Epitope-based peptide vaccine design and target site depiction against Middle East Respiratory Syndrome Coronavirus: an immune-informatics study

Designing a Candidate Multi-Epitope Vaccine against Transmissible Gastroenteritis Virus Based on Immunoinformatic and Molecular Dynamics

Transmissible gastroenteritis virus (TGEV) is an etiological agent of enteric disease that results in high mortality rates in piglets. The economic impact of the virus is considerable, causing significant losses to the pig industry. The development of an efficacious subunit vaccine to provide promising protection against TGEV is of the utmost importance. The viral antigen, spike glycoprotein (S), is widely regarded as one of the most effective antigenic components for vaccine research. In this study, we employed immunoinformatics and molecular dynamics approaches to develop an 'ideal' multi-epitope vaccine. Firstly, the dominant, non-toxic, highly antigenic T (Th, CTL) and B cell epitopes predicted from the TGEV S protein were artificially engineered in tandem to design candidate subunit vaccines. Molecular docking and dynamic simulation results demonstrate that it exhibits robust interactions with toll-like receptor 4 (TLR4). Of particular significance was the finding that the vaccine was capable of triggering an immune response in mammals, as evidenced by the immune simulation results. The humoral aspect is typified by elevated levels of IgG and IgM, whereas the cellular immune aspect is capable of eliciting the robust production of interleukins and cytokines (IFN-γ and IL-2). Furthermore, the adoption of E. coli expression systems for the preparation of vaccines will also result in cost savings. This study offers logical guidelines for the development of a secure and efficacious subunit vaccine against TGEV, in addition to providing a novel theoretical foundation and strategy to prevent associated CoV infections.

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.

Designing a smallpox B-cell and T-cell multi-epitope subunit vaccine using a comprehensive immunoinformatics approach

Smallpox is a highly contagious human disease caused by the variola virus. Although the disease was eliminated in 1979 due to its highly contagious nature and historical pathogenicity, with a mortality rate of up to 30%, this virus is an important candidate for biological weapons. Currently, vaccines are the critical measures to prevent this virus infection and spread. In this study, we designed a peptide vaccine using immunoinformatics tools, which have the potential to activate human immunity against variola virus infection efficiently. The design of peptides derives from vaccine-candidate proteins showing protective potential in vaccinia WR strains. Potential non-toxic and nonallergenic T-cell and B-cell binding and cytokine-inducing epitopes were then screened through a priority prediction using special linkers to connect B-cell epitopes and T-cell epitopes, and an appropriate adjuvant was added to the vaccine construction to enhance the immunogenicity of the peptide vaccine. The 3D structure display, docking, and free energy calculation analysis indicate that the binding affinity between the vaccine peptide and Toll-like receptor 3 is high, and the vaccine receptor complex is highly stable. Notably, the vaccine we designed is obtained from the protective protein of the vaccinia and combined with preventive measures to avoid side effects. This vaccine is highly likely to produce an effective and safe immune response against the variola virus infection in the body.

IMPORTANCE

In this work, we designed a vaccine with a cluster of multiple T-cell/B-cell epitopes, which should be effective in inducing systematic immune responses against variola virus infection. Besides, this work also provides a reference in vaccine design for preventing monkeypox virus infection, which is currently prevalent.

In-silico formulation of a next-generation polyvalent vaccine against multiple strains of monkeypox virus and other related poxviruses

Mpox (formerly known as monkeypox) virus and some related poxviruses including smallpox virus pose a significant threat to public health, and effective prevention and treatment strategies are needed. This study utilized a reverse vaccinology approach to retrieve conserved epitopes for monkeypox virus and construct a vaccine that could provide cross-protection against related viruses with similar antigenic properties. The selected virulent proteins of monkeypox virus, MPXVgp165, and Virion core protein P4a, were subjected to epitope mapping for vaccine construction. Two vaccines were constructed using selected T cell epitopes and B cell epitopes with PADRE and human beta-defensins adjuvants conjugated in the vaccine sequence. Both constructs were found to be highly antigenic, non-allergenic, nontoxic, and soluble, suggesting their potential to generate an adequate immune response and be safe for humans. Vaccine construct 1 was selected for molecular dynamic simulation studies. The simulation studies revealed that the TLR8-vaccine complex was more stable than the TLR3-vaccine complex. The lower RMSD and RMSF values of the TLR8 bound vaccine compared to the TLR3 bound vaccine suggested better stability and consistency of hydrogen bonds. The Rg values of the vaccine chain bound to TLR8 indicated overall stability, whereas the vaccine chain bound to TLR3 showed deviations throughout the simulation. These results suggest that the constructed vaccine could be a potential preventive measure against monkeypox and related viruses however, further experimental validation is required to confirm these findings.

Designing a multi-epitope vaccine against Shigella dysenteriae using immuno-informatics approach

Shigella dysenteriae has been recognized as the second most prevalent pathogen associated with diarrhea that contains blood, contributing to 12.9% of reported cases, and it is additionally responsible for approximately 200,000 deaths each year. Currently, there is no S. dysenteriae licensed vaccine. Multidrug resistance in all Shigella spp. is a growing concern. Current vaccines, such as O-polysaccharide (OPS) conjugates, are in clinical trials but are ineffective in children but protective in adults. Thus, innovative treatments and vaccines are needed to combat antibiotic resistance. In this study, we used immuno-informatics to design a new multiepitope vaccine and identified S. dysenteriae strain SD197's membrane protein targets using in-silico methods. The target protein was prioritized using membrane protein topology analysis to find membrane proteins. B and T-cell epitopes were predicted for vaccine formulation. The epitopes were shortlisted based on an IC50 value <50, antigenicity, allergenicity, and a toxicity analysis. In the final vaccine construct, a total of 8 B-cell epitopes, 12 MHC Class I epitopes, and 7 MHC Class II epitopes were identified for the Lipopolysaccharide export system permease protein LptF. Additionally, 17 MHC Class I epitopes and 14 MHC Class II epitopes were predicted for the Lipoprotein-releasing ABC transporter permease subunit LolE. These epitopes were selected and linked via KK, AAY, and GGGS linkers, respectively. To enhance the immunogenic response, RGD (arginine-glycine-aspartate) adjuvant was incorporated into the final vaccine construct. The refined vaccine structure exhibits a Ramachandran score of 91.5% and demonstrates stable interaction with TLR4. Normal Mode Analysis (NMA) reveals low eigenvalues (3.925996e-07), indicating steady and flexible molecular mobility of docked complexes. Codon optimization was carried out in an effective microbial expression system of the Escherichia coli K12 strain using the recombinant plasmid pET-28a (+). Finally, the entire in-silico analysis suggests that the suggested vaccine may induce a significant immune response against S. dysenteriae, making it a promising option for additional experimental trials.

Immunoinformatic based designing of potential immunogenic novel mRNA and peptide-based prophylactic vaccines against H5N1 and H7N9 avian influenza viruses

Influenza viruses are the most common cause of serious respiratory illnesses worldwide and are responsible for a significant number of annual fatalities. Therefore, it is crucial to look for new immunogenic sites that might trigger an effective immune response. In the present study, bioinformatics tools were used to design mRNA and multiepitope-based vaccines against H5N1 and H7N9 subtypes of avian influenza viruses. Several Immunoinformatic tools were employed to extrapolate T and B lymphocyte epitopes of HA and NA proteins of both subtypes. The molecular docking approach was used to dock the selected HTL and CTL epitopes with the corresponding MHC molecules. Eight (8) CTL, four (4) HTL, and Six (6) linear B cell epitopes were chosen for the structural arrangement of mRNA and of peptide-based prophylactic vaccine designs. Different physicochemical characteristics of the selected epitopes fitted with suitable linkers were analyzed. High antigenic, non-toxic, and non-allergenic features of the designed vaccines were noted at a neutral physiological pH. Codon optimization tool was used to check the GC content and CAI value of constructed MEVC-Flu vaccine, which were recorded to be 50.42% and 0.97 respectively. the GC content and CAI value verify the stable expression of vaccine in pET28a + vector. In-silico immunological simulation the MEVC-Flu vaccine construct revealed a high level of immune responses. The molecular dynamics simulation and docking results confirmed the stable interaction of TLR-8 and MEVC-Flu vaccine. Based on these parameters, vaccine constructs can be regarded as an optimistic choice against H5N1 and H7N9 strains of the influenza virus. Further experimental testing of these prophylactic vaccine designs against pathogenic avian influenza strains may clarify their safety and efficacy.Communicated by Ramaswamy H. Sarma.

