Multiple epitope-based vaccine prediction against SARS-CoV-2 spike glycoprotein

Bioinformatics approach for structure modeling, vaccine design, and molecular docking of Brucella candidate proteins BvrR, OMP25, and OMP31

Brucellosis is a zoonotic disease with significant economic and healthcare costs. Despite the eradication efforts, the disease persists. Vaccines prevent disease in animals while antibiotics cure humans with limitations. This study aims to design vaccines and drugs for brucellosis in animals and humans, using protein modeling, epitope prediction, and molecular docking of the target proteins (BvrR, OMP25, and OMP31). Tertiary structure models of three target proteins were constructed and assessed using RMSD, TM-score, C-score, Z-score, and ERRAT. The best models selected from AlphaFold and I-TASSER due to their superior performance according to CASP 12 - CASP 15 were chosen for further analysis. The motif analysis of best models using MotifFinder revealed two, five, and five protein binding motifs, however, the Motif Scan identified seven, six, and eight Post-Translational Modification sites (PTMs) in the BvrR, OMP25, and OMP31 proteins, respectively. Dominant B cell epitopes were predicted at (44-63, 85-93, 126-137, 193-205, and 208-237), (26-46, 52-71, 98-114, 142-155, and 183-200), and (29-45, 58-82, 119-142, 177-198, and 222-251) for the three target proteins. Additionally, cytotoxic T lymphocyte epitopes were detected at (173-181, 189-197, and 202-210), (61-69, 91-99, 159-167, and 181-189), and (3-11, 24-32, 167-175, and 216-224), while T helper lymphocyte epitopes were displayed at (39-53, 57-65, 150-158, 163-171), (79-87, 95-108, 115-123, 128-142, and 189-197), and (39-47, 109-123, 216-224, and 245-253), for the respective target protein. Furthermore, structure-based virtual screening of the ZINC and DrugBank databases using the docking MOE program was followed by ADMET analysis. The best five compounds of the ZINC database revealed docking scores ranged from (- 16.8744 to - 15.1922), (- 16.0424 to - 14.1645), and (- 14.7566 to - 13.3222) for the BvrR, OMP25, and OMP31, respectively. These compounds had good ADMET parameters and no cytotoxicity, while DrugBank compounds didn't meet Lipinski's rule criteria. Therefore, the five selected compounds from the ZINC20 databases may fulfill the pharmacokinetics and could be considered lead molecules for potentially inhibiting Brucella's proteins.

Immunoinformatics aided designing of a next generation poly-epitope vaccine against uropathogenic Escherichia coli to combat urinary tract infections

Urinary tract infections (UTIs) are the second most prevalent bacterial infections and uropathogenic Escherichia coli (UPEC) stands among the primary causative agents of UTIs. The usage of antibiotics is the routine therapy being used in various countries to treat UTIs but becoming ineffective because of increasing antibiotic resistance among UPEC strains. Thus, there must be the development of some alternative treatment strategies such as vaccine development against UPEC. In the following study, pan-genomics along with reverse vaccinology approaches is used under the framework of bioinformatics for the identification of core putative vaccine candidates, employing 307 UPEC genomes (complete and draft), available publicly. A total of nine T-cell epitopes (derived from B-cells) of both MHC classes (I and II), were prioritized among three potential protein candidates. These epitopes were then docked together by using linkers (GPGPG and AAY) and an adjuvant (Cholera Toxin B) to form a poly-valent vaccine construct. The chimeric vaccine construct was undergone by molecular modelling, further refinement and energy minimization. We predicted positive results of the vaccine construct in immune simulations with significantly high levels of immune cells. The protein-protein docking analysis of vaccine construct with toll-like receptors predicted efficient binding, which was further validated by molecular dynamics simulation of vaccine construct with TLR-2 and TLR-4 at 120 ns, resulting in stable complexes' conformation throughout the simulation run. Overall, the vaccine construct demonstrated positive antigenic response. In future, this chimeric vaccine construct or the identified epitopes could be experimentally validated for the development of UPEC vaccines against UTIs.Communicated by Ramaswamy H. Sarma.

