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

Effectiveness and Safety of COVID-19 Vaccinations: An Umbrella Meta-Analysis

Objectives: This umbrella meta-analysis aims to provide comprehensive and synthesized evidence regarding the effectiveness and safety of COVID-19 vaccinations based on current studies. Methods: Studies from the Cochrane Library, PubMed, and EMBASE, published before 10 December 2021, were included in the analysis. The pooled results of effectiveness and safety were estimated and shown in forest plots. Results: We included nineteen studies (fifteen studies regarding safety and nine regarding effectiveness) in the analysis. The mRNA vaccines, adenovirus vector vaccines, subunit vaccines, and inactivated vaccines were found to be effective; however, mRNA vaccines, adenovirus vector vaccines and subunit vaccines were associated with local adverse events and systemic events when compared with inactivated vaccines. Conclusion: Our study suggested that till date, COVID-19 vaccination is still a preferred pharmaceutical way to control the widespread pandemic. However, all reported adverse events should be revisited to provide further evidence for mass vaccinations.

Bioinformatics and immunoinformatics approach to develop potent multi-peptide vaccine for coxsackievirus B3 capable of eliciting cellular and humoral immune response

Coxsackievirus B3 (CVB3) is a viral pathogen of various human disorders with no effective preventative interventions. Herein, we aimed to design a chimeric vaccine construct for CVB3 using reverse vaccinology and immunoinformatics approaches by screening the whole viral polyprotein sequence. Firstly, screening and mapping of viral polyprotein to predict 21 immunodominant epitopes (B-cell, CD8+ and CD4+ T-cell epitopes), fused with an adjuvant (Resuscitation-promoting factor), appropriate linkers, HIV-TAT peptide, Pan DR epitope, and 6His-tag to assemble a multi-epitope vaccine construct. The chimeric construct is predicted as probable antigen, non-allergen, stable, possess encouraging physicochemical features, and indicates a broader population coverage (98 %). The tertiary structure of the constructed vaccine was predicted and refined, and its interaction with the Toll-like receptor 4 (TLR4) was investigated through molecular docking and dynamics simulation. Computational cloning of the construct was carried out in pET28a (+) plasmid to guarantee the higher expression of the vaccine protein. Lastly, in silico immune simulation foreseen that humoral and cellular immune responses would be elicited in response to the administration of such a potent chimeric construct. Thus, the design constructed could vaccinate against CVB3 infection and various CVB serotypes. However, further in vitro/in vivo research must assess its safety and effectiveness.

Immunoinformatics design of multivalent epitope vaccine against monkeypox virus and its variants using membrane-bound, enveloped, and extracellular proteins as targets

Introduction

The current monkeypox (MPX) outbreak, caused by the monkeypox virus (MPXV), has turned into a global concern, with over 59,000 infection cases and 23 deaths worldwide.

Objectives

Herein, we aimed to exploit robust immunoinformatics approach, targeting membrane-bound, enveloped, and extracellular proteins of MPXV to formulate a chimeric antigen. Such a strategy could similarly be applied for identifying immunodominant epitopes and designing multi-epitope vaccine ensembles in other pathogens responsible for chronic pathologies that are difficult to intervene against.

Methods

A reverse vaccinology pipeline was used to select 11 potential vaccine candidates, which were screened and mapped to predict immunodominant B-cell and T-cell epitopes. The finalized epitopes were merged with the aid of suitable linkers, an adjuvant (Resuscitation-promoting factor), a PADRE sequence (13 aa), and an HIV TAT sequence (11 aa) to formulate a multivalent epitope vaccine. Bioinformatics tools were employed to carry out codon adaptation and computational cloning. The tertiary structure of the chimeric vaccine construct was modeled via I-TASSER, and its interaction with Toll-like receptor 4 (TLR4) was evaluated using molecular docking and molecular dynamics simulation. C-ImmSim server was implemented to examine the immune response against the designed multi-epitope antigen.

Results and discussion

The designed chimeric vaccine construct included 21 immunodominant epitopes (six B-cell, eight cytotoxic T lymphocyte, and seven helper T-lymphocyte) and is predicted non-allergen, antigenic, soluble, with suitable physicochemical features, that can promote cross-protection among the MPXV strains. The selected epitopes indicated a wide global population coverage (93.62%). Most finalized epitopes have 70%-100% sequence similarity with the experimentally validated immune epitopes of the vaccinia virus, which can be helpful in the speedy progression of vaccine design. Lastly, molecular docking and molecular dynamics simulation computed stable and energetically favourable interaction between the putative antigen and TLR4.

