Prioritization of SARS-CoV-2 epitopes using a pan-HLA and global population inference approach

The Influence of HLA Polymorphisms on the Severity of COVID-19 in the Romanian Population

In this study, we aimed to investigate whether specific HLA alleles found in patients from Romania and the Republic of Moldova were associated with the severity of COVID-19 infection and its associated mortality. We analyzed the HLA alleles at the -A, -B, -C, -DRB1, and -DQB1 loci in a cohort of 130 individuals with severe and extremely severe forms of COVID-19, including 44 individuals who died. We compared these findings to a control group consisting of individuals who had either not been diagnosed with COVID-19 or had experienced mild forms of the disease. Using multivariate logistic regression models, we discovered that the B*27 and B*50 alleles were associated with an increased susceptibility to developing a severe form of COVID-19. The A*33 and C*15 alleles showed potential for offering protection against the disease. Furthermore, we identified two protective alleles (A*03 and DQB1*02) against the development of extremely severe forms of COVID-19. By utilizing score statistics, we established a statistically significant association between haplotypes and disease severity (p = 0.021). In summary, this study provides evidence that HLA genotype plays a role in influencing the clinical outcome of COVID-19 infection.

Pressured cytotoxic T cell epitope strength among SARS-CoV-2 variants correlates with COVID-19 severity

Heterogeneity in susceptibility among individuals to COVID-19 has been evident through the pandemic worldwide. Cytotoxic T lymphocyte (CTL) responses generated against pathogens in certain individuals are known to impose selection pressure on the pathogen, thus driving emergence of new variants. In this study, we probe the role played by host genetic heterogeneity in terms of HLA-genotypes in determining differential COVID-19 severity in patients. We use bioinformatic tools for CTL epitope prediction to identify epitopes under immune pressure. Using HLA-genotype data of COVID-19 patients from a local cohort, we observe that the recognition of pressured epitopes from the parent strain Wuhan-Hu-1 correlates with COVID-19 severity. We also identify and rank list HLA-alleles and epitopes that offer protectivity against severe disease in infected individuals. Finally, we shortlist a set of 6 pressured and protective epitopes that represent regions in the viral proteome that are under high immune pressure across SARS-CoV-2 variants. Identification of such epitopes, defined by the distribution of HLA-genotypes among members of a population, could potentially aid in prediction of indigenous variants of SARS-CoV-2 and other pathogens.

Large libraries of single-chain trimer peptide-MHCs enable antigen-specific CD8+ T cell discovery and analysis

The discovery and characterization of antigen-specific CD8+ T cell clonotypes typically involves the labor-intensive synthesis and construction of peptide-MHC tetramers. We adapt single-chain trimer (SCT) technologies into a high throughput platform for pMHC library generation, showing that hundreds can be rapidly prepared across multiple Class I HLA alleles. We use this platform to explore the impact of peptide and SCT template mutations on protein expression yield, thermal stability, and functionality. SCT libraries were an efficient tool for identifying T cells recognizing commonly reported viral epitopes. We then construct SCT libraries to capture SARS-CoV-2 specific CD8+ T cells from COVID-19 participants and healthy donors. The immunogenicity of these epitopes is validated by functional assays of T cells with cloned TCRs captured using SCT libraries. These technologies should enable the rapid analyses of peptide-based T cell responses across several contexts, including autoimmunity, cancer, or infectious disease.

HLA-I and HLA-II Peptidomes of SARS-CoV-2: A Review

The adaptive (T-cell-mediated) immune response is a key player in determining the clinical outcome, in addition to neutralizing antibodies, after SARS-CoV-2 infection, as well as supporting the efficacy of vaccines. T cells recognize viral-derived peptides bound to major histocompatibility complexes (MHCs) so that they initiate cell-mediated immunity against SARS-CoV-2 infection or can support developing a high-affinity antibody response. SARS-CoV-2-derived peptides bound to MHCs are characterized via bioinformatics or mass spectrometry on the whole proteome scale, named immunopeptidomics. They can identify potential vaccine targets or therapeutic approaches for SARS-CoV-2 or else may reveal the heterogeneity of clinical outcomes. SARS-CoV-2 epitopes that are naturally processed and presented on the human leukocyte antigen class I (HLA-I) and class II (HLA-II) were identified for immunopeptidomics. Most of the identified SARS-CoV-2 epitopes were canonical and out-of-frame peptides derived from spike and nucleocapsid proteins, followed by membrane proteins, whereby many of which are not caught by existing vaccines and could elicit effective responses of T cells in vivo. This review addresses the detection of SARS-CoV-2 viral epitopes on HLA-I and HLA-II using bioinformatics prediction and mass spectrometry (HLA peptidomics). Profiling the HLA-I and HLA-II peptidomes of SARS-CoV-2 is also detailed.