Immunoinformatics Approaches for Vaccine Design: A Fast and Secure Strategy for Successful Vaccine Development

Vaccines are major contributors to the cost-effective interventions in major infectious diseases in the global public health space [...].

Detection of the peptidyl epitope for vaccine development against MPV

Background

Monkeypox Virus (MPV) is the cause of zoonotic disease characterized by skin-eruption with pus cell formation and lymphadenopathy. This virus belongs to the Orthopoxvirus genus with DNA as its genetic material. Previously, this infection was reported from Africa and occasionally from USA and UK. However, recently there is a sudden surge of infection in non-epidemic countries and a new strain of MPVhas been discovered. Therefore it is important to revisit the phylogeny of MPV with the addition of new strains. Recently WHO also stressed the need of developing vaccines for new strains. In this scenario we have two objectives for this study -first, to reveal the exact phylogenetic position of the 2022 strain and second, to identify specific peptides which may be used for vaccine development in the future.

Methods

The phylogenetic analysis was done with the help of Bayesian phylogeny. The dN/dS calculation was performed based on DNA polymerase genes of selected MPV strains. The peptidyl-epitope was searched in MPV2022/2 SLO strain with the help of several algorithms implemented in Allergen FP v.1.0, NetMHCII 2.3, MHCpred and Toxin Pred. The structure prediction of the proteins and peptides was performed through Hpepdock. The quality of the structures was validated through the Ramachandran plot. The molecular dynamics and simulation were performed through Gromacs software. The interaction between peptide and protein was assessed through Ligplot software.

Results

The phylogenetic analysis revealed that the considered 2022 MPVstrains were close to the USA strains. The evolutionary analysis showed the volatile nature of the genome. Moreover, 9-mer peptide sequence was identified as an epitope for vaccine development.

Conclusions

The emergence of more virulent strains in near future may not be ruled out. Immunocompromised patients are more susceptible to this virus hence sub-unit vaccine is a better choice than a recombinant or attenuated vaccine against monkeypox. We have identified a small stretch of specific peptide which may be used for developing a subunit vaccine against this virus.

Immunoinformatic approach employing modeling and simulation to design a novel vaccine construct targeting MDR efflux pumps to confer wide protection against typhoidal Salmonella serovars

Overcoming multi drug resistance is one of the crucial challenges to control enteric typhoid fever caused by Salmonella typhi and Salmonella paratyphi. Overexpression of efflux pumps predominantly causes drug resistance in microorganisms. Therefore, immunotherapy targeting the various efflux pumps antigens could be a promising strategy to increase the success of vaccines. An immunoinformatic approach was employed to design a Salmonellosis multi-epitope subunit vaccine peptide consisting of linear B-cell and T-cell epitopes of multidrug resistance protein families including ATP Binding Cassette (ABC), major facilitator superfamily (MFS), resistance nodulation cell division (RND), small multidrug resistance (SMR), and multidrug and toxin extrusion (MATE). The selected epitopes exhibited conservation in both S. typhi and S. paratyphi and thus could be helpful for cross-protection. Further, the final vaccine construct encompassing the peptides, adjuvants and specific linker sequences showed high immunogenicity, solubility, non-allergenic, nontoxic, and wide population coverage due to strong binding affinity to maximum HLA alleles. The three-dimensional structure was predicted, and validated using various structure validation tools. Additionally, protein-protein docking of the chimeric vaccine construct with the TLR-2 protein and molecular dynamics demonstrated stable and efficient binding. Conclusively, the immunoinformatic study showed that the novel multi epitopic vaccine construct can simulate the both T-cell and B-cell immune responses in typhoidal Salmonella serovars and could potentially be used for prophylactic or therapeutic applications.Communicated by Ramaswamy H. Sarma.