Visual analysis of global hemorrhagic fever with renal syndrome research from 1980 to 2022: Based on CiteSpace and VOSviewer

OBJECTIVE

The development and current state of hemorrhagic fever with renal syndrome (HFRS) over the past 40 years are analyzed in this study, along with explored and discovered the hotspots and frontiers in the field, which serve as the foundation for future investigation.

METHODS

CiteSpace and VOSviewer analysis software were used to visually analyze the literature data on HFRS from 1980 to 2022, including the annual number of publications, countries and research institutions, authors, co-cited literature and keywords.

RESULTS

The number of pertinent papers published in the field of HFRS displayed an overall upward trend from 1980 to 2022. The United States, China, Germany, Sweden, and France are the top 5 countries in terms of publishing volume, with high intermediate centrality mainly concentrated in Europe and the United States. The top 10 co-occurring keywords were hemorrhagic fever, renal syndrome, infection, virus, epidemic, nephropathia epidemical, disease, hantavirus, outbreak, and transmission. According to keyword cluster analysis, there were 4 main research fields. In the HFRS-related study, there were mainly 21 notable keywords and "Korean hemorrhagic fever" had the highest hemorrhagic value (28.87).

CONCLUSION

The United States, China, Germany, Sweden and other countries attached great importance to the HFRS-related research. Moreover, the collaboration between authors and institutions in various collaborator clusters should be strengthened. In recent decades, investigations have focused on the study of viral infection and the clinical symptoms and pathophysiology of HFRS. Future research may concentrate on factors affecting host population distribution and density, such as vaccine development and meteorological factors pertaining to virus transmission.

Association of KIR Genes with Middle East Respiratory Syndrome Coronavirus Infection in South Koreans

BACKGROUND

Middle East respiratory syndrome (MERS) is a lower respiratory tract disease caused by a beta coronavirus (CoV) called MERS-CoV, characterized by a high mortality rate. We aimed to evaluate the association between genetic variation in killer cell immunoglobulin-like receptors (KIRs) and the risk of MERS in South Koreans.

METHODS

KIR genes were genotyped by multiplex polymerase chain reaction with sequence-specific primers (PCR-SSP). A case-control study was performed to identify the odds ratios (OR) of KIR genes for MERS and the association of KIR genes and their ligands, human leukocyte antigens (HLA) genes.

RESULTS

KIR2DS4D and KIR3DP1F showed higher frequencies in the group of all patients infected with MERS-CoV than in the control group (p = 0.023, OR = 2.4; p = 0.039, OR = 2.7). KIR2DL1, KIR2DP1, and KIR3DP1D were significantly associated with moderate/mild (Mo/Mi) cases. KIR2DL2, KIR2DS1, and KIR3DP1F were affected in severe cases. When we investigated the association between KIR genes and their ligands in MERS patient and control groups, KIR3DL1+/Bw4(80I)+, KIR3DL1+/Bw6+, KIR3DL1+/Bw6-, KIR2DS1+/C2+, and KIR3DS+/Bw4(80I)+ were associated with MERS. KIR3DL1+/Bw6- was found in Mo/Mi cases. KIR2DS1+/C2+ and KIR2DS2+/C1+ were found in severe cases.

CONCLUSION

Further investigations are needed to prove the various immune responses of MERS-CoV-infected cells according to variations in the KIR gene and ligand gene. A treatment strategy based on current research on the KIR gene and MERS-CoV will suggest potential treatment targets.

Immunoinformatic exploration of a multi-epitope-based peptide vaccine candidate targeting emerging variants of SARS-CoV-2

Many countries around the world are facing severe challenges due to the recently emerging variants of SARS-CoV-2. Over the last few months, scientists have been developing treatments, drugs, and vaccines to subdue the virus and prevent its transmission. In this context, a peptide-based vaccine construct containing pathogenic proteins of the virus known to elicit an immune response was constructed. An analysis of the spike protein-based epitopes allowed us to design an "epitope-based subunit vaccine" against coronavirus using the approaches of "reverse vaccinology" and "immunoinformatics." Computational experimentation and a systematic, comprehensive protocol were followed with an aim to develop and design a multi-epitope-based peptide (MEBP) vaccine candidate. Our study attempted to predict an MEBP vaccine by introducing mutations of SARS-CoV-2 (Delta, Lambda, Iota, Omicron, and Kappa) in Spike glycoprotein and predicting dual-purpose epitopes (B-cell and T-cell). This was followed by screening the selected epitopes based on antigenicity, allergenicity, and population coverage and constructing them into a vaccine by using linkers and adjuvants. The vaccine construct was analyzed for its physicochemical properties and secondary structure prediction, and a 3D structure was built, refined, and validated. Furthermore, the peptide-protein interaction of the vaccine construct with Toll-like receptor (TLR) molecules was performed. Immune profiling was performed to check the immune response. Codon optimization of the vaccine construct was performed to obtain the GC content before cloning it into the E. coli genome, facilitating its progression it into a vector. Finally, an in-silico simulation of the vaccine-protein complex was performed to comprehend its stability and conformational behavior.

Developing an efficient MGCR microneedle nanovaccine patch for eliciting Th 1 cellular response against the SARS-CoV-2 infection

Rationale: Novel vaccine R&D is essential to interrupt the COVID-19 pandemic and other epidemics in the future. Subunit vaccines have received tremendous attention for their low cost and safety. To improve the immunogenicity of subunit vaccines, we developed a novel vaccine adjuvant system. Methods: Here we rationally designed a CpG 1018 and graphene oxide-based bi-adjuvant system to deliver the Receptor-Binding Domain (RBD) of the SARS-CoV-2 spike protein and obtained the graphene oxide-based complex adjuvant nanovaccine (GCR). Furthermore, we developed a microneedle patch vaccine (MGCR) based on the GCR vaccine. Results: GCR nanovaccine displayed superb antigen loading and encapsulation efficiency. Two dosages of vaccination of GCR nanovaccine could elicit adequate RBD-specific binding antibody response with 2.14-fold higher IgG titer than Alum adjuvant vaccine. The peptide pools assay demonstrated the robust RBD-specific Type 1 Cellular response induced by the GCR nanovaccine in CD8+ T cells. Furthermore, we prepared an MGCR microneedle patch, which generated a similar RBD-specific binding antibody response to the GCR vaccine, sustained a high antibody level above 16 weeks, and significantly elevated the Tcm proportion in mouse spleen. The MGCR microneedle patch vaccine also could be stably stored at room temperature for several months and administrated without medical staff, which maximizes the vaccine distribution efficiency. Conclusion: The vaccine system could significantly improve the vaccine distribution rate in low-income areas and offer a potential vaccination approach to fight against the SARS-Cov-2 infection and other pandemics occurred in the future.

Computational analysis of immunogenic epitopes in the p30 and p54 proteins of African swine fever virus

African swine fever (ASF) is a highly infectious viral disease of pigs, which causes acute fatal haemorrhage and is a severe concern to the global pork industry. The present study followed computational approaches to identify B- and T-cell epitopes for the p30 and p54 proteins of the African swine fever virus (ASFV) by interacting with the swine leukocyte antigen (SLA) alleles. The amino acid sequences of p30 and p54 were analysed for variability and relative solvent accessibility, and their three-dimensional structures were predicted and validated. Molecular dynamics simulation was performed to study the structural and dynamic properties of the protein. Six and five linear B-cell epitopes have been predicted for p30 and p54, respectively. Four and three discontinuous B-cell epitopes have been predicted for p30 and p54, respectively. Further, the top five T-cell epitopes for SLA-1, 2, and 3 have been listed for both proteins. These results can help us to understand the immunodominant regions in the p30 and p54 proteins of ASFV and potentially assist in designing peptide-based diagnostics and vaccines. Also, the identified T-cell epitopes may be considered for peptide-based vaccine design against ASFV.Communicated by Ramaswamy H. Sarma.

