In silico discovery of antigenic proteins and epitopes of SARS-CoV-2 for the development of a vaccine or a diagnostic approach for COVID-19

Surface protein distribution in Group B Streptococcus isolates from South Africa and identifying vaccine targets through in silico analysis

Group B Streptococcus (GBS) is a major cause of pneumonia, sepsis, and meningitis in infants younger than 3 months of age. Furthermore, GBS infection in pregnant women is associated with stillbirths and pre-term delivery. It also causes disease in immunocompromised adults and the elderly, but the highest incidence of the disease occurs in neonates and young infants. At this time, there are no licensed vaccines against GBS. Complete GBS genome sequencing has helped identify genetically conserved and immunogenic proteins, which could serve as vaccine immunogens. In this study, in silico reverse vaccinology method were used to evaluate the prevalence and conservation of GBS proteins in invasive and colonizing isolates from South African infants and women, respectively. Furthermore, this study aimed to predict potential GBS vaccine targets by evaluating metrics such as antigenicity, physico-chemical properties, subcellular localization, secondary and tertiary structures, and epitope prediction and conservation. A total of 648 invasive and 603 colonizing GBS isolate sequences were screened against a panel of 89 candidate GBS proteins. Ten of the 89 proteins were highly genetically conserved in invasive and colonizing GBS isolates, nine of which were computationally inferred proteins (gbs2106, SAN_1577, SAN_0356, SAN_1808, SAN_1685, SAN_0413, SAN_0990, SAN_1040, SAN_0226) and one was the surface Immunogenic Protein (SIP). Additionally, the nine proteins were predicted to be more antigenic than the SIP protein (antigenicity score of > 0.6498), highlighting their potential as GBS vaccine antigen targets.

Bioinformatics-Driven mRNA-Based Vaccine Design for Controlling Tinea Cruris Induced by Trichophyton rubrum

Tinea cruris, a dermatophyte fungal infection predominantly caused by Trichophyton rubrum and Epidermophyton floccosum, primarily affects the groin, pubic region, and adjacent thigh. Its recurrence is frequent, attributable to repeated fungal infections in susceptible individuals, especially those with onychomycosis or tinea pedis, which act as reservoirs for dermatophytes. Given the persistent nature of tinea cruris, vaccination emerges as a promising strategy for fungal infection management, offering targeted, durable protection against various fungal species. Vaccines stimulate both humoral and cell-mediated immunity and are administered prophylactically to prevent infections while minimizing the risk of antifungal resistance development. Developing fungal vaccines is challenging due to the thick fungal cell wall, similarities between fungal and human cells, antigenic variation, and evolutionary resemblance to animals, complicating non-toxic target identification and T-cell response variability. No prior research has shown an mRNA vaccine for T. rubrum. Hence, this study proposes a novel mRNA-based vaccine for tinea cruris, potentially offering long-term immunity and reducing reliance on antifungal medications. This study explores the complete proteome of T. rubrum, identifying potential protein candidates for vaccine development through reverse vaccinology. Immunogenic epitopes from these candidates were mapped and integrated into multitope vaccines and reverse translated to construct mRNA vaccines. Then, the mRNA was translated and computationally assessed for physicochemical, chemical, and immunological attributes. Notably, 1,3-beta-glucanosyltransferase, CFEM domain-containing protein, cell wall galactomannoprotein, and LysM domain-containing protein emerged as promising vaccine targets. Antigenic, immunogenic, non-toxic, and non-allergenic cytotoxic T lymphocyte, helper T lymphocyte, and B lymphocyte epitopes were selected and linked with appropriate linkers and Toll-like receptor (TLR) agonist adjuvants to formulate vaccine candidates targeting T. rubrum. The protein-based vaccines underwent reverse translation to construct the mRNA vaccines, which, after inoculation, were translated again by host ribosomes to work as potential components for triggering the immune response. After that, molecular docking, normal mode analysis, and molecular dynamic simulation confirmed strong binding affinities and stable complexes between vaccines and TLR receptors. Furthermore, immune simulations of vaccines with and without adjuvant demonstrated activation of immune responses, evidenced by elevated levels of IgG1, IgG2, IgM antibodies, cytokines, and interleukins. There was no significant change in antibody production between vaccines with and without adjuvants, but adjuvants are crucial for activating the innate immune response via TLRs. Although mRNA vaccines hold promise against fungal infections, further research is essential to assess their safety and efficacy. Experimental validation is crucial for evaluating their immunogenicity, effectiveness, and safety.

VOE: automated analysis of variant epitopes of SARS-CoV-2 for the development of diagnostic tests or vaccines for COVID-19

Background

The development of serodiagnostic tests and vaccines for COVID-19 depends on the identification of epitopes from the SARS-CoV-2 genome. An epitope is the specific part of an antigen that is recognized by the immune system and can elicit an immune response. However, when the genetic variants contained in epitopes are used to develop rapid antigen tests (Ag-RDTs) and DNA or RNA vaccines, test sensitivity and vaccine efficacy can be low.

Methods

Here, we developed a "variant on epitope (VOE)" software, a new Python script for identifying variants located on an epitope. Variant analysis and sensitivity calculation for seven recommended epitopes were processed by VOE. Variants in 1,011 Omicron SRA reads from two variant databases (BCFtools and SARS-CoV-2-Freebayes) were processed by VOE.

