Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

Development of membrane protein-based vaccine against lumpy skin disease virus (LSDV) using immunoinformatic tools

INTRODUCTION

Lumpy skin disease, an economically significant bovine illness, is now found in previously unheard-of geographic regions. Vaccination is one of the most important ways to stop its further spread.

AIM

Therefore, in this study, we applied advanced immunoinformatics approaches to design and develop an effective lumpy skin disease virus (LSDV) vaccine.

METHODS

The membrane glycoprotein was selected for prediction of the different B- and T-cell epitopes by using the immune epitope database. The selected B- and T-cell epitopes were combined with the appropriate linkers and adjuvant resulted in a vaccine chimera construct. Bioinformatics tools were used to predict, refine and validate the 2D, 3D structures and for molecular docking with toll-like receptor 4 using different servers. The constructed vaccine candidate was further processed on the basis of antigenicity, allergenicity, solubility, different physiochemical properties and molecular docking scores.

RESULTS

The in silico immune simulation induced significant response for immune cells. In silico cloning and codon optimization were performed to express the vaccine candidate in Escherichia coli. This study highlights a good signal for the design of a peptide-based LSDV vaccine.

CONCLUSION

Thus, the present findings may indicate that the engineered multi-epitope vaccine is structurally stable and can induce a strong immune response, which should help in developing an effective vaccine towards controlling LSDV infection.

Structural and Dynamic-Based Characterization of the Recognition Patterns of E7 and TRP-2 Epitopes by MHC Class I Receptors through Computational Approaches

A detailed comprehension of MHC-epitope recognition is essential for the design and development of new antigens that could be effectively used in immunotherapy. Yet, the high variability of the peptide together with the large abundance of MHC variants binding makes the process highly specific and large-scale characterizations extremely challenging by standard experimental techniques. Taking advantage of the striking predictive accuracy of AlphaFold, we report a structural and dynamic-based strategy to gain insights into the molecular basis that drives the recognition and interaction of MHC class I in the immune response triggered by pathogens and/or tumor-derived peptides. Here, we investigated at the atomic level the recognition of E7 and TRP-2 epitopes to their known receptors, thus offering a structural explanation for the different binding preferences of the studied receptors for specific residues in certain positions of the antigen sequences. Moreover, our analysis provides clues on the determinants that dictate the affinity of the same epitope with different receptors. Collectively, the data here presented indicate the reliability of the approach that can be straightforwardly extended to a large number of related systems.

Immunodominant conserved moieties on spike protein of SARS-CoV-2 renders virulence factor for the design of epitope-based peptide vaccines

The outbreak of novel SARS-CoV-2 virion has wreaked havoc with a high prevalence of respiratory illness and high transmission due to a vague understanding of the viral antigenicity, augmenting the dire challenge to public health globally. This viral member necessitates the expansion of diagnostic and therapeutic tools to track its transmission and confront it through vaccine development. Therefore, prophylactic strategies are mandatory. Virulent spike proteins can be the most desirable candidate for the computational design of vaccines targeting SARS-CoV-2, followed by the meteoric development of immune epitopes. Spike protein was characterized using existing bioinformatics tools with a unique roadmap related to the immunological profile of SARS-CoV-2 to predict immunogenic virulence epitopes based on antigenicity, allergenicity, toxicity, immunogenicity, and population coverage. Applying in silico approaches, a set of twenty-four B lymphocyte-based epitopes and forty-six T lymphocyte-based epitopes were selected. The predicted epitopes were evaluated for their intrinsic properties. The physico-chemical characterization of epitopes qualifies them for further in vitro and in vivo analysis and pre-requisite vaccine development. This study presents a set of screened epitopes that bind to HLA-specific allelic proteins and can be employed for designing a peptide vaccine construct against SARS-CoV-2 that will confer vaccine-induced protective immunity due to its structural stability.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-023-00852-9.

Design and computational analysis of an effective multi-epitope vaccine candidate using subunit B of cholera toxin as a build-in adjuvant against urinary tract infections

Introduction

Urinary tract infection (UTI) is one of the most common infections, usually caused by uropathogenic Escherichia coli (UPEC). However, antibiotics are a usual treatment for UTIs; because of increasing antibiotic-resistant strains, vaccination can be beneficial in controlling UTIs. Using immunoinformatics techniques is an effective and rapid way for vaccine development.