Unveiling the functional epitopes of cobra venom cytotoxin by immunoinformatics and epitope-omic analyses

Approximate 70% of cobra venom is composed of cytotoxin (CTX), which is responsible for the dermonecrotic symptoms of cobra envenomation. However, CTX is generally low in immunogenicity, and the antivenom is ineffective in attenuating its in vivo toxicity. Furthermore, little is known about its epitope properties for empirical antivenom therapy. This study aimed to determine the epitope sequences of CTX using the immunoinformatic analyses and epitope-omics profiling. A conserved CTX was used in this study to determine its T-cell and B-cell epitope sequences using immunoinformatic tools and molecular docking simulation with different Human Leukocyte Antigens (HLAs). The potential T-cell and B-cell epitopes were 'KLVPLFY,' 'CPAGKNLCY,' 'MFMVSTPTK,' and 'DVCPKNSLL.' Molecular docking simulations disclosed that the HLA-B62 supertype exhibited the greatest binding affinity towards cobra venom cytotoxin. The namely L7, G18, K19, N20, M25, K33, V43, C44, K46, N47, and S48 of CTX exhibited prominent intermolecular interactions with HLA-B62. The multi-enzymatic-limited-digestion/liquid chromatography-mass spectrometry (MELD/LC-MS) also revealed three potential epitope sequences as 'LVPLFYK,' 'MFMVS,' and 'TVPVKR'. From different epitope mapping approaches, we concluded four potential epitope sites of CTX as 'KLVPLFYK', 'AGKNL', 'MFMVSTPKVPV' and 'DVCPKNSLL'. Site-directed mutagenesis of these epitopes confirmed their locations at the functional loops of CTX. These epitope sequences are crucial to CTX's structural folding and cytotoxicity. The results concluded the epitopes that resided within the functional loops constituted potential targets to fabricate synthetic epitopes for CTX-targeted antivenom production.

A Newly Identified Spike Protein Targeted Linear B-Cell Epitope Based Dissolvable Microneedle Array Successfully Eliciting Neutralizing Activities against SARS-CoV-2 Wild-Type Strain in Mice

Vaccination is a cost-effective medical intervention. Inactivated whole virusor large protein fragments-based severe acute respiratory syndrome coronavirus (SARS-CoV-2) vaccines have high unnecessary antigenic load to induce allergenicity and/orreactogenicity, which can be avoided by peptide vaccines of short peptide fragments that may induce highly targeted immune response. However, epitope identification and peptide delivery remain the major obstacles in developing peptide vaccines. Here, a multi-source data integrated linear B-cell epitope screening strategy is presented and a linear B-cell epitope enriched hotspot region is identified in Spike protein, from which a monomeric peptide vaccine (Epitope25) is developed and applied to subcutaneously immunize wildtype BALB/c mice. Indirect ELISA assay reveals specific and dose-dependent binding between Epitope25 and serum IgG antibodies from immunized mice. The neutralizing activity of sera from vaccinated mice is validated by pseudo and live SARS-CoV-2 wild-type strain neutralization assays. Then a dissolvable microneedle array (DMNA) is developed to pain-freely deliver Epitope25. Compared with intramuscular injection, DMNA and subcutaneous injection elicit neutralizing activities against SARS-CoV-2 wild-type strain as demonstrated by live SARS-CoV-2 virus neutralization assay. No obvious damages are found in major organs of immunized mice. This study may lay the foundation for developing linear B-cell epitope-based vaccines against SARS-CoV-2.

Combining Phage Display Technology with In Silico-Designed Epitope Vaccine to Elicit Robust Antibody Responses against Emerging Pathogen Tilapia Lake Virus

Antigen epitope identification is a critical step in the vaccine development process and is a momentous cornerstone for the development of safe and efficient epitope vaccines. In particular, vaccine design is difficult when the function of the protein encoded by the pathogen is unknown. The genome of Tilapia lake virus (TiLV), an emerging virus from fish, encodes protein functions that have not been elucidated, resulting in a lag and uncertainty in vaccine development. Here, we propose a feasible strategy for emerging viral disease epitope vaccine development using TiLV. We determined the targets of specific antibodies in serum from a TiLV survivor by panning a Ph.D.-12 phage library, and we identified a mimotope, TYTTRMHITLPI, referred to as Pep3, which provided protection against TiLV after prime-boost vaccination; its immune protection rate was 57.6%. Based on amino acid sequence alignment and structure analysis of the target protein from TiLV, we further identified a protective antigenic site (399TYTTRNEDFLPT410) which is located on TiLV segment 1 (S1). The epitope vaccine with keyhole limpet hemocyanin (KLH-S1399-410) corresponding to the mimotope induced the tilapia to produce a durable and effective antibody response after immunization, and the antibody depletion test confirmed that the specific antibody against S1399-410 was necessary to neutralize TiLV. Surprisingly, the challenge studies in tilapia demonstrated that the epitope vaccine elicited a robust protective response against TiLV challenge, and the survival rate reached 81.8%. In conclusion, this study revealed a concept for screening antigen epitopes of emerging viral diseases, providing promising approaches for development and evaluation of protective epitope vaccines against viral diseases. IMPORTANCE Antigen epitope determination is an important cornerstone for developing efficient vaccines. In this study, we attempted to explore a novel approach for epitope discovery of TiLV, which is a new virus in fish. We investigated the immunogenicity and protective efficacy of all antigenic sites (mimotopes) identified in serum of primary TiLV survivors by using a Ph.D.-12 phage library. We also recognized and identified the natural epitope of TiLV by bioinformatics, evaluated the immunogenicity and protective effect of this antigenic site by immunization, and revealed 2 amino acid residues that play important roles in this epitope. Both Pep3 and S1399-410 (a natural epitope identified by Pep3) elicited antibody titers in tilapia, but S1399-410 was more prominent. Antibody depletion studies showed that anti-S1399-410-specific antibodies were essential for neutralizing TiLV. Our study demonstrated a model for combining experimental and computational screens to identify antigen epitopes, which is attractive for epitope-based vaccine development.

Subunit vaccines with a saponin-based adjuvant boost humoral and cellular immunity to MERS coronavirus

Middle East respiratory syndrome coronavirus (MERS-CoV) outbreaks have constituted a public health issue with drastic mortality higher than 34%, necessitating the development of an effective vaccine. During MERS-CoV infection, the trimeric spike protein on the viral envelope is primarily responsible for attachment to host cellular receptor, dipeptidyl peptidase 4 (DPP4). With the goal of generating a protein-based prophylactic, we designed a subunit vaccine comprising the recombinant S1 protein with a trimerization motif (S1-Fd) and examined its immunogenicity and protective immune responses in combination with various adjuvants. We found that sera from immunized wild-type and human DPP4 transgenic mice contained S1-specific antibodies that can neutralize MERS-CoV infection in susceptible cells. Vaccination with S1-Fd protein in combination with a saponin-based QS-21 adjuvant provided long-term humoral as well as cellular immunity in mice. Our findings highlight the significance of the trimeric S1 protein in the development of MERS-CoV vaccines and offer a suitable adjuvant, QS-21, to induce robust and prolonged memory T cell response.

MERS virus spike protein HTL-epitopes selection and multi-epitope vaccine design using computational biology

MERS-CoV, a zoonotic virus, poses a serious threat to public health globally. Thus, it is imperative to develop an effective vaccination strategy for protection against MERS-CoV. Immunoinformatics and computational biology tools provide a faster and more cost-effective strategy to design potential vaccine candidates. In this work, the spike proteins from different strains of MERS-CoV were selected to predict HTL-epitopes that show affinity for T-helper MHC-class II HTL allelic determinant (HLA-DRB1:0101). The antigenicity and conservation of these epitopes among the selected spike protein variants in different MERS-CoV strains were analyzed. The analysis identified five epitopes with high antigenicity: QSIFYRLNGVGITQQ, DTIKYYSIIPHSIRS, PEPITSLNTKYVAPQ, INGRLTTLNAFVAQQ and GDMYVYSAGHATGTT. Then, a multi-epitope vaccine candidate was designed using linkers and adjuvant molecules. Finally, the vaccine construct was subjected to molecular docking with TLR5 (Toll-like receptor-5). The proposed vaccine construct had strong binding energy of -32.3 kcal/mol when interacting with TLR5.Molecular dynamics simulation analysis showed that the complex of the vaccine construct and TLR5 is stable. Analysis using in silico immune simulation also showed that the prospective multi-epitope vaccine design had the potential to elicit a response within 70 days, with the immune system producing cytokines and immunoglobulins. Finally, codon adaptation and in silico cloning analysis showed that the candidate vaccine could be expressed in the Escherichia coli K12 strain. Here we also designed support vaccine construct MEV-2 by using B-cell and CD8+ CTL epitopes to generate the complete immunogenic effect. This study opens new avenues for the extension of research on MERS vaccine development.Communicated by Ramaswamy H. Sarma.