Results

A variant with HIGH or MODERATE impact was found on all epitopes from both variant databases except the epitopes KLNDLCFTNV, RVQPTES, LKPFERD, and ITLCFTLKRK on the S gene and ORF7a gene. All epitope variants from the BCFtools and SARS-CoV-2 Freebayes variant databases showed about 100% sensitivity except epitopes APGQTGK and DSKVGGNYN on the S gene, which showed respective sensitivities of 28.4866% and 6.8249%, and 87.7349% and 71.1177%.

Conclusions

Therefore, the epitopes KLNDLCFTNV, RVQPTES, LKPFERD, and ITLCFTLKRK may be useful for the development of an epitope-based peptide vaccine and GGDGKMKD on the N gene may be useful for the development of serodiagnostic tests. Moreover, VOE can also be used to analyze other epitopes, and a new variant database for VOE may be further established when a new variant of SARS-CoV-2 emerges.

Immunogenicity and protection efficacy of a COVID-19 DNA vaccine encoding spike protein with D614G mutation and optimization of large-scale DNA vaccine production

Severe acute respiratory syndrome coronavirus 2 had devastating consequences for human health. Despite the introduction of several vaccines, COVID-19 continues to pose a serious health risk due to emerging variants of concern. DNA vaccines gained importance during the pandemic due to their advantages such as induction of both arms of immune response, rapid development, stability, and safety profiles. Here, we report the immunogenicity and protective efficacy of a DNA vaccine encoding spike protein with D614G mutation (named pcoSpikeD614G) and define a large-scale production process. According to the in vitro studies, pcoSpikeD614G expressed abundant spike protein in HEK293T cells. After the administration of pcoSpikeD614G to BALB/c mice through intramuscular (IM) route and intradermal route using an electroporation device (ID + EP), it induced high level of anti-S1 IgG and neutralizing antibodies (P < 0.0001), strong Th1-biased immune response as shown by IgG2a polarization (P < 0.01), increase in IFN-γ levels (P < 0.01), and increment in the ratio of IFN-γ secreting CD4+ (3.78-10.19%) and CD8+ (5.24-12.51%) T cells. Challenging K18-hACE2 transgenic mice showed that pcoSpikeD614G administered through IM and ID + EP routes conferred 90-100% protection and there was no sign of pneumonia. Subsequently, pcoSpikeD614G was evaluated as a promising DNA vaccine candidate and scale-up studies were performed. Accordingly, a large-scale production process was described, including a 36 h fermentation process of E. coli DH5α cells containing pcoSpikeD614G resulting in a wet cell weight of 242 g/L and a three-step chromatography for purification of the pcoSpikeD614G DNA vaccine.

Designing novel peptides for detecting the Omicron variant, specifying SARS-CoV-2, and simultaneously screening coronavirus infections

In this study in silico a candidate diagnostic peptide-based tool was designed in four stages including diagnosis of coronavirus diseases, simultaneously identifying of COVID-19 and SARS from other members of this family, specific identification of SARS-CoV2, and diagnosis of COVID-19 Omicron. Designed candidate peptides consist of four immunodominant peptides from the proteins of the SARS-CoV-2 spike (S) and membrane (M). The tertiary structure of each peptide was predicted. The stimulation ability of the humoral immunity for each peptide was evaluated. Finally, in silico cloning was performed to develop an expression strategy for each peptide. These four peptides have suitable immunogenicity, appropriate construct, and the ability to be expressed in E.coli. These results must be experimentally validated in vitro and in vivo to ensure the immunogenicity of the kit.Communicated by Ramaswamy H. Sarma.

A comprehensive examination of ACE2 receptor and prediction of spike glycoprotein and ACE2 interaction based on in silico analysis of ACE2 receptor

The ACE2 receptor plays a vital role not only in the SARS-CoV-induced epidemic but also in various other diseases, including cardiovascular diseases and ARDS. While studies have explored the interactions between ACE2 and SARS-CoV proteins, comprehensive research utilizing bioinformatic tools on the ACE2 protein has been lacking. The one aim of present study was to extensively analyze the regions of the ACE2 protein. After utilizing all bioinformatics tools especially G104 and L108 regions on ACE2 were come forward. The results of our analysis revealed that possible mutations or deletions in the G104 and L108 regions play a critical role in both the biological functioning and the determination of the chemical-physical properties of ACE2. Additionally, these regions were found to be more susceptible to mutations or deletions compared to other regions of the ACE2 protein. Notably, the randomly selected peptide, LQQNGSSVLS (100-109), which includes G104 and L108, exhibited a crucial role in binding the RBD of the spike protein, as supported by docking scores. Furthermore, both MDs and iMODs results provided evidence that G104 and L108 influence the dynamics of ACE2-spike complexes. This study is expected to offer a new perspective on the ACE2-SARS-CoV interaction and other research areas where ACE2 plays a significant role, such as biotechnology (protein engineering, enzyme optimization), medicine (RAS, pulmonary and cardiac diseases), and basic research (structural motifs, stabilizing protein folds, or facilitating important inter molecular contacts, protein's proper structure and function).Communicated by Ramaswamy H. Sarma.