Conclusion

Our results show that the multi-epitope vaccine might elicit cellular and humoral immune responses and could be a potential vaccine candidate against the MPXV infection. Further experimental testing of the proposed vaccine is warranted to validate its safety and efficacy profile.

Immunoinformatics design of B and T-cell epitope-based SARS-CoV-2 peptide vaccination

SARS-COV-2 is a virulent respiratory virus, first identified in China (Wuhan) at the end of 2019. Scientists and researchers are trying to find any possible solution to this deadly viral disease. Different drug source agents have been identified, including western medicine, natural products, and traditional Chinese medicine. They have the potential to counteract COVID-19. This virus immediately affects the liver and causes a decrease in oxygen levels. In this study, multiple vacciome approaches were employed for designing a multi-epitope subunit vaccine for battling against SARS-COV-2. Vaccine designing, immunogenicity, allergenic, and physico-chemical assessment were performed by using the vacciome approach. The vaccine design is likely to be antigenic and produce potent interactions with ACE2 and NSP3 receptors. The developed vaccine has also been given to in-silico cloning models and immune response predictions. A total number of 12 CTL and 12 HTL antigenic epitopes were predicted from three selected covid-19 virulent proteins (spike protein, nucleocapsid protein, and membrane proteins, respectively) based on C-terminal cleavage and MHC binding scores. These predicted epitopes were amalgamated by AYY and GPGPG linkers, and a β-defensins adjuvant was inserted into the N-terminus of this vaccine. This analysis shows that the recommended vaccine can produce immune responses against SARS-COV-2. Designing and developing of the mentioned vaccine will require further experimental validation.

Immunoinformatics Approaches in Designing Vaccines Against COVID-19

Since the onset of the COVID-19 pandemic, a number of approaches have been adopted by the scientific communities for developing efficient vaccine candidate against SARS-CoV-2. Conventional approaches of developing a vaccine require a long time and a series of trials and errors which indeed limit the feasibility of such approaches for developing a dependable vaccine in an emergency situation like the COVID-19 pandemic. Hitherto, most of the available vaccines have been developed against a particular antigen of SARS-CoV, spike protein in most of the cases, and intriguingly, these vaccines are not effective against all the pathogenic coronaviruses. In this context, immunoinformatics-based reverse vaccinology approaches enable a robust design of efficacious peptide-based vaccines against all the infectious strains of coronaviruses within a short frame of time. In this chapter, we enumerate the methodological trajectory of developing a universal anti-SARS-CoV-2 vaccine, namely, "AbhiSCoVac," through advanced computational biology-based immunoinformatics approach and its in-silico validation using molecular dynamics simulations.

Designing a multi-epitope vaccine against coxsackievirus B based on immunoinformatics approaches

Coxsackievirus B (CVB) is one of the major viral pathogens of human myocarditis and cardiomyopathy without any effective preventive measures; therefore, it is necessary to develop a safe and efficacious vaccine against CVB. Immunoinformatics methods are both economical and convenient as in-silico simulations can shorten the development time. Herein, we design a novel multi-epitope vaccine for the prevention of CVB by using immunoinformatics methods. With the help of advanced immunoinformatics approaches, we predicted different B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes, respectively. Subsequently, we constructed the multi-epitope vaccine by fusing all conserved epitopes with appropriate linkers and adjuvants. The final vaccine was found to be antigenic, non-allergenic, and stable. The 3D structure of the vaccine was then predicted, refined, and evaluated. Molecular docking and dynamics simulation were performed to reveal the interactions between the vaccine with the immune receptors MHC-I, MHC-II, TLR3, and TLR4. Finally, to ensure the complete expression of the vaccine protein, the sequence of the designed vaccine was optimized and further performed in-silico cloning. In conclusion, the molecule designed in this study could be considered a potential vaccine against CVB infection and needed further experiments to evaluate its safety and efficacy.

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.