Recent trends in next generation immunoinformatics harnessed for universal coronavirus vaccine design

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally devastated public health, the economies of many countries and quality of life universally. The recent emergence of immune-escaped variants and scenario of vaccinated individuals being infected has raised the global concerns about the effectiveness of the current available vaccines in transmission control and disease prevention. Given the high rate mutation of SARS-CoV-2, an efficacious vaccine targeting against multiple variants that contains virus-specific epitopes is desperately needed. An immunoinformatics approach is gaining traction in vaccine design and development due to the significant reduction in time and cost of immunogenicity studies and increasing reliability of the generated results. It can underpin the development of novel therapeutic methods and accelerate the design and production of peptide vaccines for infectious diseases. Structural proteins, particularly spike protein (S), along with other proteins have been studied intensively as promising coronavirus vaccine targets. Numbers of promising online immunological databases, tools and web servers have widely been employed for the design and development of next generation COVID-19 vaccines. This review highlights the role of immunoinformatics in identifying immunogenic peptides as potential vaccine targets, involving databases, and prediction and characterization of epitopes which can be harnessed for designing future coronavirus vaccines.

UreB immunodominant epitope-specific CD8+ T-cell responses were beneficial in reducing gastric symptoms in Helicobacter pylori-infected individuals

BACKGROUND AND AIMS

Although Helicobacter pylori is recognized as an extracellular infection bacterium, it can lead to an increase in the number of CD8⁺ T cells after infection. At present, the characteristics of H. pylori antigen-specific CD8⁺ T cells and the epitope response have not been elucidated. This study was focused on putative protective antigen UreB to detect specific CD8⁺ T-cell responses in vitro and screen for predominant response epitopes.

METHODS

The PBMCs collected from H. pylori-infected individuals were stimulated by UreB peptide pools in vitro to identify the immunodominant CD8⁺ T-cell epitopes. Furthermore, their HLA restriction characteristics were detected accordingly by NGS. Finally, the relationship between immunodominant responses and appearance of gastric symptoms after H. pylori infection was conducted.

RESULTS

UreB-specific CD8⁺ T-cell responses were detected in H. pylori-infected individuals. Three of UreB dominant epitopes (A-2 (UreB_443-451 : GVKPNMIIK), B-4 (UreB_420-428 : SEYVGSVEV), and C-1 (UreB_5-13 : SRKEYVSMY)) were firstly identified and mainly presented by HLA-A*1101, HLA-B*4001 and HLA-C*0702 alleles, respectively. C-1 responses were mostly occurred in H. pylori-infected subjects without gastric symptoms and may alleviate the degree of gastric inflammation.

CONCLUSIONS

The UreB dominant epitope-specific CD8⁺ T-cell response was closely related to the gastric symptoms after H. pylori infection, and the C-1 (UreB_5-13 ) dominant peptides may be protective epitopes.

Protocol for a scoping review of potential vaccine candidates predicted by VaxiJen for different viral pathogens between 2017-2021

BACKGROUND

Vaccination is essential for the prevention of infectious diseases and has helped to reduce disease-related mortality, such as pneumonia. However, traditional vaccine development is time-consuming and risky. Reverse vaccinology (RV) is a promising alternative to developing vaccines based on the in silico discovery of antigens, often termed 'potential vaccine candidates' (PVCs), using a pathogen's proteome. RV prediction technologies, such as VaxiJen (founded in 2007), are used to take the first step toward vaccine development. VaxiJen is used by researchers to identify PVCs for various diseases. A 10-year review of these PVCs was published in 2017. There has since been no review of viral PVCs predicted by VaxiJen from 2017 to 2021. The proposed scoping review aims to address this gap.

METHODS

This protocol is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) 2015 checklist. The review will employ Arksey and O'Malley's five-stage methodological framework, which was later enhanced by Levac et al. and the Joanna Briggs Institute (JBI). The PRISMA extension for Scoping Reviews (PRISMA-ScR) reporting guideline will be utilized with this framework. PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic will be searched using the term 'vaxijen'. The inclusion criteria will be English-only full-text original articles published in peer-reviewed journals and unpublished papers from 2017 to 2021. Rayyan will be used to deduplicate, screen titles and abstracts of articles. The articles' full texts will be examined. The data will be extracted using Microsoft Excel. Using a data charting form, data will be sifted and organized by key categories and themes.

DISCUSSION

This protocol was submitted for publication and went through an extensive peer review process. The review has implications for novel vaccine development against various viruses. The key limitation of this study is language bias due to the selection of English-only papers because of limited resources. This study will not require ethical clearance since it will use secondary data and will not include patients. Nevertheless, this research is part of a larger project that was submitted for ethical consideration to the Biomedical Research Ethics Committee of the University of KwaZulu-Natal in South Africa. This study's findings will be published in a peer-reviewed journal and provided to relevant stakeholders.

SYSTEMATIC REVIEW REGISTRATION

Open Science Framework (OSF): https://osf.io/ht8wr.

Exploiting reverse vaccinology approach for the design of a multiepitope subunit vaccine against the major SARS-CoV-2 variants

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.

Immunoinformatics-Aided Design of a Peptide Based Multiepitope Vaccine Targeting Glycoproteins and Membrane Proteins against Monkeypox Virus

Monkeypox is a self-limiting zoonotic viral disease and causes smallpox-like symptoms. The disease has a case fatality ratio of 3-6% and, recently, a multi-country outbreak of the disease has occurred. The currently available vaccines that have provided immunization against monkeypox are classified as live attenuated vaccinia virus-based vaccines, which pose challenges of safety and efficacy in chronic infections. In this study, we have used an immunoinformatics-aided design of a multi-epitope vaccine (MEV) candidate by targeting monkeypox virus (MPXV) glycoproteins and membrane proteins. From these proteins, seven epitopes (two T-helper cell epitopes, four T-cytotoxic cell epitopes and one linear B cell epitopes) were finally selected and predicted as antigenic, non-allergic, interferon-γ activating and non-toxic. These epitopes were linked to adjuvants to design a non-allergic and antigenic candidate MPXV-MEV. Further, molecular docking and molecular dynamics simulations predicted stable interactions between predicted MEV and human receptor TLR5. Finally, the immune-simulation analysis showed that the candidate MPXV-MEV could elicit a human immune response. The results obtained from these in silico experiments are promising but require further validation through additional in vivo experiments.

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.

Comprehensive computational analysis reveals YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides across HFRS causing Hantaviruses and their association with viral pathogenesis and host immune regulation

Hemorrhagic fever with renal syndrome (HFRS) is an acute zoonotic disease transmitted through aerosolized excrement of rodents. The etiology of HFRS is complex due to the involvement of viral factors and host immune and genetic factors. The viral species that dominantly cause HFRS are Puumala virus (PUUV), Seoul virus (SEOV), Dobrava-Belgrade virus (DOBV), and Hantaan virus (HTNV). Despite continuous prevention and control measures, HFRS remains a significant public health problem worldwide. The nucleocapsid protein of PUUV, SEOV, DOBV, and HTNV is a multifunctional viral protein involved in various stages of the viral replication cycle. However, the exact role of nucleoproteins in viral pathogenesis is yet to be discovered. Targeting a universal host protein exploited by most viruses would be a game-changing strategy that offers broad-spectrum solutions and rapid epidemic control. The objective of this study is to understand the replication and pathogenesis of PUUV, SEOV, DOBV, and HTNV by targeting tyrosine-based motif (YXXΦ[I/L/M/F/V]) and YXXΦ-like tetrapeptides. In the light of the current study, in silico analysis uncovered many different YXXΦ[I/L/M/F/V] motifs and YXXΦ-like tetrapeptides within nucleoproteins of PUUV, SEOV, DOBV, and HTNV. Following that, the 3D structures of nucleoproteins were predicted using AlphaFold2 to map the location of YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides in a 3D environment. Further, in silico analysis and characterization of Post Translational Modifications (PTMs) revealed multiple PTMs sites within YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides, which contribute to virulence and host immune regulation. Our study proposed that the predicted YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides may confer specific functions such as virulence, host immune regulation, and pathogenesis to nucleoproteins of PUUV, SEOV, DOBV, and HTNV. However, in vivo and in vitro studies on YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides will assign new biological roles to these antiviral targets.

Design of a multi-epitope vaccine against the pathogenic fungi Candida tropicalis using an in silico approach

Background

Candida tropicalis causes tropical invasive fungal infections, with a high mortality. This fungus has been found to be resistant to antifungal classes such as azoles, echinocandins, and polyenes in several studies. As a result, it is vital to identify novel approaches to prevent and treat C. tropicalis infections. In this study, an in silico technique was utilized to deduce and evaluate a powerful multivalent epitope-based vaccine against C. tropicalis, which targets the secreted aspartic protease 2 (SAP2) protein. This protein is implicated in virulence and host invasion.