In silico discovery of diagnostic/vaccine candidate antigenic epitopes and a multi-epitope peptide vaccine (NaeVac) design for the brain-eating amoeba Naegleria fowleri causing human meningitis

Naegleria fowleri, the brain-eating amoeba, is a free-living amoeboflagellate with three different life cycles (trophozoite, flagellated, and cyst) that lives in a variety of habitats around the world including warm freshwater and soil. It causes a disease called naegleriasis leading meningitis and primary amoebic meningoencephalitis (PAM) in humans. N. fowleri is transmitted through contaminated water sources such as insufficiently chlorinated swimming pool water or contaminated tap water, and swimmers are at risk. N. fowleri is found all over the world, and most infections were reported in both developed and developing countries with high mortality rates and serious clinical findings. Until now, there is no FDA approved vaccine and early diagnosis is urgent against this pathogen. In this study, by analyzing the N. fowleri vaccine candidate proteins (Mp2CL5, Nfa1, Nf314, proNP-A and proNP-B), it was aimed to discover diagnostic/vaccine candidate epitopes and to design a multi-epitope peptide vaccine against this pathogen. After the in silico evaluation, three prominent diagnostic/vaccine candidate epitopes (EAKDSK, LLPHIRILVY, and FYAKLLPHIRILVYS) with the highest antigenicities were discovered and a potentially highly immunogenic/antigenic multi-epitope peptide vaccine (NaeVac) was designed against the brain-eating amoeba N. fowleri causing human meningitis.

Molecular characterization of Anaplasma ovis Msp4 protein in strains isolated from ticks in Turkey: A multi-epitope synthetic vaccine antigen design against Anaplasma ovis using immunoinformatic tools

Tick-borne pathogens increasingly threaten animal and human health as well as cause great economic loss in the livestock industry. Among these pathogens, Anaplasma ovis causing a decrease in meat and milk yield is frequently detected in sheep in many countries including Turkey. This study aimed to reveal potential vaccine candidate epitopes in Msp4 protein using sequence data from Anaplasma ovis isolates and then to design a multi-epitope protein to be used in vaccine formulations against Anaplasma ovis. For this purpose, Msp4 gene was sequenced from Anaplasma ovis isolates (n:6) detected in ticks collected from sheep in Turkey and the sequence data was compared with previous sequences from different countries in order to detect the variations of Msp4 gene/protein. Potential vaccine candidate and diagnostic epitopes were predicted using various immunoinformatics tools. Among the discovered vaccine candidate epitopes, antigenic and conserved were selected, and then a multi-epitope protein was designed. The designed vaccine protein was tested for the assessment of TLR-2, IgG, and IFN-g responses by molecular docking and immune simulation analyses. Among the discovered epitopes, EVASEGSGVM and YQFTPEISLV epitopes with properties of high antigenicity, non-allergenicity, and non-toxicity were proposed to be used for Anaplasma ovis in further serodiagnostic and vaccine studies.

Single-residue linear and conformational B cell epitopes prediction using random and ESM-2 based projections

B cell epitope prediction methods are separated into linear sequence-based predictors and conformational epitope predictions that typically use the measured or predicted protein structure. Most linear predictions rely on the translation of the sequence to biologically based representations and the applications of machine learning on these representations. We here present CALIBER 'Conformational And LInear B cell Epitopes pRediction', and show that a bidirectional long short-term memory with random projection produces a more accurate prediction (test set AUC=0.789) than all current linear methods. The same predictor when combined with an Evolutionary Scale Modeling-2 projection also improves on the state of the art in conformational epitopes (AUC = 0.776). The inclusion of the graph of the 3D distances between residues did not increase the prediction accuracy. However, the long-range sequence information was essential for high accuracy. While the same model structure was applicable for linear and conformational epitopes, separate training was required for each. Combining the two slightly increased the linear accuracy (AUC 0.775 versus 0.768) and reduced the conformational accuracy (AUC = 0.769).

Reverse vaccinology and immunoinformatics approach to design a chimeric epitope vaccine against Orientia tsutsugamushi

Scrub typhus is a vector-borne infectious disease caused by Orientia tsutsugamushi and it is reportedly associated with up to 20 % of hospitalized cases of febrile illnesses. The major challenge of vaccine development is the lack of identified antigens that can induce both heterotypic and homotypic immunity including the production of antibodies, cytotoxic T lymphocyte, and helper T lymphocytes. We employed a comprehensive immunoinformatic prediction algorithm to identify immunogenic epitopes of the 56-kDa type-specific cell membrane surface antigen and surface cell antigen A of O. tsutsugamushi to select potential candidates for developing vaccines and diagnostic assays. We identified 35 linear and 29 continuous immunogenic B-cell epitopes and 51 and 27 strong-binding T-cell epitopes of major histocompatibility complex class I and class II molecules, respectively, in the conserved and variable regions of the 56-kDa type-specific surface antigen. The predicted B- and T-cell epitopes were used to develop immunogenic multi-epitope candidate vaccines and showed to elicit a broad-range of immune protection. A stable interactions between the multi-epitope vaccines and the host fibronectin protein were observed using docking and simulation methods. Molecular dynamics simulation studies demonstrated that the multi-epitope vaccine constructs and fibronectin docked models were stable during simulation time. Furthermore, the multi-epitope vaccine exhibited properties such as antigenicity, non-allergenicity and ability to induce interferon gamma production and had strong associations with their respective human leukocyte antigen alleles of world-wide population coverage. A correlation of immune simulations and the in-silico predicted immunogenic potential of multi-epitope vaccines implicate for further investigations to accelerate designing of epitope-based vaccine candidates and chimeric antigens for development of serological diagnostic assays for scrub typhus.