SARS-CoV-2 subunit vaccine adjuvants and their signaling pathways

INTRODUCTION

Vaccines are the agreed upon weapon against the COVID-19 pandemic. This review discusses about COVID-19 subunit vaccines adjuvants and their signaling pathways, which could provide a glimpse into the selection of appropriate adjuvants for prospective vaccine development studies.

AREAS COVERED

In the introduction, a brief background about the SARS-CoV-2 pandemic, the vaccine development race and classes of vaccine adjuvants were provided. . The antigen, trial stage, and types of adjuvants were extracted from the included articles and thun assimilated. Finally, the pattern recognition receptors (PRRs), their classes, cognate adjuvants, and potential signaling pathways were comprehended.

EXPERT OPINION

Adjuvants are unsung heroes of subunit vaccines. The in silico studies are very vital in avoiding several costly trial errors and save much work times. The majority of the (pre)clinical studies are promising. It is encouraging that most of the selected adjuvants are novel. Much emphasis must be paid to the optimal paring of antigen-adjuvant-PRRs for obtaining the desired vaccine effect. A good subunit vaccine/adjuvant is one that has high efficacy, safety, dose sparing, and rapid seroconversion rate and broad spectrum of immune response. In the years to come, COVID-19 adjuvanted subunit vaccines are expected to have superior utility than any other vaccines for various reasons.

In Silico Modeling as a Perspective in Developing Potential Vaccine Candidates and Therapeutics for COVID-19

The potential of computational models to identify new therapeutics and repurpose existing drugs has gained significance in recent times. The current ‘COVID-19’ pandemic caused by the new SARS CoV2 virus has affected over 200 million people and caused over 4 million deaths. The enormity and the consequences of this viral infection have fueled the research community to identify drugs or vaccines through a relatively expeditious process. The availability of high-throughput datasets has cultivated new strategies for drug development and can provide the foundation towards effective therapy options. Molecular modeling methods using structure-based or computer-aided virtual screening can potentially be employed as research guides to identify novel antiviral agents. This review focuses on in-silico modeling of the potential therapeutic candidates against SARS CoVs, in addition to strategies for vaccine design. Here, we particularly focus on the recently published SARS CoV main protease (Mpro) active site, the RNA-dependent RNA polymerase (RdRp) of SARS CoV2, and the spike S-protein as potential targets for vaccine development. This review can offer future perspectives for further research and the development of COVID-19 therapies via the design of new drug candidates and multi-epitopic vaccines and through the repurposing of either approved drugs or drugs under clinical trial.

Vaccinomics: a future avenue for vaccine development against emerging pathogens

INTRODUCTION

Vaccines are a major achievement in medical sciences, but the development of more effective vaccines against infectious diseases is essential for prevention and control of emerging pathogens worldwide. The application of omics technologies has advanced vaccinology through the characterization of host-vector-pathogen molecular interactions and the identification of candidate protective antigens. However, major challenges such as host immunity, pathogen and environmental factors, vaccine efficacy and safety need to be addressed. Vaccinomics provides a platform to address these challenges and improve vaccine efficacy and safety.

AREAS COVERED

In this review, we summarize current information on vaccinomics and propose quantum vaccinomics approaches to further advance vaccine development through the identification and combination of antigen protective epitopes, the immunological quantum. The COVID-19 pandemic caused by SARS-CoV-2 is an example of emerging infectious diseases with global impact on human health.

EXPERT OPINION

Vaccines are required for the effective and environmentally sustainable intervention for the control of emerging infectious diseases worldwide. Recent advances in vaccinomics provide a platform to address challenges in improving vaccine efficacy and implementation. As proposed here, quantum vaccinomics will contribute to vaccine development, efficacy, and safety by facilitating antigen combinations to target pathogen infection and transmission in emerging infectious diseases.

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.