Towards a novel peptide vaccine for Middle East respiratory syndrome coronavirus and its possible use against pandemic COVID-19

Insights into structural vaccinology harnessed for universal coronavirus vaccine development

Structural vaccinology is pivotal in expediting vaccine design through high-throughput screening of immunogenic antigens. Leveraging the structural and functional characteristics of antigens and immune cell receptors, this approach employs protein structural comparison to identify conserved patterns in key pathogenic components. Molecular modeling techniques, including homology modeling and molecular docking, analyze specific three-dimensional (3D) structures and protein interactions and offer valuable insights into the 3D interactions and binding affinity between vaccine candidates and target proteins. In this review, we delve into the utilization of various immunoinformatics and molecular modeling tools to streamline the development of broad-protective vaccines against coronavirus disease 2019 variants. Structural vaccinology significantly enhances our understanding of molecular interactions between hosts and pathogens. By accelerating the pace of developing effective and targeted vaccines, particularly against the rapidly mutating severe acute respiratory syndrome coronavirus 2 and other prevalent infectious diseases, this approach stands at the forefront of advancing immunization strategies. The combination of computational techniques and structural insights not only facilitates the identification of potential vaccine candidates but also contributes to the rational design of vaccines, fostering a more efficient and targeted approach to combatting infectious diseases.

Development of a novel circular mRNA vaccine of six protein combinations against Staphylococcus aureus

Staphylococcus aureus is an extraordinarily versatile pathogen, which is currently the most common cause of nosocomial and community infections. Considering that increased antibiotic resistance may hasten the spread of S. aureus, developing an effective vaccine can possibly aid in its control. The RNA vaccine coding immunodominance epitopes from bacteria provide a potential method to induce T and B cell immune responses by translating them into cells. Furthermore, using bioinformatics to create circular RNA vaccines can ensure that the translation of the vaccine is potent and durable. In this study, 7 cytotoxic T lymphocyte (CTL) epitopes, 4 helper T lymphocyte (HTL) epitopes, and 15 B cell epitopes from 6 proteins that are closely associated with the S. aureus virulence and invasion and critical to natural immune responses were mapped. To verify their interactions, all epitopes were docked with the corresponding MHC alleles. The final vaccine was composed of 26 epitopes and the adjuvant β-defencin, and a disulfide bond was also introduced to improve its stability. After the prediction of structure and characteristics, the developed vaccine was docked with TLR2 and TLR4, which induce immunological responses in S. aureus infection. According to the molecular dynamic simulation, the vaccine might interact strongly with TLRs. Meanwhile, it performed well in immunological simulation and population coverage prediction. Finally, the vaccine was converted into a circular RNA using a series of helper sequences to aid in vaccine circulation translation. Hopefully, this proposed structure will be proven to serve a viable vaccine against S. aureus.Communicated by Ramaswamy H. Sarma.

Automatic diagnosis of COVID-19 from CT images using CycleGAN and transfer learning

The outbreak of the corona virus disease (COVID-19) has changed the lives of most people on Earth. Given the high prevalence of this disease, its correct diagnosis in order to quarantine patients is of the utmost importance in the steps of fighting this pandemic. Among the various modalities used for diagnosis, medical imaging, especially computed tomography (CT) imaging, has been the focus of many previous studies due to its accuracy and availability. In addition, automation of diagnostic methods can be of great help to physicians. In this paper, a method based on pre-trained deep neural networks is presented, which, by taking advantage of a cyclic generative adversarial net (CycleGAN) model for data augmentation, has reached state-of-the-art performance for the task at hand, i.e., 99.60% accuracy. Also, in order to evaluate the method, a dataset containing 3163 images from 189 patients has been collected and labeled by physicians. Unlike prior datasets, normal data have been collected from people suspected of having COVID-19 disease and not from data from other diseases, and this database is made available publicly. Moreover, the method's reliability is further evaluated by calibration metrics, and its decision is interpreted by Grad-CAM also to find suspicious regions as another output of the method and make its decisions trustworthy and explainable.

Structural and non-structural proteins in SARS-CoV-2: potential aspects to COVID-19 treatment or prevention of progression of related diseases