Immunoinformatic-based design of immune-boosting multiepitope subunit vaccines against monkeypox virus and validation through molecular dynamics and immune simulation

Monkeypox virus is the causative agent of monkeypox disease, belonging to an orthopoxvirus genus, with a disease pattern similar to that of smallpox. The number of monkeypox cases have robustly increased recently in several countries around the world, potentially causing an international threat. Therefore, serious measures are indispensable to be taken to mitigate the spread of the disease and hence, under these circumstances, vaccination is the best choice to neutralize the monkeypox virus. In the current study, we used immunoinformatic approaches to target the L1R, B5R, and A33R proteins of the monkeypox virus to screen for immunogenic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes to construct multiepitope subunit vaccines. Various online tools predicted the best epitope from immunogenic targets (L1R, B5R, and A33R) of monkeypox virus. The predicted epitopes were joined together by different linkers and subjected to 3D structure prediction. Molecular dynamics simulation analysis confirmed the proper folding of the modeled proteins. The strong binding of the constructed vaccines with human TLR-2 was verified by the molecular docking and determination of dissociation constant values. The GC content and codon adaptation index (CAI) values confirmed the high expression of the constructed vaccines in the pET-28a (+) expression vector. The immune response simulation data delineated that the injected vaccines robustly activated the immune system, triggering the production of high titers of IgG and IgM antibodies. In conclusion, this study provided a solid base of concept to develop dynamic and effective vaccines that contain several monkeypox virus-derived highly antigenic and nonallergenic peptides to control the current pandemic of monkeypox virus.

Traditional Chinese medicine treatment for COVID-19: An overview of systematic reviews and meta-analyses

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a rapidly spreading disease that has caused an extensive burden to the world. Consequently, a large number of clinical trials have examined the efficacy of traditional Chinese medicine (TCM) for treating and preventing COVID-19, with coinciding proliferation of reviews summarizing these studies.

OBJECTIVE

This study aimed to evaluate the methodological quality and evidence quality of systematic reviews and meta-analyses on the efficacy of TCM.

SEARCH STRATEGY

Seven electronic databases, including PubMed, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Chongqing VIP, Wanfang Data and SinoMed, were searched for systematic reviews and meta-analyses in October 2021. Search terms such as "Chinese medicine," "Lianhua Qingwen" and "COVID-19" were used.

INCLUSION CRITERIA

Systematic reviews and meta-analyses of randomized controlled trials that evaluated the efficacy of TCM treatment of COVID-19 were included.

DATA EXTRACTION AND ANALYSIS

A Measurement Tool to Assess Systematic Reviews Version 2.0 (AMSTAR 2) was used to evaluate the methodological quality. The quality of evidence was graded using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. Data extraction and analysis were performed by two reviewers independently.

RESULTS

There were 17 meta-analyses included in our overview. The intervention group was defined as TCM combined with Western medicine, while the control group was Western medicine alone. The methodological quality of all the included studies was moderate to poor. A total of 89 outcome indicators were evaluated, of which, 8 were rated as moderate quality, 39 as low quality, and 41 as very low quality. Only one outcome measure was graded as being of high quality. The moderate quality of evidence indicated that, for the treatment of COVID-19, the clinical efficacy of TCM in combination with Western medicine was better, in terms of lung recovery, rate of conversion to severe/critical cases, symptom scores, duration of symptoms, mortality, and length of hospital stay.

CONCLUSION

Evidence from the included studies shows that, compared with conventional Western medical therapy alone, the addition of TCM to COVID-19 treatment may improve clinical outcomes. Overall, the quality of evidence of TCM for COVID-19 was moderate to poor. Meta-analyses of the use of TCM in the treatment of COVID-19 can be used for clinical decision making by accounting for the experiences of clinical experts, medical policies, and other factors.

Imperative persistent interaction analysis of anticancer noscapine-ionic liquid with calf thymus DNA