Identification of evolutionary trajectories shared across human betacoronaviruses

Comparing the evolution of distantly related viruses can provide insights into common adaptive processes related to shared ecological niches. Phylogenetic approaches, coupled with other molecular evolution tools, can help identify mutations informative on adaptation, whilst the structural contextualization of these to functional sites of proteins may help gain insight into their biological properties. Two zoonotic betacoronaviruses capable of sustained human-to-human transmission have caused pandemics in recent times (SARS-CoV-1 and SARS-CoV-2), whilst a third virus (MERS-CoV) is responsible for sporadic outbreaks linked to animal infections. Moreover, two other betacoronaviruses have circulated endemically in humans for decades (HKU1 and OC43). To search for evidence of adaptive convergence between established and emerging betacoronaviruses capable of sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1 and SARS-CoV-2), we developed a methodological pipeline to classify shared non-synonymous mutations as putatively denoting homoplasy (repeated mutations that do not share direct common ancestry) or stepwise evolution (sequential mutations leading towards a novel genotype). In parallel, we look for evidence of positive selection, and draw upon protein structure data to identify potential biological implications. We find 30 mutations, with four of these [codon sites 18121 (nsp14/residue 28), 21623 (spike/21), 21635 (spike/25) and 23948 (spike/796); SARS-CoV-2 genome numbering] displaying evolution under positive selection and proximity to functional protein regions. Our findings shed light on potential mechanisms underlying betacoronavirus adaptation to the human host and pinpoint common mutational pathways that may occur during establishment of human endemicity.

Large libraries of single-chain trimer peptide-MHCs enable rapid antigen-specific CD8+ T cell discovery and analysis

CD8 + cytotoxic T cell responses against viral infection represent a major element of the adaptive immune response. We describe the development of a peptide antigen - major histompatibility complex (pMHC) library representing the full SARS-CoV-2 viral proteome, and comprised of 634 pMHC multimers representing the A*02.01, A*24.02, and B*07.02 HLA alleles, as well as specific antigens associated with the cytomegalovirus (CMV). These libraries were used to capture non-expanded CD8 + T cells from blood samples collected from 64 infected individuals, and then analyzed using single cell RNA-seq. The discovery and characterization of antigen-specific CD8 ⁺ T cell clonotypes typically involves the labor-intensive synthesis and construction of peptide-MHC tetramers. We adapted single-chain trimer (SCT) technologies into a high throughput platform for pMHC library generation, showing that hundreds can be rapidly prepared across multiple Class I HLA alleles. We used this platform to explore the impact of peptide and SCT template mutations on protein expression yield, thermal stability, and functionality. SCT libraries were an efficient tool for identifying T cells recognizing commonly reported viral epitopes. We then constructed SCT libraries designed to capture SARS-CoV-2 specific CD8 ⁺ T cells from COVID-19 participants and healthy donors. The immunogenicity of these epitopes was validated by functional assays of T cells with cloned TCRs captured using SCT libraries. These technologies should enable the rapid analyses of peptide-based T cell responses across several contexts, including autoimmunity, cancer, or infectious disease.

Immunology to Immunotherapeutics of SARS-CoV-2: Identification of Immunogenic Epitopes for Vaccine Development

The emergence of COVID19 pandemic caused by SARS-CoV-2 virus has created a global public health and socio-economic crisis. Immunoinformatics-based approaches to investigate the potential antigens is the fastest way to move towards a multiepitope-based vaccine development. This review encompasses the underlying mechanisms of pathogenesis, innate and adaptive immune signaling along with evasion pathways of SARS-CoV-2. Furthermore, it compiles the promiscuous peptides from in silico studies which are subjected to prediction of cytokine milieu using web-based servers. Out of the 434 peptides retrieved from all studies, we have identified 33 most promising T cell vaccine candidates. This review presents a list of the most potential epitopes from several proteins of the virus based on their immunogenicity, homology, conservancy and population coverage studies. These epitopes can form a basis of second generation of vaccine development as the first generation vaccines in various stages of trials mostly focus only on Spike protein. We therefore, propose them as most potential candidates which can be taken up immediately for confirmation by experimental studies.