Designing of a new multi-epitope vaccine against Leishmania major using Leish-F1 epitopes: An In-silico study

Cutaneous leishmaniasis (CL) is the most common form of the disease which can cause malignant lesions on the skin. Vaccination for the prevention and treatment of leishmaniasis can be the most effective way to combat this disease. In this study, we designed a novel multi-epitope vaccine against Leishmania major (L. major) using immunoinformatics tools to assess its efficacy in silico. Sequences of Leish-F1 protein (TSA, Leif, and LMSTI1) of L. major were taken from GenBank. The helper T (Th) and cytotoxic T (Tc) epitopes of the protein were predicted. The final multi-epitope consisted of 18 CTL epitopes joined by AAY linker. There were also nine HTL epitopes in the structure of the vaccine construct, joined by GPGPG linker. The profilin adjuvant (the toll-like receptor 11 agonist) was also added into the construct by AAY Linker. There were 613 residues in the structure of the vaccine construct. The multi-epitope vaccine candidate was stable and non-allergic. The data obtained from the binding of final multi-epitope vaccine-TLR11 residues (band lengths and weighted scores) unveiled the ligand and the receptor high score of binding affinity. Moreover, in silico assessment of the vaccine construct cloning achieved its suitable expression in E. coli host. Based on these results, the current multi-epitope vaccine prevents L. major infection in silico, while further confirmatory assessments are required.

SARS-CoV-2 variants infectivity prediction and therapeutic peptide design using computational approaches

The outbreak of severe acute respiratory coronavirus 2 (SARS-CoV-2) has created a public health emergency globally. SARS-CoV-2 enters the human cell through the binding of the spike protein to human angiotensin converting enzyme 2 (ACE2) receptor. Significant changes have been reported in the mutational landscape of SARS-CoV-2 in the receptor binding domain (RBD) of S protein, subsequent to evolution of the pandemic. The present study examines the correlation between the binding affinity of mutated S-proteins and the rate of viral infectivity. For this, the binding affinity of SARS-CoV and variants of SARS-CoV-2 towards ACE2 was computationally determined. Subsequently, the RBD mutations were classified on the basis of the number of strains identified with respect to each mutation and the resulting variation in the binding affinity was computationally examined. The molecular docking studies indicated a significant correlation between the Z-Rank score of mutated S proteins and the rate of infectivity, suitable for predicting SARS-CoV-2 infectivity. Accordingly, a 30-mer peptide was designed and the inhibitory properties were computationally analyzed. Single amino acid-wise mutation was performed subsequently to identify the peptide with the highest binding affinity. Molecular dynamics and free energy calculations were then performed to examine the stability of the peptide-protein complexes. Additionally, selected peptides were synthesized and screened using a colorimetric assay. Together, this study developed a model to predict the rate of infectivity of SARS-CoV-2 variants and propose a potential peptide that can be used as an inhibitor for the viral entry to human.Communicated by Ramaswamy H. Sarma.

In silico discovery of epitopes of gag and env proteins for the development of a multi-epitope vaccine candidate against Maedi Visna Virus using reverse vaccinology approach

Maedi Visna Virus (MVV) causes a chronic viral disease in sheep. Since there is no specific therapeutic drug that targets MVV, development of a vaccine against the MVV is inevitable. This study aimed to analyze the gag and env proteins as vaccine candidate proteins and to identify epitopes in these proteins. In addition, it was aimed to construct a multi-epitope vaccine candidate. According to the obtained results, the gag protein was detected to be more conserved and had a higher antigenicity value. Also, the number of alpha helix in the secondary structure was higher and transmembrane helices were not detected. Although many B cell and MHC-I/II epitopes were predicted, only 19 of them were detected to have the properties of antigenic, non-allergenic, non-toxic, soluble, and non-hemolytic. Of these epitopes, five were remarkable due to having the highest antigenicity value. However, the final multi-epitope vaccine was constructed with 19 epitopes. A strong affinity was shown between the final multi-epitope vaccine and TLR-2/4. In conclusion, the gag protein was a better antigen. However, both proteins had epitopes with high antigenicity value. Also, the final multi-epitope vaccine construct had a potential to be used as a peptide vaccine due to its immuno-informatics results.

Evolutionary aspects of mutation in functional motif and post-translational modifications in SARS-CoV-2 3CLpro (Mpro): an in-silico study

SARS CoV-2 is the virus that caused the COVID-19 pandemic. The main protease is one of the most prominent pharmacological targets for developing anti-COVID-19 therapeutic drugs (Mpro); SARS-CoV-2 replication is dependent on this component. SARS CoV-2's Mpro/cysteine protease is quite identical to SARS CoV-1's Mpro/cysteine protease. However, there is limited information on its structural and conformational properties. The present study aims to perform a complete in silico evaluation of Mpro protein's physicochemical properties. The motif prediction, post-translational modifications, effect of point mutation, and phylogenetic links were studied with other homologs to understand the molecular and evolutionary mechanisms of these proteins. The Mpro protein sequence was obtained in FASTA format from the RCSB Protein Data Bank. The structure of this protein was further characterized and analyzed using standard bioinformatics methods. According to Mpro's in-silico characterization, the protein is a basic, non-polar, and thermally stable globular protein. The outcomes of the phylogenetic and synteny study showed that the protein's functional domain amino acid sequence is substantially conserved. Furthermore, it has undergone many changes at the motif level over time from porcine epidemic diarrhoea virus to SARS-CoV 2, possibly to achieve various functions. Several post-translational modifications (PTMs) were also observed, and the possibilities of changes in Mpro protein exhibit additional orders of peptidase function regulation. During heatmap development, the effect of a point mutation on the Mpro protein was seen. This protein's structural characterization will aid in a better understanding of its function and mechanism of action.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42485-023-00105-9.