In this study, we have shown the interaction between opium poppy alkaloid noscapine-based ionic liquid [Pip-Nos]OTf and ct-DNA using UV-visible absorption spectroscopy, fluorescence spectroscopy, CD, and computational studies. The absorption spectra showed a hypochromic shift with no shift in the absorption maxima suggesting groove or electrostatic binding. Fluorescence spectra showed an enhancement in fluorescence emission suggesting that the probable mode of binding should be groove binding. Ethidium bromide (EB) competitive and Ionic strength study showed the absence of intercalative and electrostatic modes of interaction. Further, CD analysis of ct-DNA suggested a groove binding mode of interaction of [Pip-Nos]OTf with ct-DNA. [Pip-Nos]OTf displayed a strong binding with the target ct-DNA with a molecular docking score of -41.47 kJ/mol with all 3D coordinates and full conformation. Also, molecular binding contact analyses depicted the stable binding of drug and ct-DNA with potential hydrogen bonds and hydrophobic interactions. The structural superimposition dynamics analysis showed the stable binding of [Pip-Nos]OTf with the ct-DNA model through RMSD statistics. Moreover, the ligand interaction calculations revealed the involvement of large binding energy along with a high static number of molecular forces including the hydrogen bonds and hydrophobic interactions in their complexation. These significant results report the potency of [Pip-Nos]OTf and its important futuristic role in cancer therapeutics.

Exploring whole proteome to contrive multi-epitope-based vaccine for NeoCoV: An immunoinformtics and in-silico approach

Neo-Coronavirus (NeoCoV) is a novel Betacoronavirus (β-CoVs or Beta-CoVs) discovered in bat specimens in South Africa during 2011. The viral sequence is highly similar to Middle East Respiratory Syndrome, particularly that of structural proteins. Thus, scientists have emphasized the threat posed by NeoCoV associated with human angiotensin-converting enzyme 2 (ACE2) usage, which could lead to a high death rate and faster transmission rate in humans. The development of a NeoCoV vaccine could provide a promising option for the future control of the virus in case of human infection. In silico predictions can decrease the number of experiments required, making the immunoinformatics approaches cost-effective and convenient. Herein, with the aid of immunoinformatics and reverse vaccinology, we aimed to formulate a multi-epitope vaccine that may be used to prevent and treat NeoCoV infection. Based on the NeoCoV proteins, B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes were shortlisted. Four vaccines (Neo-1-4) were devised by fusing shortlisted epitopes with appropriate adjuvants and linkers. The secondary and three-dimensional structures of final vaccines were then predicted. The binding interactions of these potential vaccines with toll-like immune receptors (TLR-2, TLR-3, and TLR-4) and major histocompatibility complex molecules (MHC-I and II) reveal that they properly fit into the receptors' binding domains. Besides, Neo-1 and Neo-4 vaccines exhibited better docking energies of -101.08 kcal/mol and -114.47 kcal/mol, respectively, with TLR-3 as compared to other vaccine constructs. The constructed vaccines are highly antigenic, non-allergenic, soluble, non-toxic, and topologically assessable with good physiochemical characteristics. Codon optimization and in-silico cloning confirmed efficient expression of the designed vaccines in Escherichia coli strain K12. In-silico immune simulation indicated that Neo-1 and Neo-4 vaccines could induce a strong immune response against NeoCoV. Lastly, the binding stability and strong binding affinity of Neo-1 and Neo-4 with TLR-3 receptor were validated using molecular dynamics simulations and free energy calculations (Molecular Mechanics/Generalized Born Surface Area method). The final vaccines require experimental validation to establish their safety and effectiveness in preventing NeoCoV infections.

In Silico Studies on Zinc Oxide Based Nanostructured Oil Carriers with Seed Extracts of Nigella sativa and Pimpinella anisum as Potential Inhibitors of 3CL Protease of SARS-CoV-2

Coming into the second year of the pandemic, the acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants continue to be a serious health hazard globally. A surge in the omicron wave, despite the discovery of the vaccines, has shifted the attention of research towards the discovery and use of bioactive compounds, being potential inhibitors of the viral structural proteins. The present study aimed at the green synthesis of zinc oxide (ZnO) nanoparticles with seed extracts of Nigella sativa and Pimpinella anisum—loaded nanostructured oil carriers (NLC)—using a mixture of olive and black seed essential oils. The synthesized ZnO NLC were extensively characterized. In addition, the constituent compounds in ZnO NLC were investigated as a potential inhibitor for the SARS-CoV-2 main protease (3CLpro or Mpro) where 27 bioactive constituents, along with ZnO in the nanostructure, were subjected to molecular docking studies. The resultant high-score compounds were further validated by molecular dynamics simulation. The study optimized the compounds dithymoquinone, δ-hederin, oleuropein, and zinc oxide with high docking energy scores (ranging from −7.9 to −9.9 kcal/mol). The RMSD and RMSF data that ensued also mirrored these results for the stability of proteins and ligands. RMSD and RMSF data showed no conformational change in the protein during the MD simulation. Histograms of every simulation trajectory explained the ligand properties and ligand–protein contacts. Nevertheless, further experimental investigations and validation of the selected candidates are imperative to take forward the applicability of the nanostructure as a potent inhibitor of COVID-19 (Coronavirus Disease 2019) for clinical trials.