Methods

Three conserved protective antigens (FdeC, Hma, and UpaB) were selected to develop a novel multi-epitope vaccine consisting of subunit B of cholera toxin (CTB) as a mucosal build-in adjuvant to enhance the immune responses. Epitopes-predicted B and T cells and suitable linkers were used to separate them and effectively increase the vaccine's immunogenicity. The vaccine protein's primary, secondary, and tertiary structures were evaluated, and the best 3D model was selected. Since CTB is the TLR2 ligand, molecular docking was made between the vaccine protein and TLR2. Molecular dynamic (MD) simulation was employed to evaluate the stability of the vaccine protein-TLR2 complex. The vaccine construct was subjected to in silico cloning.

Results

The designed vaccine protein has multiple properties in the analysis. The HADDOCK outcomes show an excellent interaction between vaccine protein and TLR2. The MD results confirm the stability of the vaccine protein- TLR2 complex during the simulation. In silico cloning verified the expression efficiency of our vaccine protein.

Conclusion

The results of this study suggest that our designed vaccine protein could be a promising vaccine candidate against UTI, but further in vitro and in vivo studies are needed.

Modeling of MT. P495, an mRNA-based vaccine against the phosphate-binding protein PstS1 of Mycobacterium tuberculosis

Tuberculosis (TB) is a contagious disease that predominantly affects the lungs, but can also spread to other organs via the bloodstream. TB affects about one-fourth population of the world. With age, the effectiveness of Bacillus Calmette-Guérin (BCG), the only authorized TB vaccine, decreases. In the quest for a prophylactic and immunotherapeutic vaccine, in this study, a hypothetical mRNA vaccine is delineated, named MT. P495, implementing in silico and immunoinformatics approaches to evaluate key aspects and immunogenic epitopes across the PstS1, a highly conserved periplasmic protein of Mycobacterium tuberculosis (Mtb). PstS1 elicited the potential to generate 99.9% population coverage worldwide. The presence of T- and B-cell epitopes across the PstS1 protein were validated using several computational prediction tools. Molecular docking and dynamics simulation confirmed stable epitope-allele interaction. Immune cell response to the antigen clearance rate was verified by the in silico analysis of immune simulation. Codon optimization confirmed the efficient translation of the mRNA in the host cell. With Toll-like receptors, the vaccine exhibited stable and strong interactions. Findings suggest that the MT. P495 vaccine probably will elicit specific immune responses against Mtb. This mRNA vaccine model is a ready source for further wet-lab validation to confirm the efficacy of this proposed vaccine candidate.

Peptide Vaccines as Therapeutic and Prophylactic Agents for Female-Specific Cancers: The Current Landscape

Breast and gynecologic cancers are significant global threats to women's health and those living with the disease require lifelong physical, financial, and social support from their families, healthcare providers, and society as a whole. Cancer vaccines offer a promising means of inducing long-lasting immune response against the disease. Among various types of cancer vaccines available, peptide vaccines offer an effective strategy to elicit specific anti-tumor immune responses. Peptide vaccines have been developed based on tumor associated antigens (TAAs) and tumor specific neoantigens which can also be of viral origin. Molecular alterations in HER2 and non-HER2 genes are established to be involved in the pathogenesis of female-specific cancers and hence were exploited for the development of peptide vaccines against these diseases, most of which are in the latter stages of clinical trials. However, prophylactic vaccines for viral induced cancers, especially those against Human Papillomavirus (HPV) infection are well established. This review discusses therapeutic and prophylactic approaches for various types of female-specific cancers such as breast cancer and gynecologic cancers with special emphasis on peptide vaccines. We also present a pipeline for the design and evaluation of a multiepitope peptide vaccine that can be active against female-specific cancers.

In silico designing and immunoinformatics analysis of a novel peptide vaccine against metallo-beta-lactamase (VIM and IMP) variants

The rapid spread of acquired metallo-beta-lactamases (MBLs) among gram negative pathogens is becoming a global concern. Improper use of broad-spectrum antibiotics can trigger the colonization and spread of resistant strains which lead to increased mortality and significant economic loss. In the present study, diverse immunoinformatic approaches are applied to design a potential epitope-based vaccine against VIM and IMP MBLs. The amino acid sequences of VIM and IMP variants were retrieved from the GenBank database. ABCpred and BCPred online Web servers were used to analyze linear B cell epitopes, while IEDB was used to determine the dominant T cell epitopes. Sequence validation, allergenicity, toxicity and physiochemical analysis were performed using web servers. Seven sequences were identified for linear B cell dominant epitopes and 4 sequences were considered as dominant CD4+ T cell epitopes, and the predicted epitopes were joined by KK and GPGPG linkers. Stabilized multi-epitope protein structure was obtained using molecular dynamics simulation. Molecular docking showed that the designed vaccine exhibited sustainable and strong binding interactions with Toll-like receptor 4 (TLR4). Finally, codon adaptation and in silico cloning studies were performed to design an effective vaccine production strategy. Immune simulation significantly provided high levels of immunoglobulins, T helper cells, T-cytotoxic cells and INF-γ. Even though the introduced vaccine candidate demonstrates a very potent immunogenic potential, but wet-lab validation is required to further assessment of the effectiveness of this proposed vaccine candidate.