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.

A Promising Tool in Serological Diagnosis: Current Research Progress of Antigenic Epitopes in Infectious Diseases

Infectious diseases, caused by various pathogens in the clinic, threaten the safety of human life, are harmful to physical and mental health, and also increase economic burdens on society. Infections are a complex mechanism of interaction between pathogenic microorganisms and their host. Identification of the causative agent of the infection is vital for the diagnosis and treatment of diseases. Etiological laboratory diagnostic tests are therefore essential to identify pathogens. However, due to its rapidity and automation, the serological diagnostic test is among the methods of great significance for the diagnosis of infections with the basis of detecting antigens or antibodies in body fluids clinically. Epitopes, as a special chemical group that determines the specificity of antigens and the basic unit of inducing immune responses, play an important role in the study of immune responses. Identifying the epitopes of a pathogen may contribute to the development of a vaccine to prevent disease, the diagnosis of the corresponding disease, and the determination of different stages of the disease. Moreover, both the preparation of neutralizing antibodies based on useful epitopes and the assembly of several associated epitopes can be used in the treatment of disease. Epitopes can be divided into B cell epitopes and T cell epitopes; B cell epitopes stimulate the body to produce antibodies and are therefore commonly used as targets for the design of serological diagnostic experiments. Meanwhile, epitopes can fall into two possible categories: linear and conformational. This article reviews the role of B cell epitopes in the clinical diagnosis of infectious diseases.

Utility of in silico-identified-peptides in spike-S1 domain and nucleocapsid of SARS-CoV-2 for antibody detection in COVID-19 patients and antibody production

SARS-CoV-2 contains four structural proteins, two of which, the spike and nucleocapsid, are commonly used for the standardization of novel methods for antibody detection; however, some limitations in their use have been observed due to the homology of this virus with other phylogenetically-related viruses. We performed in silico analysis to search for novel immunogenic and antigenic peptides. A total of twenty-five peptides were preliminarily selected, located in the 3D structure of both proteins. Finally, eight peptides were selected: one located in the N protein and seven in the S1 domain of the spike protein. Additionally, the localization of selected peptides in 2D structures and possible changes in the sequences of these peptides in SARS-CoV-2 variants of concern were analyzed. All peptides were synthetized in MAP8 format, and recombinant S (trimer and RBD) and N proteins were used as antigens to search for antibodies in serum samples derived from COVID-19 patients, and for antibody response in New Zealand rabbits. Results showed high recognition of the serum derived from COVID-19 patients to all selected peptides; however, only the RBD3 peptide induced antibody production. In conclusion, this work provides evidence for a new strategy in peptide selection and its use for antibody detection or antibody production in animals.

Conjugation with 8-arm PEG and CRM197 enhances the immunogenicity of SARS-CoV-2 ORF8 protein

Safe and effective vaccines are urgently needed to combat the COVID-19 pandemic. However, the SARS-CoV-2 variants raise concerns about the effectiveness of vaccines. As a SARS-CoV-2 antigen target, ORF8 strongly inhibits the IFN-β and NF-κB-responsive promoter, and can be potentially used for the development of SARS-CoV-2 vaccine. However, it is necessary to improve the immunogenicity of ORF8 by adjuvants or delivery systems. CRM₁₉₇ was a carrier protein with the ability to activate T helper cells for antigens. Eight-arm PEG could conjugate multiple antigen molecules in one entity with inherent adjuvant effect. In the present study, ORF8 was conjugated with CRM₁₉₇ and 8-arm PEG, respectively. The cellular and humoral immune responses to the conjugates (ORF8-CRM and ORF8-PEG) were evaluated in the BALB/c mice. As compared with ORF8-CRM and ORF8 administrated with aluminum adjuvant (ORF8/AL), ORF8-PEG induced a higher ORF8-specific IgG titer (2.6 × 10⁴), higher levels of cytokines (IFN-γ, TNF-α, IFN-β, and IL-5), stronger splenocyte proliferation. Thus, conjugation with 8-arm PEG was an effective method to improve the immune response to ORF8. Moreover, ORF8-PEG did not lead to apparent toxicity to the cardiac, liver and renal functions. ORF8-PEG was expected to act as an effective vaccine to provide the immune protection against SARS-CoV-2.