Molecular dynamics simulation approach for discovering potential inhibitors against SARS-CoV-2: A structural review

Since the commencement of the novel Coronavirus, the disease has quickly turned into a worldwide crisis so that there has been growing attention in discovering possible hit compounds for tackling this pandemic. Discovering standard treatment strategies is a serious challenge because little information is available about this emerged infectious virus. Regarding the high impact of time, applying computational procedures to choose promising drugs from a catalog of licensed medications provides a precious chance for combat against the life-threatening disorder of COVID-19. Molecular dynamics (MD) simulation is a promising approach for assessing the binding affinity of ligand-receptor as well as observing the conformational trajectory of docked complexes over time. Given that many computational studies are performed using MD along with the molecular docking on various candidates as antiviral inhibitors of COVID-19 protease, there is a demand to conduct a comprehensive review of the most important studies to reveal and compare the potential introduced agents that this study covers this defect. In this context, the present review intends to prepare an overview of these studies by considering RMSD, RMSF, radius of gyration, binding free energy, and Solvent-Accessible Surface Area (SASA) as effective parameters for evaluation. The outcomes will offer a road map for adjusting antiviral inhibitors, which can facilitate the selection and development of drug candidates for use in the medical therapy. Finally, the molecular modeling approaches rendered by this study may be valuable for future computational studies.

Novel Strategies of Immunization against COVID-19

COVID-19 manifested itself as a global pandemic in 2019 but even in 2021, it is still not successfully contained. This virus has claimed millions of lives worldwide and rendered many more jobless. Apart from causing mild to severe pneumonia, the virus has also caused a loss of livelihood for thousands globally, along with widespread trauma and depression. Since the transmission rate of the virus is so high, temporary prophylaxis relied on sanitization, wearing masks and physical distancing. However, a long-term solution for stopping viral spread is vaccination. Apart from being the fastest way to induce immunity against the virus, vaccination is also the cheapest and most practical way. However, a vaccine can only be commercially available after it has passed through various clinical trial phases. So far, more than two hundred potential vaccine candidates underwent different phases of the clinical trial, and some of the front-runners have shown more than 90% efficacy. This review has compiled all such vaccine candidates, their types, their modes of action, and the associated pros and cons. The current advances in clinical trials of vaccines have also been discussed, such as plant-based and cocktail vaccines that have recently emerged. Nowadays, novel strains like Delta plus are also emerging and posing a threat. Thus, it is mandatory to get vaccinated and choose a vaccine that provides long-term protection against multiple strains.

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.

Target-based drug discovery, ADMET profiling and bioactivity studies of antibiotics as potential inhibitors of SARS-CoV-2 main protease (Mpro)

A recent outbreak of a new strain of Coronavirus (SARS-CoV-2) has become a global health burden, which has resulted in deaths. No proven drug has been found to effectively cure this fast-spreading infection, hence the need to explore old drugs with the known profile in tackling this pandemic. A computer-aided drug design approach involving virtual screening was used to obtain the binding scores and inhibiting efficiencies of previously known antibiotics against SARS-CoV-2 main protease (Mpro). The drug-likeness analysis of the repurposed drugs were done using the Molinspiration chemoinformatics tool, while the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis was carried out using ADMET SAR-2 webserver. Other analyses performed include bioactivities of the repurposed drug as a probable anti-SARS-CoV-2 agent and oral bioavailability analyses among others. The results were compared with those of drugs currently involved in clinical trials in the ongoing pandemic. Although antibiotics have been speculated to be of no use in the treatment of viral infections, literature has emerged lately to reveal the antiviral potential and immune-boosting ability of antibiotics. This study identified Tarivid and Ciprofloxacin with binding affinities of - 8.3 kcal/mol and - 8.1 kcal/mol, respectively as significant inhibitors of SARS-CoV-2 (Mpro) with better pharmacokinetics, drug-likeness and oral bioavailability, bioactivity properties, ADMET properties and inhibitory strength compared to Remdesivir (- 7.6 kcal/mol) and Azithromycin (- 6.3 kcal/mol). These observations will provide insight for further research (clinical trial) in the cure and management of COVID-19.