Artificial Intelligence-Based Data-Driven Strategy to Accelerate Research, Development, and Clinical Trials of COVID Vaccine

The global COVID-19 (coronavirus disease 2019) pandemic, which was caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a significant loss of human life around the world. The SARS-CoV-2 has caused significant problems to medical systems and healthcare facilities due to its unexpected global expansion. Despite all of the efforts, developing effective treatments, diagnostic techniques, and vaccinations for this unique virus is a top priority and takes a long time. However, the foremost step in vaccine development is to identify possible antigens for a vaccine. The traditional method was time taking, but after the breakthrough technology of reverse vaccinology (RV) was introduced in 2000, it drastically lowers the time needed to detect antigens ranging from 5-15 years to 1-2 years. The different RV tools work based on machine learning (ML) and artificial intelligence (AI). Models based on AI and ML have shown promising solutions in accelerating the discovery and optimization of new antivirals or effective vaccine candidates. In the present scenario, AI has been extensively used for drug and vaccine research against SARS-COV-2 therapy discovery. This is more useful for the identification of potential existing drugs with inhibitory human coronavirus by using different datasets. The AI tools and computational approaches have led to speedy research and the development of a vaccine to fight against the coronavirus. Therefore, this paper suggests the role of artificial intelligence in the field of clinical trials of vaccines and clinical practices using different tools.

Cellular immunity in patients with COVID-19: molecular biology, pathophysiology, and clinical implications

The COVID-19 pandemic is caused by the SARS-CoV-2 coronavirus. From the viewpoint of factors critical to contain the virus, the neutralizing antibodies to SARS-CoV-2 garner most of the attention, however, it is essential to acknowledge that it is the level of the virus-specific T cell and B cell response that forms a basis for an effective neutralizing antibody response. T cell responses develop early and correlate with the protection, but they are relatively attenuated in the severe disease, in part due to lymphopenia. Understanding the role of different T cell subpopulations in the protection or the COVID-19 pathogenesis is critical to the prevention and treatment. The expression profile of different T cell subpopulations varies with the COVID-19 severity and is associated with the degree of T cell responses and the disease outcome. The structural changes in the genome, transcriptome, and proteome of SARS-CoV-2 promote the emergence of new variants of the virus and can reduce its interaction with antibodies and result in avoiding the neutralization. There is a strong correlation between the number of virus-specific CD4 T cells and neutralizing IgG antibody titers against SARS-CoV-2. During the primary viral infection, there is a wide variation in the cellular and humoral immune responses, patients with severe and prolonged symptoms showing highly imbalanced cellular and humoral immune responses. This review focuses on the generation and clinical significance of cellular immunity in the protection against severe acute infection and reinfection, as well as the potential involvement of seasonal coronavirus-specific cross-reactive T cells in response to SARS-CoV-2.

Anxiety and psychological needs of high school students: COVID-19 period

The study aims to examine the relationship between anxiety and psychological needs of high school students during the COVID-19 pandemic period. The fact that the COVID-19 virus poses a threat to mental health as well as physical health, the effects of the pandemic period on the psychological needs and anxiety level of adolescents, especially in a critical developmental stage, and the scarcity of studies concerning adolescent mental health in this period, constituted the purpose of the current study. The quantitative (N = 502) and qualitative data (N = 29) of the study, in which triangulation design was used, were collected from high school students studying in the Southeast of Turkey. In the quantitative part of the research Multiple Linear Regression was implemented and content analysis was used in the qualitative part. The results indicate that love, belonging and power, which are subdimensions of basic psychological needs, are significant predictors of anxiety level. Additionally, it is seen that the need for freedom subdimension is the least predictive variable for the anxiety level. It is concluded that there are moderate negative and significant relationships between the general and subdimensions of basic psychological needs and the level of state anxiety. In this sense, it has been found that the level of anxiety tends to decrease as the level of the satisfaction of basic psychological needs increases. The results in the qualitative analysis part largely overlap with the results in the quantitative part. Suggestions based on the findings of the study are made to researchers.