Coronavirus disease 2019 (COVID-19) is caused by a new member of the Coronaviridae family known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There are structural and non-structural proteins (NSPs) in the genome of this virus. S, M, H, and E proteins are structural proteins, and NSPs include accessory and replicase proteins. The structural and NSP components of SARS-CoV-2 play an important role in its infectivity, and some of them may be important in the pathogenesis of chronic diseases, including cancer, coagulation disorders, neurodegenerative disorders, and cardiovascular diseases. The SARS-CoV-2 proteins interact with targets such as angiotensin-converting enzyme 2 (ACE2) receptor. In addition, SARS-CoV-2 can stimulate pathological intracellular signaling pathways by triggering transcription factor hypoxia-inducible factor-1 (HIF-1), neuropilin-1 (NRP-1), CD147, and Eph receptors, which play important roles in the progression of neurodegenerative diseases like Alzheimer's disease, epilepsy, and multiple sclerosis, and multiple cancers such as glioblastoma, lung malignancies, and leukemias. Several compounds such as polyphenols, doxazosin, baricitinib, and ruxolitinib could inhibit these interactions. It has been demonstrated that the SARS-CoV-2 spike protein has a stronger affinity for human ACE2 than the spike protein of SARS-CoV, leading the current study to hypothesize that the newly produced variant Omicron receptor-binding domain (RBD) binds to human ACE2 more strongly than the primary strain. SARS and Middle East respiratory syndrome (MERS) viruses against structural and NSPs have become resistant to previous vaccines. Therefore, the review of recent studies and the performance of current vaccines and their effects on COVID-19 and related diseases has become a vital need to deal with the current conditions. This review examines the potential role of these SARS-CoV-2 proteins in the initiation of chronic diseases, and it is anticipated that these proteins could serve as components of an effective vaccine or treatment for COVID-19 and related diseases. Video Abstract.

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.

mRNA vaccines in the prevention and treatment of diseases

Messenger ribonucleic acid (mRNA) vaccines made their successful public debut in the effort against the COVID-19 outbreak starting in late 2019, although the history of mRNA vaccines can be traced back decades. This review provides an overview to discuss the historical course and present situation of mRNA vaccine development in addition to some basic concepts that underly mRNA vaccines. We discuss the general preparation and manufacturing of mRNA vaccines and also discuss the scientific advances in the in vivo delivery system and evaluate popular approaches (i.e., lipid nanoparticle and protamine) in detail. Next, we highlight the clinical value of mRNA vaccines as potent candidates for therapeutic treatment and discuss clinical progress in the treatment of cancer and coronavirus disease 2019. Data suggest that mRNA vaccines, with several prominent advantages, have achieved encouraging results and increasing attention due to tremendous potential in disease management. Finally, we suggest some potential directions worthy of further investigation and optimization. In addition to basic research, studies that help to facilitate storage and transportation will be indispensable for practical applications.

Antiviral activities of 4H-chromen-4-one scaffold-containing flavonoids against SARS-CoV-2 using computational and in vitro approaches

The widespread outbreak of the novel coronavirus called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused the main health challenge worldwide. This pandemic has attracted the attention of the research communities in various fields, prompting efforts to discover rapid drug molecules for the treatment of the life-threatening COVID-19 disease. This study is aimed at investigating 4H-chromen-4-one scaffold-containing flavonoids that combat the SARS-CoV-2 virus using computational and in vitro approaches. Virtual screening studies of the molecule's library for 4H-chromen-4-one scaffold were performed with the recently reported coronavirus main protease (M^pro, also called 3CL^pro) because it plays an essential role in the maturation and processing of the viral polyprotein. Based on the virtual screening, the top hit molecules such as isoginkgetin and afzelin molecules were selected for further estimating in vitro antiviral efficacies against SARS-CoV-2 in Vero cells. Additionally, these molecules were also docked with RNA-dependent RNA Polymerase (RdRp) to reveal the ligands-protein molecular interaction. In the in vitro study, isoginkgetin showed remarkable inhibition potency against the SARS-CoV-2 virus, with an IC₅₀ value of 22.81 μM, compared to remdesivir, chloroquine, and lopinavir with IC₅₀ values of 7.18, 11.63, and 11.49 μM, respectively. Furthermore, the complex stability of isoginkgetin with an active binding pocket of the SARS-CoV-2 M^pro and RdRp supports its inhibitory potency against the SARS-CoV-2. Thus, isoginkgetin is a potent leading drug candidate and needs to be used in in vivo trials for the treatment of SARS-CoV-2 infected patients.

Modeling and simulations of CoViD-19 molecular mechanism induced by cytokines storm during SARS-CoV2 infection

It is highly desired to explore the interventions of COVID-19 for early treatment strategies. Such interventions are still under consideration. A model is benchmarked research and comprises target cells, virus infected cells, immune cells, pro-inflammatory cytokines, and, anti-inflammatory cytokine. The interaction of the drug with the inflammatory sub-system is analyzed with the aid of kinetic modeling. The impact of drug therapy on the immune cells is modelled and the computational framework is verified with the aid of numerical simulations. The work includes a significant hypothesis that quantifies the complex dynamics of the infection, by relating it to the effect of the inflammatory syndrome generated by IL-6. In this paper we use the cancer immunoediting process: a dynamic process initiated by cancer cells in response to immune surveillance of the immune system that it can be conceptualized by an alternating movement that balances immune protection with immune evasion. The mechanisms of resistance to immunotherapy seem to broadly overlap with those used by cancers as they undergo immunoediting to evade detection by the immune system. In this process the immune system can both constrain and promote tumour development, which proceeds through three phases termed: (i) Elimination, (ii) Equilibrium, and, (iii) Escape [1]. We can also apply these concepts to viral infection, which, although it is not exactly “immunoediting”, has many points in common and helps to understand how it expands into an “untreated” host and can help in understanding the SARS-CoV2 virus infection and treatment model.