Results

By focusing on the Sap2 protein, 11 highly antigenic, non-allergic, non-toxic, and conserved epitopes were identified. These were subsequently paired with RS09 and flagellin adjuvants, as well as a pan HLA DR-binding epitope (PADRE) sequence to create a vaccine candidate that elicited both cell-mediated and humoral immune responses. It was projected that the vaccine design would be soluble, stable, antigenic, and non-allergic. Ramachandran plot analysis was applied to validate the vaccine construct’s 3-dimensional model. The vaccine construct was tested (at 100 ns) using molecular docking and molecular dynamics simulations, which demonstrated that it can stably connect with MHC-I and Toll-like receptor molecules. Based on in silico studies, we have shown that the vaccine construct can be expressed in E. coli. We surmise that the vaccine design is unrelated to any human proteins, indicating that it is safe to use.

Conclusions

The vaccine design looks to be an effective option for preventing C. tropicalis infections, based on the outcomes of the studies. A fungal vaccine can be proposed as prophylactic medicine and could provide initial protection as sometimes diagnosis of infection could be challenging. However, more in vitro and in vivo research is needed to prove the efficacy and safety of the proposed vaccine design.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-022-00415-3.

Immunoinformatics approach to epitope-based vaccine design against the SARS-CoV-2 in Bangladeshi patients

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic which has brought a great challenge to public health. After the first emergence of novel coronavirus SARS-CoV-2 in the city of Wuhan, China, in December 2019. As of March 2020, SARS-CoV-2 was first reported in Bangladesh and since then the country has experienced a steady rise in infections, resulting in 13,355,191 cases and 29,024 deaths as of 27 February 2022. Bioinformatics techniques are used to predict B cell and T cell epitopes from the new SARS-CoV-2 spike glycoprotein in order to build a unique multiple epitope vaccine. The immunogenicity, antigenicity scores, and toxicity of these epitopes were evaluated and chosen based on their capacity to elicit an immune response.

RESULT

The best multi-epitope of the possible immunogenic property was created by combining epitopes. EAAAK, AAY, and GPGPG linkers were used to connect the epitopes. In several computer-based immune response analyses, this vaccine design was found to be efficient, as well as having high population coverage.

CONCLUSION

This research is entirely reliant on the development of epitope-based vaccines, and these in silico findings would represent a major step forward in the development of a vaccine that might eradicate SARS-CoV-2 in Bangladeshi patients.

In silico designing of a novel epitope-based candidate vaccine against Streptococcus pneumoniae with introduction of a new domain of PepO as adjuvant

BACKGROUND

Streptococcus pneumoniae is the leading reason for invasive diseases including pneumonia and meningitis, and also secondary infections following viral respiratory diseases such as flu and COVID-19. Currently, serotype-dependent vaccines, which have several insufficiency and limitations, are the only way to prevent pneumococcal infections. Hence, it is plain to need an alternative effective strategy for prevention of this organism. Protein-based vaccine involving conserved pneumococcal protein antigens with different roles in virulence could provide an eligible alternative to existing vaccines.

METHODS

In this study, PspC, PhtD and PsaA antigens from pneumococcus were taken to account to predict B-cell and helper T-cell epitopes, and epitope-rich regions were chosen to build the construct. To enhance the immunogenicity of the epitope-based vaccine, a truncated N-terminal fragment of pneumococcal endopeptidase O (PepO) was used as a potential TLR2/4 agonist which was identified by molecular docking studies. The ultimate construct was consisted of the chosen epitope-rich regions, along with the adjuvant role (truncated N-PepO) and suitable linkers.

RESULTS

The epitope-based vaccine was assessed as regards physicochemical properties, allergenicity, antigenicity, and toxicity. The 3D structure of the engineered construct was modeled, refined, and validated. Molecular docking and simulation of molecular dynamics (MD) indicated the proper and stable interactions between the vaccine and TLR2/4 throughout the simulation periods.

CONCLUSIONS

For the first time this work presents a novel vaccine consisting of epitopes of PspC, PhtD, and PsaA antigens which is adjuvanted with a new truncated domain of PepO. The computational outcomes revealed that the suggested vaccine could be deemed an efficient therapeutic vaccine for S. pneumoniae; nevertheless, in vitro and in vivo examinations should be performed to prove the potency of the candidate vaccine.

A new approach for determining SARS-CoV-2 epitopes using machine learning-based in silico methods

The emergence of machine learning-based in silico tools has enabled rapid and high-quality predictions in the biomedical field. In the COVID-19 pandemic, machine learning methods have been used in many topics such as predicting the death of patients, modeling the spread of infection, determining future effects, diagnosis with medical image analysis, and forecasting the vaccination rate. However, there is a gap in the literature regarding identifying epitopes that can be used in fast, useful, and effective vaccine design using machine learning methods and bioinformatics tools. Machine learning methods can give medical biotechnologists an advantage in designing a faster and more successful vaccine. The motivation of this study is to propose a successful hybrid machine learning method for SARS-CoV-2 epitope prediction and to identify nonallergen, nontoxic, antigen peptides that can be used in vaccine design from the predicted epitopes with bioinformatics tools. The identified epitopes will be effective not only in the design of the COVID-19 vaccine but also against viruses from the SARS family that may be encountered in the future. For this purpose, epitope prediction performances of random forest, support vector machine, logistic regression, bagging with decision tree, k-nearest neighbor and decision tree methods were examined. In the SARS-CoV and B-cell datasets used for education in the study, epitope estimation was performed again after the datasets were balanced with the synthetic minority oversampling technique (SMOTE) method since the epitope class samples were in the minority compared to the nonepitope class. The experimental results obtained were compared and the most successful predictions were obtained with the random forest (RF) method. The epitope prediction performance in balanced datasets was found to be higher than that in the original datasets (94.0% AUC and 94.4% PRC for the SMOTE-SARS-CoV dataset; 95.6% AUC and 95.3% PRC for the SMOTE-B-cell dataset). In this study, 252 peptides out of 20312 peptides were determined to be epitopes with the SMOTE-RF-SVM hybrid method proposed for SARS-CoV-2 epitope prediction. Determined epitopes were analyzed with AllerTOP 2.0, VaxiJen 2.0 and ToxinPred tools, and allergic, nonantigen, and toxic epitopes were eliminated. As a result, 11 possible nonallergic, high antigen and nontoxic epitope candidates were proposed that could be used in protein-based COVID-19 vaccine design ("VGGNYNY", "VNFNFNGLTG", "RQIAPGQTGKI", "QIAPGQTGKIA", "SYECDIPIGAGI", "STFKCYGVSPTKL", "GVVFLHVTYVPAQ", "KNHTSPDVDLGDI", "NHTSPDVDLGDIS", "AGAAAYYVGYLQPR", "KKSTNLVKNKCVNF"). It is predicted that the few epitopes determined by machine learning-based in silico methods will help biotechnologists design fast and accurate vaccines by reducing the number of trials in the laboratory environment.

An Immunoinformatic Strategy to Develop New Mycobacterium tuberculosis Multi-epitope Vaccine

Mycobacterium tuberculosis causes a life-threatening disease known as tuberculosis (TB). In 2021, tuberculosis was the second cause of death after COVID-19 among infectious diseases. Latent life cycle and development of multidrug resistance in one hand and lack of an effective vaccine in another hand have made TB a global health issue. Here, a multi-epitope vaccine have been designed against TB using five new antigenic protein and immunoinformatic tools. To do so, immunodominant MHC-I/MHC-II binding epitopes of Rv2346, Rv2347, Rv3614, Rv3615 and Rv2031 antigenic proteins have been selected using advanced computational procedures. The vaccine was designed by linking ten epitopes from the antigenic proteins and flagellin and TpD as adjuvant. Three-dimensional (3D) structure of the vaccine was modeled, was refined and was evaluated using bioinformatics tools. The 3D structure of the vaccine was docked into the toll-like-receptors (TLR3, 4, 8) to evaluate potential interaction between the vaccine and TLRs. Evaluation of immunological and physicochemical properties of the constructed vaccine have demonstrated the vaccine construct can induce significant humoral and cellular immune responses, the vaccine is non-allergenic and can be recognized by TLR proteins. The immunoinformatic results reported in the present study demonstrates that it is worth following the designed vaccine by experimental investigations.

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.