Antibody and T Cell Immune Responses to SARS-CoV-2 Peptides in COVID-19 Convalescent Patients

Identifying immunogenic targets of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is critical to advance diagnostic and disease control strategies. We analyzed humoral (ELISA) and T-cell (ELISpot) immune responses to spike (S) and nucleocapsid (N) SARS-CoV-2 proteins as well as to human endemic coronavirus (eCoV) peptides in serum from convalescent coronavirus disease 2019 (COVID-19) patients from Tatarstan, Russia. We identified multiple SARS-CoV-2 peptides that were reactive with serum antibodies and T cells from convalescent COVID-19. In addition, age and gender associated differences in the reactivity to S and N protein peptides were identified. Moreover, several SARS-CoV-2 peptides tested negatively correlated with disease severity and lung damage. Cross-reactivity to eCoV peptides was analyzed and found to be lower in COVID-19 compared to controls. In this study, we demonstrate the changing pattern of immunogenic peptide reactivity in COVID-19 serum based on age, gender and previous exposure to eCoVs. These data highlight how humoral immune responses and cytotoxic T cell responses to some of these peptides could contribute to SARS-CoV-2 pathogenesis.

Elucidating T Cell and B Cell Responses to SARS-CoV-2 in Humans: Gaining Insights into Protective Immunity and Immunopathology

The SARS-CoV-2 pandemic is an unprecedented epochal event on at least two fronts. Firstly, in terms of the rapid spread and the magnitude of the outbreak, and secondly, on account of the equally swift response of the scientific community that has galvanized itself into action and has successfully developed, tested and deployed highly effective and novel vaccines in record time to combat the virus. The sophistication and diversification of the scientific toolbox we now have at our disposal has enabled us to interrogate both the breadth and the depth of the immune response to a degree that is unparalleled in recent memory. In terms of our understanding of what is critical to contain the virus and mitigate the effects the pandemic, neutralizing antibodies to SARS-CoV-2 garner most of the attention, however, it is essential to recognize that it is the quality and the fitness of the virus-specific T cell and B cell response that lays the foundation and the backdrop for an effective neutralizing antibody response. In this report, we will review some of the key findings that have helped define and delineate some of the essential attributes of T and B cell responses in the setting of SARS-CoV-2 infection.

Nanotechnology-empowered vaccine delivery for enhancing CD8+ T cells-mediated cellular immunity

After centuries of development, using vaccination to stimulate immunity has become an effective method for prevention and treatment of a variety of diseases including infective diseases and cancers. However, the tailor-made efficient delivery system for specific antigens is still urgently needed due to the low immunogenicity and stability of antigens, especially for vaccines to induce CD8⁺ T cells-mediated cellular immunity. Unlike B cells-mediated humoral immunity, CD8⁺ T cells-mediated cellular immunity mainly aims at the intracellular antigens from microorganism in virus-infected cells or genetic mutations in tumor cells. Therefore, the vaccines for stimulating CD8⁺ T cells-mediated cellular immunity should deliver the antigens efficiently into the cytoplasm of antigen presenting cells (APCs) to form major histocompatibility complex I (MHCI)-antigen complex through cross-presentation, followed by activating CD8⁺ T cells for immune protection and clearance. Importantly, nanotechnology has been emerged as a powerful tool to facilitate these multiple processes specifically, allowing not only enhanced antigen immunogenicity and stability but also APCs-targeted delivery and elevated cross-presentation. This review summarizes the process of CD8⁺ T cells-mediated cellular immunity induced by vaccines and the technical advantages of nanotechnology implementation in general, then provides an overview of the whole spectrum of nanocarriers studied so far and the recent development of delivery nanotechnology in vaccines against infectious diseases and cancer. Finally, we look forward to the future development of nanotechnology for the next generation of vaccines to induce CD8⁺ T cells-mediated cellular immunity.

Insights into Innate Immune Response Against SARS-CoV-2 Infection

The innate immune system is mandatory for the activation of antiviral host defense and eradication of the infection. In this regard, dendritic cells, natural killer cells, macrophages, neutrophils representing the cellular component, and cytokines, interferons, complement or Toll-Like Receptors, representing the mediators of unspecific response act together for both activation of the adaptive immune response and viral clearance. Of great importance is the proper functioning of the innate immune response from the very beginning. For instance, in the early stages of viral infection, the defective interferon response leads to uncontrolled viral replication and pathogen evasion, while hypersecretion during the later stages of infection generates hyperinflammation. This cascade activation of systemic inflammation culminates with cytokine storm syndrome and hypercoagulability state, due to a close interconnection between them. Thus an unbalanced reaction, either under- or over- stimulation of the innate immune system will lead to an uncoordinated response and unfavorable disease outcomes. Since both cellular and humoral factors are involved in the time-course of the innate immune response, in this review we aimed to address their gradual involvement in the antiviral response with emphasis on key steps in SARS-CoV-2 infection.

