with population coverages of 94.77 and 90.67%, respectively. Finally, the immune response simulation and molecular docking were done using the C-IMMSIM simulator and AutoDock Vina to confirm the effectiveness of the proposed vaccine. By the end of this project: twenty-three peptide-based vaccine was designed for use as a universal cancer vaccine which has a high world population coverage for MHC1 (94.77%) and MHC2 (90.67%) related alleles.

Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts

The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 214 countries and areas in the world, and has significantly affected every aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deaths still increase significantly and have no sign of a well-controlled situation, e.g., as of 13 July 2020, from a total number of around 13.1 million positive cases, 571,527 deaths were reported in the world. Motivated by recent advances and applications of artificial intelligence (AI) and big data in various areas, this paper aims at emphasizing their importance in responding to the COVID-19 outbreak and preventing the severe effects of the COVID-19 pandemic. We firstly present an overview of AI and big data, then identify the applications aimed at fighting against COVID-19, next highlight challenges and issues associated with state-of-the-art solutions, and finally come up with recommendations for the communications to effectively control the COVID-19 situation. It is expected that this paper provides researchers and communities with new insights into the ways AI and big data improve the COVID-19 situation, and drives further studies in stopping the COVID-19 outbreak.

Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts

The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 214 countries and areas in the world, and has significantly affected every aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deaths still increase significantly and have no sign of a well-controlled situation, e.g., as of 13 July 2020, from a total number of around 13.1 million positive cases, 571,527 deaths were reported in the world. Motivated by recent advances and applications of artificial intelligence (AI) and big data in various areas, this paper aims at emphasizing their importance in responding to the COVID-19 outbreak and preventing the severe effects of the COVID-19 pandemic. We firstly present an overview of AI and big data, then identify the applications aimed at fighting against COVID-19, next highlight challenges and issues associated with state-of-the-art solutions, and finally come up with recommendations for the communications to effectively control the COVID-19 situation. It is expected that this paper provides researchers and communities with new insights into the ways AI and big data improve the COVID-19 situation, and drives further studies in stopping the COVID-19 outbreak.

An insight into the epitope-based peptide vaccine design strategy and studies against COVID-19

SARS-CoV-2 is a new member of the coronavirus family and caused the pandemic of coronavirus disease 2019 (COVID-19) in 2020. It is crucial to design and produce an effective vaccine for the prevention of rapid transmission and possible deaths wcaused by the disease. Although intensive work and research are being carried out all over the world to develop a vaccine, an effective and approved formulation that can prevent the infection and limit the outbreak has not been announced yet. Among all types of vaccines, epitope-based peptide vaccines outshine with their low-cost production, easy modification in the structure, and safety. In this review, vaccine studies against COVID-19 have been summarized and detailed information about the epitope-based peptide vaccines against COVID-19 has been provided. We have not only compared the peptide vaccine with other types of vaccines but also presented comprehensive literature information about development steps for an effective and protective formulation to give an insight into on-going peptide vaccine studies against SARS-CoV-2.