Development of peptide vaccine candidate using highly antigenic PE-PGRS family proteins to stimulate the host immune response against Mycobacterium tuberculosis H37Rv: an immuno-informatics approach

Tuberculosis (TB) is a fast spreading; transmissible disease caused by the Mycobacterium tuberculosis (M. tuberculosis). M. tuberculosis has a high death rate in its endemic regions due to a lack of appropriate treatment and preventative measures. We have used a vaccinomics strategy to create an effective multi-epitope vaccine against M. tuberculosis. The antigenic proteins with the highest antigenicity were utilised to predict cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes. CTL and HTL epitopes were covered in 99.97% of the population. Seven epitopes each of CTL, HTL, and LBL were ultimately selected and utilised to develop a multi-epitope vaccine. A vaccine design was developed by combining these epitopes with suitable linkers and LprG adjuvant. The vaccine chimera was revealed to be highly immunogenic, non-allergenic, and non-toxic. To ensure a better expression within the Escherichia coli K12 (E. coli K12) host system, codon adaptation and in silico cloning were accomplished. Following that, various validation studies were conducted, including molecular docking, molecular dynamics simulation, and immunological simulation, all of which indicated that the designed vaccine would be stable in the biological environment and effective against M. tuberculosis infection. The immune simulation revealed higher levels of T-cell and B-cell activity, which corresponded to the actual immune response. Exposure simulations were repeated several times, resulting in increased clonal selection and faster antigen clearance. These results suggest that, if proposed vaccine chimera would test both in-vitro and in-vivo, it could be a viable treatment and preventive strategy for TB.Communicated by Ramaswamy H. Sarma.

Computational vaccinology guided design of multi-epitope subunit vaccine against a neglected arbovirus of the Americas

Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions.Communicated by Ramaswamy H. Sarma.

Current advances and challenges in COVID-19 vaccine development: from conventional vaccines to next-generation vaccine platforms

The world is grappling with an unprecedented public health crisis COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2. Due to the high transmission/mortality rates and socioeconomic impacts of the COVID-19, its control is crucial. In the absence of specific treatment, vaccines represent the most efficient way to control and stop the pandemic. Many companies around the world are currently making efforts to develop the vaccine to combat COVID-19. This review outlines key strategies for generating SARS-CoV-2 vaccine candidates, along with the mechanism of action, advantages, and potential limitations of each vaccine. The use of nanomaterials and nanotechnology for COVID-19 vaccines development will also be discussed.

Peptides for Vaccine Development

This review discusses peptide epitopes used as antigens in the development of vaccines in clinical trials as well as future vaccine candidates. It covers peptides used in potential immunotherapies for infectious diseases including SARS-CoV-2, influenza, hepatitis B and C, HIV, malaria, and others. In addition, peptides for cancer vaccines that target examples of overexpressed proteins are summarized, including human epidermal growth factor receptor 2 (HER-2), mucin 1 (MUC1), folate receptor, and others. The uses of peptides to target cancers caused by infective agents, for example, cervical cancer caused by human papilloma virus (HPV), are also discussed. This review also provides an overview of model peptide epitopes used to stimulate non-specific immune responses, and of self-adjuvanting peptides, as well as the influence of other adjuvants on peptide formulations. As highlighted in this review, several peptide immunotherapies are in advanced clinical trials as vaccines, and there is great potential for future therapies due the specificity of the response that can be achieved using peptide epitopes.

A novel ensemble fuzzy classification model in SARS-CoV-2 B-cell epitope identification for development of protein-based vaccine

B-cell epitope prediction research has received growing interest since the development of the first method. B-cell epitope identification with the aid of an accurate prediction method is one of the most important steps in epitope-based vaccine development, immunodiagnostic testing, antibody production, disease diagnosis, and treatment. Nevertheless, using experimental methods in epitope mapping is very time-consuming, costly, and labor-intensive. Therefore, although successful predictions with in silico methods are very important in epitope prediction, there are limited studies in this area. The aim of this study is to propose a new approach for successfully predicting B-cell epitopes for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, the SARS-CoV B-cell epitope prediction performances of different fuzzy learning classification models genetic cooperative competitive learning (GCCL), fuzzy genetics-based machine learning (GBML), Chi's method (CHI), Ishibuchi's method with weight factor (W), structural learning algorithm on vague environment (SLAVE) and the state-of-the-art ensemble fuzzy classification model were compared. The obtained results showed that the proposed ensemble approach has the lowest error in SARS-CoV B-cell epitope estimation compared to the base fuzzy learners (average error rates; ensemble fuzzy=8.33, GCCL=30.42, GBML=23.82, CHI=29.17, W=46.25, and SLAVE=20.42). SARS-CoV and SARS-CoV-2 have high genome similarities. Therefore, the most successful method determined for SARS-CoV B-cell epitope prediction was used in SARS-CoV-2 cell epitope prediction. Finally, the eventual B-cell epitope prediction results obtained for SARS-CoV-2 with the ensemble fuzzy classification model were compared with the epitope sequences predicted by the BepiPred server and immunoinformatics studies in the literature for the same protein sequences according to VaxiJen 2.0 scores. We hope that the developed epitope prediction method will help design effective vaccines and drugs against future outbreaks of the coronavirus family, especially SARS-CoV-2 and its possible mutations.

Precise location of two novel linear epitopes on the receptor-binding domain surface of MERS-CoV spike protein recognized by two different monoclonal antibodies

Middle East respiratory syndrome coronavirus (MERS-CoV) is a coronavirus which can cause severe human respiratory diseases with a fatality rate of almost 36%. In this study, we report the generation, characterization and epitope mapping of several monoclonal antibodies against the spike receptor-binding domain (RBD) of MERS-CoV. Two monoclonal antibodies (4C7 and 6E8) that can react with linearized RBD have been selected for subsequent identification of RBD mAb-binding epitopes. Two distinct novel linear epitopes, ⁴²³FTCSQIS⁴²⁹ and ⁵⁴⁶SPLEGGGWL⁵⁵⁴,were precisely located at the outermost surface of RBD by dot-blot hybridization and ELISAs. Multiple sequence alignment analysis showed that these two peptides were highly conserved. Alanine (A)-scanning mutagenesis demonstrated that residues 423F, 428I, and 429S are the crucial residues for the linear epitope ⁴²³FTCSQIS⁴²⁹ while residues 548L, 550G, 553W, 554L for epitope ⁵⁴⁶SPLEGGGWL⁵⁵⁴. These findings may be helpful for further understanding of the function of RBD protein and the development of subsequent diagnosis and detection methods.

Comparative Immunogenicity of the Recombinant Receptor-Binding Domain of Protein S SARS-CoV-2 Obtained in Prokaryotic and Mammalian Expression Systems

The receptor-binding domain (RBD) of the protein S SARS-CoV-2 is considered to be one of the appealing targets for developing a vaccine against COVID-19. The choice of an expression system is essential when developing subunit vaccines, as it ensures the effective synthesis of the correctly folded target protein, and maintains its antigenic and immunogenic properties. Here, we describe the production of a recombinant RBD protein using prokaryotic (pRBD) and mammalian (mRBD) expression systems, and compare the immunogenicity of prokaryotic and mammalian-expressed RBD using a BALB/c mice model. An analysis of the sera from mice immunized with both variants of the protein revealed that the mRBD expressed in CHO cells provides a significantly stronger humoral immune response compared with the RBD expressed in E.coli cells. A specific antibody titer of sera from mice immunized with mRBD was ten-fold higher than the sera from the mice that received pRBD in ELISA, and about 100-fold higher in a neutralization test. The data obtained suggests that mRBD is capable of inducing neutralizing antibodies against SARS-CoV-2.

A New Epitope Selection Method: Application to Design a Multi-Valent Epitope Vaccine Targeting HRAS Oncogene in Squamous Cell Carcinoma

We developed an epitope selection method for the design of MHC targeting peptide vaccines. The method utilizes predictions for several clinical checkpoint filters, including binding affinity, immunogenicity, antigenicity, half-life, toxicity, IFNγ release, and instability. The accuracy of the prediction tools for these filter variables was confirmed using experimental data obtained from the Immune Epitope Database (IEDB). We also developed a graphical user interface computational tool called 'PCOptim' to assess the success of an epitope filtration method. To validate the filtration methods, we used a large data set of experimentally determined, immunogenic SARS-CoV-2 epitopes, which were obtained from a meta-analysis. The validation process proved that placing filters on individual parameters was the most effective method to select top epitopes. For a proof-of-concept, we designed epitope-based vaccine candidates for squamous cell carcinoma, selected from the top mutated epitopes of the HRAS gene. By comparing the filtered epitopes to PCOptim's output, we assessed the success of the epitope selection method. The top 15 mutations in squamous cell carcinoma resulted in 16 CD8 epitopes which passed the clinical checkpoints filters. Notably, the identified HRAS epitopes are the same as the clinical immunogenic HRAS epitope-based vaccine candidates identified by the previous studies. This indicates further validation of our filtration method. We expect a similar turn-around for the other designed HRAS epitopes as a vaccine candidate for squamous cell carcinoma. Furthermore, we obtained a world population coverage of 89.45% for the top MHC Class I epitopes and 98.55% population coverage in the absence of the IFNγ release clinical checkpoint filter. We also identified some of the predicted human epitopes to be strong binders to murine MHC molecules, which provides insight into studying their immunogenicity in preclinical models. Further investigation in murine models could warrant the application of these epitopes for treatment or prevention of squamous cell carcinoma.