Immunogenic SARS-CoV2 Epitopes Defined by Mass Spectrometry

SARS-CoV-2 infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID19, the disease caused by SARS-CoV-2, T cell responses are important in mediating recovery and immune-protection. The identification of immunogenic epitopes that can elicit a meaningful T cell response can be elusive. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes; however, our previous studies find that 'immunodominant' SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing SARS-CoV-2. We postulated that immunogenic epitopes for SARS-CoV-2 are best defined by directly analyzing peptides eluted from the peptide-MHC complex and then validating immunogenicity empirically by determining if such peptides can elicit T cells recognizing SARS-CoV-2 antigen-expressing cells. Using a tandem mass spectrometry approach, we identified epitopes of SARS-CoV-2 derived not only from structural but also non-structural genes in regions highly conserved among SARS-CoV-2 strains including recently recognized variants. We report here, for the first time, several novel SARS-CoV-2 epitopes from membrane glycol-protein (MGP) and non-structure protein-13 (NSP13) defined by mass-spectrometric analysis of MHC-eluted peptides, provide empiric evidence for their immunogenicity to induce T cell response.

Significance Statement

Current state of the art uses putative epitope peptides based on in silico prediction algorithms to evaluate the T cell response among COVID-19 patients. However, none of these peptides have been tested for immunogenicity, i.e. the ability to elicit a T cell response capable of recognizing endogenously presented peptide. In this study, we used MHC immune-precipitation, acid elution and tandem mass spectrometry to define the SARS-CoV-2 immunopeptidome for membrane glycol-protein and the non-structural protein. Furthermore, taking advantage of a highly robust endogenous T cell (ETC) workflow, we verify the immunogenicity of these MS-defined peptides by in vitro generation of MGP and NSP13 peptide-specific T cells and confirm T cell recognition of MGP or NSP13 endogenously expressing cell lines.

In Silico Defined SARS-CoV2 Epitopes May Not Predict Immunogenicity to COVID19

SARS-CoV-2 infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID19, the disease caused by SARS-CoV-2, it has become increasingly apparent that T cell responses are equally, if not more important than humoral responses in mediating recovery and immune-protection. One of the major challenges in developing T cell-based therapies for infectious and malignant diseases has been the identification of immunogenic epitopes that can elicit a meaningful T cell response. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes deduced from binding affinities and consensus data. Our studies find that, in contrast to current dogma, 'immunodominant' SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing naturally presented SARS-CoV-2 epitopes.

SARS-CoV-2 mutations in Brazil: from genomics to putative clinical conditions

Due to the high rate of transmissibility, Brazil became the new COVID-19 outbreak epicenter and, since then, is being monitored to understand how SARS-CoV-2 mutates and spreads. We combined genomic and structural analysis to evaluate genomes isolated from different regions of Brazil and show that the most prevalent mutations were located in the S, N, ORF3a and ORF6 genes, which are involved in different stages of viral life cycle and its interaction with the host cells. Structural analysis brought to light the positions of these mutations on protein structures, contributing towards studies of selective structure-based drug discovery and vaccine development.

Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs

The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The goal of this study was to use artificial intelligence (AI) to predict blueprints for designing universal vaccines against SARS-CoV-2, that contain a sufficiently broad repertoire of T-cell epitopes capable of providing coverage and protection across the global population. To help achieve these aims, we profiled the entire SARS-CoV-2 proteome across the most frequent 100 HLA-A, HLA-B and HLA-DR alleles in the human population, using host-infected cell surface antigen presentation and immunogenicity predictors from the NEC Immune Profiler suite of tools, and generated comprehensive epitope maps. We then used these epitope maps as input for a Monte Carlo simulation designed to identify statistically significant "epitope hotspot" regions in the virus that are most likely to be immunogenic across a broad spectrum of HLA types. We then removed epitope hotspots that shared significant homology with proteins in the human proteome to reduce the chance of inducing off-target autoimmune responses. We also analyzed the antigen presentation and immunogenic landscape of all the nonsynonymous mutations across 3,400 different sequences of the virus, to identify a trend whereby SARS-COV-2 mutations are predicted to have reduced potential to be presented by host-infected cells, and consequently detected by the host immune system. A sequence conservation analysis then removed epitope hotspots that occurred in less-conserved regions of the viral proteome. Finally, we used a database of the HLA haplotypes of approximately 22,000 individuals to develop a "digital twin" type simulation to model how effective different combinations of hotspots would work in a diverse human population; the approach identified an optimal constellation of epitope hotspots that could provide maximum coverage in the global population. By combining the antigen presentation to the infected-host cell surface and immunogenicity predictions of the NEC Immune Profiler with a robust Monte Carlo and digital twin simulation, we have profiled the entire SARS-CoV-2 proteome and identified a subset of epitope hotspots that could be harnessed in a vaccine formulation to provide a broad coverage across the global population.