Multifaceted Assessment of Wastewater-Based Epidemiology for SARS-CoV-2 in Selected Urban Communities in Davao City, Philippines: A Pilot Study

Over 60 countries have integrated wastewater-based epidemiology (WBE) in their COVID-19 surveillance programs, focusing on wastewater treatment plants (WWTP). In this paper, we piloted the assessment of SARS-CoV-2 WBE as a complementary public health surveillance method in susceptible communities in a highly urbanized city without WWTP in the Philippines by exploring the extraction and detection methods, evaluating the contribution of physico-chemical-anthropogenic factors, and attempting whole-genome sequencing (WGS). Weekly wastewater samples were collected from sewer pipes or creeks in six communities with moderate-to-high risk of COVID-19 transmission, as categorized by the City Government of Davao from November to December 2020. Physico-chemical properties of the wastewater and anthropogenic conditions of the sites were noted. Samples were concentrated using a PEG-NaCl precipitation method and analyzed by RT-PCR to detect the SARS-CoV-2 N, RdRP, and E genes. A subset of nine samples were subjected to WGS using the Minion sequencing platform. SARS-CoV-2 RNA was detected in twenty-two samples (91.7%) regardless of the presence of new cases. Cycle threshold values correlated with RNA concentration and attack rate. The lack of a sewershed map in the sampled areas highlights the need to integrate this in the WBE planning. A combined analysis of wastewater physico-chemical parameters such as flow rate, surface water temperature, salinity, dissolved oxygen, and total dissolved solids provided insights on the ideal sampling location, time, and method for WBE, and their impact on RNA recovery. The contribution of fecal matter in the wastewater may also be assessed through the coliform count and in the context of anthropogenic conditions in the area. Finally, our attempt on WGS detected single-nucleotide polymorphisms (SNPs) in wastewater which included clinically reported and newly identified mutations in the Philippines. This exploratory report provides a contextualized framework for applying WBE surveillance in low-sanitation areas.

Novel In Silico mRNA vaccine design exploiting proteins of M. tuberculosis that modulates host immune responses by inducing epigenetic modifications

Tuberculosis is an airborne infectious disease caused by Mycobacterium tuberculosis. BCG is the only approved vaccine. However, it has limited global efficacy. Pathogens could affect the transcription of host genes, especially the ones related to the immune system, by inducing epigenetic modifications. Many proteins of M. tuberculosis were found to affect the host's epigenome. Nine proteins were exploited in this study to predict epitopes to develop an mRNA vaccine against tuberculosis. Many immunoinformatics tools were employed to construct this vaccine to elicit cellular and humoral immunity. We performed molecular docking between selected epitopes and their corresponding MHC alleles. Thirty epitopes, an adjuvant TLR4 agonist RpfE, constructs for subcellular trafficking, secretion booster, and specific linkers were combined to develop the vaccine. This proposed construct was tested to cover 99.38% of the population. Moreover, it was tested to be effective and safe. An in silico immune simulation of the vaccine was also performed to validate our hypothesis. It also underwent codon optimization to ensure mRNA's efficient translation once it reaches the cytosol of a human host. Furthermore, secondary and tertiary structures of the vaccine peptide were predicted and docked against TLR-4 and TLR-3.Molecular dynamics simulation was performed to validate the stability of the binding complex. It was found that this proposed construction can be a promising vaccine against tuberculosis. Hence, our proposed construct is ready for wet-lab experiments to approve its efficacy.

Optimizing peptide inhibitors of SARS-Cov-2 nsp10/nsp16 methyltransferase predicted through molecular simulation and machine learning

Coronaviruses, including the recent pandemic strain SARS-Cov-2, use a multifunctional 2'-O-methyltransferase (2'-O-MTase) to restrict the host defense mechanism and to methylate RNA. The nonstructural protein 16 2'-O-MTase (nsp16) becomes active when nonstructural protein 10 (nsp10) and nsp16 interact. Novel peptide drugs have shown promise in the treatment of numerous diseases and new research has established that nsp10 derived peptides can disrupt viral methyltransferase activity via interaction of nsp16. This study had the goal of optimizing new analogous nsp10 peptides that have the ability to bind nsp16 with equal to or higher affinity than those naturally occurring. The following research demonstrates that in silico molecular simulations can shed light on peptide structures and predict the potential of new peptides to interrupt methyltransferase activity via the nsp10/nsp16 interface. The simulations suggest that misalignments at residues F68, H80, I81, D94, and Y96 or rotation at H80 abrogate MTase function. We develop a new set of peptides based on conserved regions of the nsp10 protein in the Coronaviridae species and test these to known MTase variant values. This results in the prediction that the H80R variant is a solid new candidate for potential new testing. We envision that this new lead is the beginning of a reputable foundation of a new computational method that combats coronaviruses and that is beneficial for new peptide drug development.

Development of a new serotyping ELISA for Toxoplasma gondii type II, type III and Africa 1 lineages using in silico peptide discovery methods, well categorized feline and human outbreak serum samples

BACKGROUND

Discovery of new Toxoplasma gondii serotyping epitopes is important due to reports showing the influence of genotype on the severity of toxoplasmosis. In Turkey, genotypes belonging to type II, type III and Africa 1 lineages were mainly detected. The present study focused on to find out epitopes with high discriminative capacity to serotype these genotypes using well characterized strains isolated from Turkey.

METHODS

To meet this objective, GRA6 and GRA7 genes were sequenced from strains belonging to the type II, III and Africa 1 lineages, and B cell epitopes inside these sequences were predicted by Bcepred and additional docking analysis was performed with B cell receptor. Based on these analyses, 22 peptides harboring lineage specific epitopes were synthesized. Then, the serotyping potency of these peptides was tested using peptide ELISA and well categorized serum samples collected from stray cats infected with genotypes of the different lineages type II (n:9), III (n:1) and Africa 1 (n:1). As a result of peptide-ELISA, a serotyping schema was constructed with peptides that show high discriminative capacity and this assay was validated by sera collected from humans after an outbreak (n:30) and mother/newborn pair sera (n:3). Later, the validated serotyping schema was used to serotype a larger group of human (n:38) and cat (n:24) sera.