Sterilizing Immunity against COVID-19: Developing Helper T cells I and II activating vaccines is imperative

Six months after the publication of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) sequence, a record number of vaccine candidates were listed, and quite a number of them have since been approved for emergency use against the novel coronavirus disease 2019 (COVID-19). This unprecedented pharmaceutical feat did not only show commitment, creativity and collaboration of the scientific community, but also provided a swift solution that prevented global healthcare system breakdown. Notwithstanding, the available data show that most of the approved COVID-19 vaccines protect only a proportion of recipients against severe disease but do not prevent clinical manifestation of COVID-19. There is therefore the need to probe further to establish whether these vaccines can induce sterilizing immunity, otherwise, COVID-19 vaccination would have to become a regular phenomenon. The emergence of SARS-CoV-2 variants could further affect the capability of the available COVID-19 vaccines to prevent infection and protect recipients from a severe form of the disease. These notwithstanding, data about which vaccine(s), if any, can confer sterilizing immunity are unavailable. Here, we discuss the immune responses to viral infection with emphasis on COVID-19, and the specific adaptive immune response to SARS-CoV-2 and how it can be harnessed to develop COVID-19 vaccines capable of conferring sterilizing immunity. We further propose factors that could be considered in the development of COVID-19 vaccines capable of stimulating sterilizing immunity. Also, an old, but effective vaccine development technology that can be applied in the development of COVID-19 vaccines with sterilizing immunity potential is reviewed.

Exploration of antigenic determinants in spike glycoprotein of SARS-CoV2 and identification of five salient potential epitopes

Emerging pathogens have been an eternal threat to mankind. In a series of pandemics caused by notorious coronaviruses, a newly emerged SARS-CoV2 virus is creating panic among the world population. The unavailability of reliable theranostics insists the exploration of antigenic determinants in spike glycoprotein of SARS-CoV2. The four novel inserts ('70VSGTNGT76', '150KSWM153', 247SYLTPG252 and 674QTQTNSPRR682) in SARS-CoV2 spike protein were unraveled via multiple sequence alignment of spike proteins of SARS-CoV2, SARS-CoV, and MERS-CoV. The three-dimension (3D) modeling of the spike protein of the SARS-CoV2 and their interaction with the ACE2 receptor was delineated with the help of SWISS-MODEL and 3DLigandSite web servers. The predicted 3D model of SARS-CoV2 was further verified by SAVES, RAMPAGE, and ProSA-web tools. The potential B-cell immunogenic epitopes of SARS-CoV2 were predicted out by using various software viz. IEDB B-cell epitopes prediction tool, BepiPred linear epitope prediction tool, Emini Surface Accessibility Prediction tool, and Kolaskar-Tongaonkar antigenicity web tool. The five epitopes (i.e. '71SGTNGTKRFDN81, 247SYLTPG252, 634RVYST638, 675QTQTNSPRRARSV687, and 1054QSAPH1058) were selected as potent antigenic determinants. The quantum of information generated by this study will prove beneficial for the development of effective therapeutics, diagnostics, and multi-epitopic vaccines to combat this ongoing menace.

An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis

Tuberculosis (TB) is a highly contagious disease that mostly affects the lungs and is caused by a bacterial pathogen, Mycobacterium tuberculosis. The associated mortality rate of TB is much higher compared to any other disease and the situation is more worrisome by the rapid emergence of drug resistant strains. Bacillus Calmette-Guerin (BCG) is the only licensed attenuated vaccine available for use in humans however, many countries have stopped its use as it fails to confer protective immunity. Therefore, urgent efforts are required to identify new and safe vaccine candidates that are not only provide high immune protection but also have broad spectrum applicability. Considering this, herein, I performed an extensive computational vaccine analysis to investigate 200 complete sequenced genomes of M. tuberculosis to identify core vaccine candidates that harbor safe, antigenic, non-toxic, and non-allergic epitopes. To overcome literature reported limitations of epitope-based vaccines, I carried out additional analysis by designing a multi-epitopes vaccine to achieve maximum protective immunity as well as to make experimental follow up studies easy by selecting a vaccine that can be easily analyzed because of its favorable physiochemical profile. Based on these analyses, I identified two potential vaccine proteins that fulfill all required vaccine properties. These two vaccine proteins are diacylglycerol acyltransferase and ESAT-6-like protein. Epitopes: DSGGYNANS from diacylglycerol acyltransferase and AGVQYSRAD, ADEEQQQAL, and VSRADEEQQ from ESAT-6-like protein were found to cover all necessary parameters and thus used in a multi-epitope vaccine construct. The designed vaccine is depicting a high binding affinity for different immune receptors and shows stable dynamics and rigorous van der Waals and electrostatic binding energies. The vaccine also simulates profound primary, secondary, tertiary immunoglobulin production as well as high interleukins and interferons count. In summary, the designed vaccine is ideal to be evaluated experimentally to decipher its real biological efficacy in controlling drug resistant infections of M. tuberculosis.

Role of artificial intelligence in peptide vaccine design against RNA viruses

RNA viruses have high rate of replication and mutation that help them adapt and change according to their environmental conditions. Many viral mutants are the cause of various severe and lethal diseases. Vaccines, on the other hand have the capacity to protect us from infectious diseases by eliciting antibody or cell-mediated immune responses that are pathogen-specific. While there are a few reviews pertaining to the use of artificial intelligence (AI) for SARS-COV-2 vaccine development, none focus on peptide vaccination for RNA viruses and the important role played by AI in it. Peptide vaccine which is slowly coming to be recognized as a safe and effective vaccination strategy has the capacity to overcome the mutant escape problem which is also being currently faced by SARS-COV-2 vaccines in circulation.Here we review the present scenario of peptide vaccines which are developed using mathematical and computational statistics methods to prevent the spread of disease caused by RNA viruses. We also focus on the importance and current stage of AI and mathematical evolutionary modeling using machine learning tools in the establishment of these new peptide vaccines for the control of viral disease.

Identification of immunodominant epitopes in allelic variants VK210 and VK247 of Plasmodium Vivax Circumsporozoite immunogen

Plasmodium vivax-induced malaria is among the leading causes of morbidity and mortality in sub-tropical and tropical regions and infect 2.85 billion people globally. The continual rise and propagation of resistance against anti-malarial drugs is a prerequisite to develop a potent vaccine candidate for Plasmodium vivax (P. vivax). Circumsporozoite protein (CSP) is an important immunogen of malaria parasite that has the conserved CSP structure as an immune dominant B-cell epitope. In current study, we focused on designing multi-epitope vaccines (MEVs) using various immunoinformatics tools against Pakistani based allelic variants VK210 and VK247 of P. vivax CSP (PvCSP) gene. Antigenicity, allergic potential and physicochemical parameters of both PvCSP variants were assessed for the designed MEVs and they were within acceptable range suitable for post experimental investigations. The three-dimensional structures of both MEVs have been predicted ab initio, optimized, and validated by using different online servers. The both MEVs candidates were stable and free from aggregation-prone regions. The stability of both MEVs had been improved by a disulfide engineering approach. To estimate the binding energy and stability of the MEVs, molecular docking simulation and binding free energy calculations with TLR-4 immune receptor have been conducted. The docking score of PvCSP210 and PvCSP247 for TLR-4 was -6.34 kJ/mol and - 2.3 kJ/mol, respectively. For PvCSP210-TLR4 system, mean RMSD was 4.96 Å while PvCSP247-TLR4 system, average RMSD was 4.49 Å. The binding free energy of PvCSP210-TLR4 complex and PvCSP247-TLR4 complex was -50.49/-117.15 kcal/mol (MMGBSA/MMPSA) and -52.94/-96.26 kcal/mol (MMGBSA/MMPSA), respectively. The expression of both MEVs produced in Escherichia coli K12 expression system by in silico cloning was significant. Immune simulation revealed that the proposed MEVs induce strong humoral and cellular immunological responses, in addition to significant production of interleukins and cytokines. In conclusions, we believed that the MEVs proposed in current research, using combine approach of immunoinformatics, structural biology and biophysical approaches, could induce protective and effective immune responses against P. vivax and the experimental validation of our findings could contribute to the development of potential malaria vaccine.