Adaptive immune responses to SARS-CoV-2 infection in severe versus mild individuals

The global Coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has affected more than eight million people. There is an urgent need to investigate how the adaptive immunity is established in COVID-19 patients. In this study, we profiled adaptive immune cells of PBMCs from recovered COVID-19 patients with varying disease severity using single-cell RNA and TCR/BCR V(D)J sequencing. The sequencing data revealed SARS-CoV-2-specific shuffling of adaptive immune repertories and COVID-19-induced remodeling of peripheral lymphocytes. Characterization of variations in the peripheral T and B cells from the COVID-19 patients revealed a positive correlation of humoral immune response and T-cell immune memory with disease severity. Sequencing and functional data revealed SARS-CoV-2-specific T-cell immune memory in the convalescent COVID-19 patients. Furthermore, we also identified novel antigens that are responsive in the convalescent patients. Altogether, our study reveals adaptive immune repertories underlying pathogenesis and recovery in severe versus mild COVID-19 patients, providing valuable information for potential vaccine and therapeutic development against SARS-CoV-2 infection.

COVID-19 and SARS-CoV-2. Modeling the present, looking at the future

Since December 2019 the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has produced an outbreak of pulmonary disease which has soon become a global pandemic, known as COronaVIrus Disease-19 (COVID-19). The new coronavirus shares about 82% of its genome with the one which produced the 2003 outbreak (SARS CoV-1). Both coronaviruses also share the same cellular receptor, which is the angiotensin-converting enzyme 2 (ACE2) one. In spite of these similarities, the new coronavirus has expanded more widely, more faster and more lethally than the previous one. Many researchers across the disciplines have used diverse modeling tools to analyze the impact of this pandemic at global and local scales. This includes a wide range of approaches - deterministic, data-driven, stochastic, agent-based, and their combinations - to forecast the progression of the epidemic as well as the effects of non-pharmaceutical interventions to stop or mitigate its impact on the world population. The physical complexities of modern society need to be captured by these models. This includes the many ways of social contacts - (multiplex) social contact networks, (multilayers) transport systems, metapopulations, etc. - that may act as a framework for the virus propagation. But modeling not only plays a fundamental role in analyzing and forecasting epidemiological variables, but it also plays an important role in helping to find cures for the disease and in preventing contagion by means of new vaccines. The necessity for answering swiftly and effectively the questions: could existing drugs work against SARS CoV-2? and can new vaccines be developed in time? demands the use of physical modeling of proteins, protein-inhibitors interactions, virtual screening of drugs against virus targets, predicting immunogenicity of small peptides, modeling vaccinomics and vaccine design, to mention just a few. Here, we review these three main areas of modeling research against SARS CoV-2 and COVID-19: (1) epidemiology; (2) drug repurposing; and (3) vaccine design. Therefore, we compile the most relevant existing literature about modeling strategies against the virus to help modelers to navigate this fast-growing literature. We also keep an eye on future outbreaks, where the modelers can find the most relevant strategies used in an emergency situation as the current one to help in fighting future pandemics.

Predicting the Immunogenicity of T cell epitopes: From HIV to SARS-CoV-2

We describe a physics-based learning model for predicting the immunogenicity of Cytotoxic T Lymphocyte (CTL) epitopes derived from diverse pathogens, given a Human Leukocyte Antigen (HLA) genotype. The model was trained and tested on experimental data on the relative immunodominance of CTL epitopes in Human Immunodeficiency Virus infection. The method is more accurate than publicly available models. Our model predicts that only a fraction of SARS-CoV-2 epitopes that have been predicted to bind to HLA molecules is immunogenic. The immunogenic CTL epitopes across all SARS-CoV-2 proteins are predicted to provide broad population coverage, but the immunogenic epitopes in the SARS-CoV-2 spike protein alone are unlikely to do so. Our model predicts that several immunogenic SARS-CoV-2 CTL epitopes are identical to those contained in low-pathogenicity coronaviruses circulating in the population. Thus, we suggest that some level of CTL immunity against COVID-19 may be present in some individuals prior to SARS-CoV-2 infection.