In silico vaccine design and epitope mapping of New Delhi metallo-beta-lactamase (NDM): an immunoinformatics approach

BACKGROUND

Antibiotic resistance is a global health crisis. The adage that "prevention is better than cure" is especially true regarding antibiotic resistance because the resistance appears and spreads much faster than the production of new antibiotics. Vaccination is an important strategy to fight infectious agents; however, this strategy has not attracted sufficient attention in antibiotic resistance prevention. New Delhi metallo-beta-lactamase (NDM) confers resistance to many beta-lactamases, including important carbapenems like imipenem. Our goal in this study is to use an immunoinformatics approach to develop a vaccine that can elicit strong and specific immune responses against NDMs that prevent the development of antibiotic-resistant bacteria.

RESULTS

In this study, 2194 NDM sequences were aligned to obtain a conserved sequence. One continuous B cell epitope and three T cell CD4+ epitopes were selected from NDMs conserved sequence. Epitope conservancy for B cell and HLA-DR, HLA-DQ, and HLA-DP epitopes was 100.00%, 99.82%, 99.41%, and 99.86%, respectively, and population coverage of MHC II epitopes for the world was 99.91%. Permutation of the four epitope fragments resulted in 24 different peptides, of which 6 peptides were selected after toxicity, allergenicity, and antigenicity assessment. After primary vaccine design, only one vaccine sequence with the highest similarity with discontinuous B cell epitope in NDMs was selected. The final vaccine can bind to various Toll-like receptors (TLRs). The prediction implied that the vaccine would be stable with a good half-life. An immune simulation performed by the C-IMMSIM server predicted that two doses of vaccine injection can induce a strong immune response to NDMs. Finally, the GC-Content of the vaccine was designed very similar to E. coli K12.

CONCLUSIONS

In this study, immunoinformatics strategies were used to design a vaccine against different NDM variants that could produce an effective immune response against this antibiotic-resistant factor.

Exploring the room for repurposed hydroxychloroquine to impede COVID-19: toxicities and multipronged combination approaches with pharmaceutical insights

Introduction: SARS-CoV-2 has fatally affected the whole world with millions of deaths. Amidst the dilemma of a breakthrough in vaccine development, hydroxychloroquine (HCQ) was looked upon as a prospective repurposed candidate. It has confronted numerous controversies in the past few months as a chemoprophylactic and treatment option for COVID-19. Recently, it has been withdrawn by the World Health Organization for its use in an ongoing pandemic. However, its benefit/risk ratio regarding its use in COVID-19 disease remains poorly justified. An extensive literature search was done using Scopus, PubMed, Google Scholar, www.cdc.gov, www.fda.gov, and who.int.Areas covered: Toxicity vexations of HCQ; pharmaceutical perspectives on new advances in drug delivery approaches; computational modeling (PBPK and PD modeling) overtures; multipronged combination approaches for enhanced synergism with antiviral and anti-inflammatory agents; immuno-boosting effects.Expert commentary: Harnessing the multipronged pharmaceutical perspectives will optimistically help the researchers, scientists, biotech, and pharmaceutical companies to bring new horizons in the safe and efficacious utilization of HCQ alone or in combination with remdesivir and immunomodulatory molecules like bovine lactoferrin in a fight against COVID-19. Combinational therapies with free forms or nanomedicine based targeted approaches can act synergistically to boost host immunity and stop SARS-CoV-2 replication and invasion to impede the infection.

Exploring SARS-COV-2 structural proteins to design a multi-epitope vaccine using immunoinformatics approach: An in silico study