Drugs repurposing against SARS-CoV2 and the new variant B.1.1.7 (alpha strain) targeting the spike protein: molecular docking and simulation studies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) is responsible for the global COVID-19 pandemic and millions of deaths worldwide. In December 2020, a new alpha strain of SARS-CoV2 was identified in the United Kingdom. It was referred to as VUI 202012/01 (Alpha strain modelled under investigation, 2020, month 12, number 01). The interaction between spike protein and ACE2 receptor is a prerequisite for entering virion into the host cell. The present study is focussed on the spike protein of the SARS-COV 2, involving the comparison of binding affinity of new alpha strain modelled spike with previous strain spike (PDB ID:7DDN) using in silico molecular docking, dynamics and simulation studies. The molecular docking studies of the alpha strain modelled spike protein confirmed its higher affinity for the ACE2 receptor than the spike protein of the dominant strain. Similar computational approaches have also been used to investigate the potency of FDA approved drugs from the ZINC Database against the spike protein of new alpha strain modelled and old ones. The drug molecules which showed strong affinity for both the spike proteins are then subjected to ADME analysis. The overall binding energy of Conivaptan (-107.503 kJ/mol) and Trosec (-94.029 kJ/mol) is indicative of their strong binding affinities, well supported by interactions with critical residues.

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We investigated the potential FDA drugs for repurposing against the spike protein of alpha strain modelled of SARS-CoV-2.

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Spike protein of alpha strain modelled of SARS-CoV-2 has more affinity for the ACE2 receptor of host cell than previous strains and, therefore, is more contagious.

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Conivaptan, Ecamsule and Trosec are common drugs that bind strongly with spike protein of both the strains .

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Molecular Docking and simulation studies show that Conivaptan and Trosec emerged as potential inhibitors of the alpha strain modelled spike protein.

An immunoinformatics study: designing multivalent T-cell epitope vaccine against canine circovirus

BACKGROUND

Canine circovirus is a deadly pathogen of dogs and causes vasculitis and hemorrhagic enteritis. It causes lethal gastroenteritis in pigs, fox, and dogs. Canine circovirus genome contains two main (and opposite) transcription units which encode two open reading frames (ORFs), a replicase-associated protein (Rep) and the capsid (Cap) protein. The replicase protein and capsid protein consist of 303 amino acids and 270 amino acids respectively. Several immuno-informatics methods such as epitope screening, molecular docking, and molecular-dynamics simulations were used to craft peptide-based vaccine construct against canine circovirus.

RESULTS

The vaccine construct was designed by joining the selected epitopes with adjuvants by suitable linker. The cloning and expression of the vaccine construct was also performed using in silico methods. Screening of epitopes was conducted by NetMHC server that uses ANN (Artificial neural networking) algorithm. These methods are fast and cost-effective for screening epitopes that can interact with dog leukocyte antigens (DLA) and initiate an immune response. Overall, 5 epitopes, YQHLPPFRF, YIRAKWINW, ALYRRLTLI, HLQGFVNLK, and GTMNFVARR, were selected and used to design a vaccine construct. The molecular docking and molecular dynamics simulation studies show that these epitopes can bind with DLA molecules with stability. The codon adaptation and in silico cloning studies show that the vaccine can be expressed by Escherichia coli K12 strain.

CONCLUSION

The results suggest that the vaccine construct can be useful in preventing the dogs from canine circovirus infections. However, the results need further validation by performing other in vitro and in vivo experiments.

Structural bioinformatics used to predict the protein targets of remdesivir and flavones in SARS-CoV-2 infection

BACKGROUND

During the current SARS-CoV-2 pandemic, the identification of effective antiviral drugs is crucial. Unfortunately, no specific treatment or vaccine is available to date.

OBJECTIVE

Here, we aimed to predict the interactions between SARS-CoV-2 proteins and protein targets from the human body for some flavone molecules (kaempferol, morin, pectolinarin, myricitrin, and herbacetin) in comparison to synthetic compounds (hydroxychloroquine, remdesivir, ribavirin, ritonavir, AMD-070, favipiravir).

METHODS

Using MOE software and advanced bioinformatics and cheminformatics portals, we conducted an extensive analysis based on various structural and functional features of compounds, such as their amphiphilic field, flexibility, and steric features. The structural similarity analysis of natural and synthetic compounds was performed using Tanimoto coefficients. The interactions of some compounds with SARS-CoV-2 3CLprotease or RNA-dependent RNA polymerase were described using 2D protein-ligand interaction diagrams based on known crystal structures. The potential targets of considered compounds were identified using the SwissTargetPrediction web tool.

RESULTS

Our results showed that remdesivir, pectolinarin, and ritonavir present a strong structural similarity which may be correlated to their similar biological activity. As common molecular targets of compounds in the human body, ritonavir, kaempferol, morin, and herbacetin can activate multidrug resistance-associated proteins, while remdesivir, ribavirin, and pectolinarin appear as ligands for adenosine receptors.

CONCLUSION

Our evaluation recommends remdesivir, pectolinarin, and ritonavir as promising anti-SARS-CoV-2 agents.

The use of negative oxygen ion clusters [O2-(H2O)n] and bicarbonate ions [HCO3-] as the supportive treatment of COVID-19 infections: A possibility

The COVID-19 or novel coronavirus SARS-CoV-2 pandemic is challenging worldwide healthcare system and severely affecting global economy. Furious efforts to end the pandemic including prevention of spread of SARS-CoV-2, use of antiviral drugs, symptomatic treatments and vaccination are underway. But there are no effective treatments available to save the dying patient in stage 2 (pulmonary) and stage 3 (hyperinflammation) of the infection. The detailed genetic and phenotypical analysis of SARS-CoV-2 revealed that the spike protein (S1) has increased positive charges (compared to SARS-CoV) on them and are responsible for attachment to human angiotensin-converting enzyme 2 (ACE2) receptor and infection by the virus. In addition, it was also reported that the inflammation in the tissue rendered the lung environment more acidic supporting the fusion of SARS-CoV-2 with the cells. We hypothesize that the intermittent use of the oxygen ionizer generating negative oxygen ion clusters [O₂^-(H₂O)_n] and sodium bicarbonate nebulizer (generating HCO₃^-); when connected to ventilator inlet or oxygen concentrator will neutralize the spike protein of the virus in respiratory tract and lungs and change the lung environment to neutral/alkaline condition respectively facilitating improved oxygen pressure in blood. These physical changes can effectively reduce the viral burden and help the patient recover from the infection faster.

nCOV-19 peptides mass fingerprinting identification, binding, and blocking of inhibitors flavonoids and anthraquinone of Moringa oleifera and hydroxychloroquine

An rare pandemic of viral pneumonia occurs in December 2019 in Wuhan, China, which is now recognized internationally as Corona Virus Disease 2019 (COVID-19), the etiological agent classified as Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2). According to the World Health Organization (WHO), it has so far expanded to more than 213 countries/territories worldwide. Our study aims to find the viral peptides of SARS-COV-2 by peptide mass fingerprinting (PMF) in order to predict its novel structure and find an inhibitor for each viral peptide. For this reason, we calculated the mass of amino acid sequences translated from the SARS-CoV2 whole genome and identify the peptides that may be a target for inhibition. Molecular peptide docking with Moringa oleifera, phytochemicals (aqueous and ethanolic) leaf extracts of flavonoids (3.56 ± 0.03), (3.83 ± 0.02), anthraquinone (11.68 ± 0.04), (10.86 ± 0.06) and hydroxychloroquine present therapy of COVID-19 in Pakistan for comparative study. Results indicate that 15 peptides of SARS-CoV2 have been identified from PMF, which is then used as a selective inhibitor. The maximum energy obtained from AutoDock Vina for hydroxychloroquine is -5.1 kcal/mol, kaempferol (flavonoid) is -6.2 kcal/mol, and for anthraquinone -6 kcal/mol. Visualization of docking complex, important effects are observed regarding the binding of peptides to drug compounds. In conclusion, it is proposed that these compounds are effective antiviral agents against COVID-19 and can be used in clinical trials.Communicated by Ramaswamy H. Sarma.