RESULTS

Among 22 peptides, GRA6II/c, GRA7III/d, and GRA6 Africa 1/b epitopes have shown discriminative capacity. During the validation of peptide-ELISA, the serotype of toxoplasmosis outbreak and mother/newborn cases were detected to be serotype II. Moreover, the analyses in a larger group showed that serotype II was prevalent in humans and stray cats.

CONCLUSIONS

Overall, the results showed that the serotyping schema could be successfully used to serotype T. gondii infections caused by type II, III and Africa 1 genotype.

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.

Mining of linear B cell epitopes of SARS-CoV-2 ORF8 protein from COVID-19 patients

Given the on-going SARS-CoV-2 pandemic, identification of immunogenic targets against the viral protein will provide crucial advances towards the development of sensitive diagnostic tools and vaccination strategies. Our previous study has found that ORF8 protein of SARS-CoV-2 is highly immunogenic and shows high sensitivity in identifying COVID-19 disease. In this study, by employing overlapping linear peptides, we characterized the IgG immunodominant regions on SARS-CoV-2 ORF8 protein that are seropositive in the sera from SARS-CoV-2-infected patients. The major immunogenic epitopes are localized at (1) N-termini alpha helix, (2) the resides spanning beta 2 and 3 sheets, and (3) the loop between beta 4 and 5 sheets. Additionally, hamster model infected by SARS-CoV-2 further validates the seropositivity of the linear epitopes in vivo, demonstrating a potential application of the linear peptide-based immunization strategy. Taken together, identification and validation of these B-cell linear epitopes will provide insights into the design of serological diagnostics and peptide-based vaccination approach against this pandemic virus of high priority.

Construction of a multiepitope vaccine candidate against Fasciola hepatica: an in silico design using various immunogenic excretory/secretory antigens

BACKGROUND

Fasciola hepatica is an important pathogen that causes liver fluke disease in definitive hosts such as livestock animals and humans. Various excretory/secretory products have been used in serological diagnosis and vaccination studies targeting fasciolosis. There are no commercial vaccines against fasciolosis yet. Bioinformatic analysis based on computational methods have lower cost and provide faster output compared to conventional vaccine antigen discovery techniques. The aim of this study was to predict B- and T-cell specific epitopes of four excretory/secretory antigens (Kunitz-type serine protease inhibitor, cathepsin L1, helminth defense molecule, and glutathione S-transferase) of Fasciola hepatica and to construct a multiepitope vaccine candidate against fasciolosis.

METHODS AND RESULTS

Initially, nonallergic and the highest antigenic B- and T- cell epitopes were selected and then, physico-chemical parameters, secondary and tertiary structures of designed multiepitope vaccine candidate were predicted. Tertiary structure was refined and validated using online bioinformatic tools. Linear and discontinuous B-cell epitopes and disulfide bonds were determined. Finally, molecular docking analysis for MHC-I and MHC-II receptors was performed.

CONCLUSION

This multi-epitope vaccine candidate antigen, with high immunological properties, can be considered as a promising vaccine candidate for animal experiments and wet lab studies.

In-silico design of envelope based multi-epitope vaccine candidate against Kyasanur forest disease virus

Kyasanur forest disease virus (KFDV) causing tick-borne hemorrhagic fever which was earlier endemic to western Ghats, southern India, it is now encroaching into new geographic regions, but there is no approved medicine or effective vaccine against this deadly disease. In this study, we did in-silico design of multi-epitope subunit vaccine for KFDV. B-cell and T-cell epitopes were predicted from conserved regions of KFDV envelope protein and two vaccine candidates (VC1 and VC2) were constructed, those were found to be non-allergic and possess good antigenic properties, also gives cross-protection against Alkhurma hemorrhagic fever virus. The 3D structures of vaccine candidates were built and validated. Docking analysis of vaccine candidates with toll-like receptor-2 (TLR-2) by Cluspro and PatchDock revealed strong affinity between VC1 and TLR2. Ligplot tool was identified the intermolecular hydrogen bonds between vaccine candidates and TLR-2, iMOD server confirmed the stability of the docking complexes. JCAT sever ensured cloning efficiency of both vaccine constructs and in-silico cloning into pET30a (+) vector by SnapGene showed successful translation of epitope region. IMMSIM server was identified increased immunological responses. Finally, multi-epitope vaccine candidates were designed and validated their efficiency, it may pave the way for up-coming vaccine and diagnostic kit development.

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.