In December 2019, a new virus called SARS-CoV-2 was reported in China and quickly spread to other parts of the world. The development of SARS-COV-2 vaccines has recently received much attention from numerous researchers. The present study aims to design an effective multi-epitope vaccine against SARS-COV-2 using the reverse vaccinology method. In this regard, structural proteins from SARS-COV-2, including the spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins, were selected as target antigens for epitope prediction. A total of five helper T lymphocytes (HTL) and five cytotoxic T lymphocytes (CTL) epitopes were selected after screening the predicted epitopes for antigenicity, allergenicity, and toxicity. Subsequently, the selected HTL and CTL epitopes were fused via flexible linkers. Next, the cholera toxin B-subunit (CTxB) as an adjuvant was linked to the N-terminal of the chimeric structure. The proposed vaccine was analyzed for the properties of physicochemical, antigenicity, and allergenicity. The 3D model of the vaccine construct was predicted and docked with the Toll-like receptor 4 (TLR4). The molecular dynamics (MD) simulation was performed to evaluate the stable interactions between the vaccine construct and TLR4. The immune simulation was also conducted to explore the immune responses induced by the vaccine. Finally, in silico cloning of the vaccine construct into the pET-28 (+) vector was conducted. The results obtained from all bioinformatics analysis stages were satisfactory; however, in vitro and in vivo tests are essential to validate these results.

A computational study to disclose potential drugs and vaccine ensemble for COVID-19 conundrum

The nucleocapsid (N) protein of SARS-COV-2, a virus responsible for the current COVID-19 pandemic, is considered a potential candidate for the design of new drugs and vaccines. The protein is central to several critical events in virus production, with its highly druggable nature and rich antigenic determinants making it an excellent anti-viral biomolecule. Docking-based virtual screening using the Asinex anti-viral library identified binding of drug molecules at three specific positions: loop 1 region, loop 2 region and β-sheet core pockets, the loop 2 region being the most common binding and stable site for the bulk of the molecules. In parallel, the protein was characterized by vaccine design perspective and harboured three potential B cell-derived T cell epitopes: PINTNSSPD, GVPINTNSS, and DHIGTRNPA. The epitopes are highly antigenic, virulent, non-allergic, non-toxic, bind with good affinity to the highly prevalent DRB*0101 allele and show an average population coverage of 95.04%. A multi-epitope vaccine ensemble which was 83 amino acids long was created. This was highly immunogenic, robust in generating both humoral and cellular immune responses, thermally stable, and had good physicochemical properties that could be easily analyzed in in vivo and in vitro studies. Conformational dynamics of both drug and vaccine ensemble with respect to the receptors are energetically stable, shedding light on favourable conformation and chemical interactions. These facts were validated by subjecting the complexes to relative and absolute binding free energy methods of MMGB/PBSA and WaterSwap. A strong agreement on the system stability was disclosed that supported ligand high affinity potential for the receptors. Collectively, this work sought to provide preliminary experimental data of existing anti-viral drugs as a possible therapy for COVID-19 infections and a new peptide-based vaccine for protection against this pandemic virus.

Mitigate the cytokine storm due to the severe COVID-19: A computational investigation of possible allosteric inhibitory actions on IL-6R and IL-1R using selected phytochemicals

The novel corona virus 2019 (COVID 19) is growing at an increasing rate with high mortality. Meanwhile, the cytokine storm is the most dangerous and potentially life-threatening event related to COVID 19. Phyto-compounds found in existing Ayurveda drugs have the ability to inhibit the Interleukin 6 (IL-6R) and Interleukin 1 (IL-1R) receptors. IL-6R and IL-1R receptors involve in cytokine storm and recognition of phytochemicals with proven safety profiles could open a pathway to the development of the most effective drugs against cytokine storm. In this study, we intend to perform an in silico investigation of effective phyto compounds, which can be isolated from selected medicinal herbs to avoid cytokine storm, inhibiting the IL-6 and IL-1 receptor binding process. An extensive literature survey followed by virtual screening was carried out to identify phytochemicals with potential anti-hyper-inflammatory action. Flexible docking was conducted for validated models of IL-1R and IL-6R-α with the most promising phytochemicals at possible allosteric sites using AutoDock Vina. Molecular dynamics (MD) studies were conducted for selected protein-ligand complexes using LARMD server and conformational changes were evaluated. According to the results, taepeenin J had Gibbs energy (ΔG) of -10.85 kcal/mol towards IL-1R but had limited oral bioavailability. MD analysis revealed that taepeenin J can cause significant conformational movements in IL-1R. Nortaepeenin B showed a ΔG of -8.5 kcal/mol towards IL-6R-α with an excellent oral bioavailability. MD analysis predicted that it can cause significant conformational movements in IL-6R-α. Hence, the evaluated phytochemicals are potential candidates for further in vitro studies for the development of medicine against cytokine storm on behalf of SARS-COV-2 infected patients.