GRA8 DNA vaccine formulations protect against chronic toxoplasmosis

Toxoplasma gondii has a very wide host range and infects all warm-blooded animals including humans. The disease causes great economic losses both in animals and humans. Vaccination is the most effective approach to fight against toxoplasmosis however an effective vaccine has not been developed yet. In the present study, GRA8 protein of T. gondii that showed high immunogenicity in our previous microarray screening study was used to develop a DNA vaccine using pcDNA 3.3 vector for the first time. In order to increase the potency of the DNA vaccine, 10 times lower amount of GRA8 DNA vaccine was combined with molecular adjuvant CpG and formulated into a commercial liposome (pcDNA3.3-GRA8+CpG+Escort). Mice were vaccinated intramuscularly two times at three-week intervals and challenged orally with the T. gondii PRU strain tissue cysts. The humoral immune response was determined by Western Blot and ELISA. The cellular immune response was analyzed by flow cytometry, cytokine ELISA and MTT assay. Among the vaccine groups, pcDNA3.3-GRA8 and pcDNA3.3-GRA8+CpG+Escort induced strong IgG response compared to controls (P < 0.001). The IgG1 and IgG2a responses showed a balanced Th1-Th2 polarization. The ratio of CD4⁺ and CD8⁺ T lymphocytes secreting IFN-γ increased, and significantly higher extracellular IFN-γ secretion was achieved compared to the controls (P < 0.01). The amount of tissue cysts in the group of mice vaccinated with pcDNA3.3-GRA8 decreased significantly compared to control groups (P < 0.0001). In the group vaccinated with pcDNA3.3-GRA8+CpG+Escort, the amount of tissue cysts also decreased significantly compared to PBS (P = 0.0086) and Empty plasmid+CpG+Escort (P = 0.0007) groups. This study showed for the first time that pcDNA 3.3. vector encoding GRA8 with or without CpG and Liposome can induce strong cellular and humoral immune responses and confer strong protection against mouse model of chronic toxoplasmosis.

Bioinformatics Analysis Unveils Certain Mutations Implicated in Spike Structure Damage and Ligand-Binding Site of Severe Acute Respiratory Syndrome Coronavirus 2

There are certain mutations related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In addition to these known mutations, other new mutations have been found across regions in this study. Based on the results, in which 4,326 SARS-CoV-2 whole sequences were used, some mutations are found to be peculiar with certain regions, while some other mutations are found in all regions. In Asia, mutations (3 different mutations in QLA46612 isolated from South Korea) were found in the same sequence. Although huge number of mutations are detected (more than 70 in Asia) by regions, according to bioinformatics tools, some of them which are G75V (isolated from North America), T95I (isolated from South Korea), G143V (isolated from North America), M177I (isolated from Asia), L293M (isolated from Asia), P295H (isolated from Asia), T393P (isolated from Europe), P507S (isolated from Asia), and D614G (isolated from all regions) (These color used only make correct) predicted a damage to spike' protein structure. Furthermore, this study also aimed to reveal how binding sites of ligands change if the spike protein structure is damaged, and whether more than one mutation affects ligand binding. Mutations that were predicted to damage the structure did not affect the ligand-binding sites, whereas ligands' binding sites were affected in those with multiple mutations. It is thought that this study will give a different perspective to both the vaccine SARS-CoV studies and the change in the structure of the spike protein belonging to this virus against mutations.

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

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

Spike protein mutational landscape in India during the complete lockdown phase: Could Muller's ratchet be a future game-changer for COVID-19?

The dire need of effective preventive measures and treatment approaches against SARS-CoV-2 virus, causing COVID-19 pandemic, calls for an in-depth understanding of its evolutionary dynamics with attention to specific geographic locations, since lockdown and social distancing to prevent the virus spread could lead to distinct localized dynamics of virus evolution within and between countries owing to different environmental and host-specific selection pressures. To decipher any correlation between SARS-CoV-2 evolution and its epidemiology in India, we studied the mutational diversity of spike glycoprotein, the key player for the attachment, fusion and entry of virus to the host cell. For this, we analyzed the sequences of 630 Indian isolates as available in GISAID database till June 07, 2020 (during the time-period before the start of Unlock 1.0 in India on and from June 08, 2020), and detected the spike protein variants to emerge from two major ancestors – Wuhan-Hu-1/2019 and its D614G variant. Average stability of the docked spike protein – host receptor (S-R) complexes for these variants correlated strongly (R² = 0.96) with the fatality rates across Indian states. However, while more than half of the variants were found unique to India, 67% of all variants showed lower stability of S-R complex than the respective ancestral variants, indicating a possible fitness loss in recently emerged variants, despite a continuous increase in mutation rate. These results conform to the sharply declining fatality rate countrywide (>7-fold during April 11 – June 28, 2020). Altogether, while we propose the potential of S-R complex stability to track disease severity, we urge an immediate need to explore if SARS-CoV-2 is approaching mutational meltdown in India.

Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Background

To contain the pandemics caused by SARS-CoV-2, early detection approaches with high accuracy and accessibility are critical. Generating an antigen-capture based detection system would be an ideal strategy complementing the current methods based on nucleic acids and antibody detection. The spike protein is found on the outside of virus particles and appropriate for antigen detection.

Methods

In this study, we utilized bioinformatics approaches to explore the immunodominant fragments on spike protein of SARS-CoV-2.

Results

The S1 subunit of spike protein was identified with higher sequence specificity. Three immunodominant fragments, Spike_56-94, Spike_199-264, and Spike_577-612, located at the S1 subunit were finally selected via bioinformatics analysis. The glycosylation sites and high-frequency mutation sites on spike protein were circumvented in the antigen design. All the identified fragments present qualified antigenicity, hydrophilicity, and surface accessibility. A recombinant antigen with a length of 194 amino acids (aa) consisting of the selected immunodominant fragments as well as a universal Th epitope was finally constructed.

Conclusion

The recombinant peptide encoded by the construct contains multiple immunodominant epitopes, which is expected to stimulate a strong immune response in mice and generate qualified antibodies for SARS-CoV-2 detection.