Construction, Expression, and Evaluation of the Naturally Acquired Humoral Immune Response against Plasmodium vivax RMC-1, a Multistage Chimeric Protein

The PvCelTOS, PvCyRPA, and Pvs25 proteins play important roles during the three stages of the P. vivax lifecycle. In this study, we designed and expressed a P. vivax recombinant modular chimeric protein (PvRMC-1) composed of the main antigenic regions of these vaccine candidates. After structure modelling by prediction, the chimeric protein was expressed, and the antigenicity was assessed by IgM and IgG (total and subclass) ELISA in 301 naturally exposed individuals from the Brazilian Amazon. The recombinant protein was recognized by IgG (54%) and IgM (40%) antibodies in the studied individuals, confirming the natural immunogenicity of the epitopes that composed PvRMC-1 as its maintenance in the chimeric structure. Among responders, a predominant cytophilic response mediated by IgG1 (70%) and IgG3 (69%) was observed. IgM levels were inversely correlated with age and time of residence in endemic areas (p < 0.01). By contrast, the IgG and IgM reactivity indexes were positively correlated with each other, and both were inversely correlated with the time of the last malaria episode. Conclusions: The study demonstrates that PvRMC-1 was successfully expressed and targeted by natural antibodies, providing important insights into the construction of a multistage chimeric recombinant protein and the use of naturally acquired antibodies to validate the construction.

Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins

The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies in silico. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body.Communicated by Ramaswamy H. Sarma.

A subunit vaccine against pneumonia: targeting Streptococcus pneumoniae and Klebsiella pneumoniae

Community-acquired pneumonia is primarily caused by Streptococcus pneumoniae and Klebsiella pneumoniae, two pathogens that have high morbidity and mortality rates. This is largely due to bacterial resistance development against current antibiotics and the lack of effective vaccines. The objective of this work was to develop an immunogenic multi-epitope subunit vaccine capable of eliciting a robust immune response against S. pneumoniae and K. pneumoniae. The targeted proteins were the pneumococcal surface proteins (PspA and PspC) and choline-binding protein (CbpA) of S. pneumoniae and the outer membrane proteins (OmpA and OmpW) of K. pneumoniae. Different computational approaches and various immune filters were employed for designing a vaccine. The immunogenicity and safety of the vaccine were evaluated by utilizing many physicochemical and antigenic profiles. To improve structural stability, disulfide engineering was applied to a portion of the vaccine structure with high mobility. Molecular docking was performed to examine the binding affinities and biological interactions at the atomic level between the vaccine and Toll-like receptors (TLR2 and 4). Further, the dynamic stabilities of the vaccine and TLRs complexes were investigated by molecular dynamics simulations. While the immune response induction capability of the vaccine was assessed by the immune simulation study. Vaccine translation and expression efficiency was determined through an in silico cloning experiment utilizing the pET28a(+) plasmid vector. The obtained results revealed that the designed vaccine is structurally stable and able to generate an effective immune response to combat pneumococcal infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13721-023-00416-3.

Governing HPV-related carcinoma using vaccines: Bottlenecks and breakthroughs

Human papillomavirus (HPV) contributes to sexually transmitted infection, which is primarily associated with pre-cancerous and cancerous lesions in both men and women and is among the neglected cancerous infections in the world. At global level, two-, four-, and nine-valent pure L1 protein encompassed vaccines in targeting high-risk HPV strains using recombinant DNA technology are available. Therapeutic vaccines are produced by early and late oncoproteins that impart superior cell immunity to preventive vaccines that are under investigation. In the current review, we have not only discussed the clinical significance and importance of both preventive and therapeutic vaccines but also highlighted their dosage and mode of administration. This review is novel in its way and will pave the way for researchers to address the challenges posed by HPV-based vaccines at the present time.

Designing a Multi-Epitope Vaccine against Toxoplasma gondii: An Immunoinformatics Approach

Infection with the intracellular apicomplexan parasite Toxoplasma gondii causes serious clinical outcomes in both human and veterinary settings worldwide. Although approximately one-third of the world’s population is infected with T. gondii, an effective human vaccine for this disease remains unavailable. We aimed to design a potential T. gondii vaccine candidate that consisted of the B- and T-lymphocyte epitopes of three parasite immunogenic antigens. Firstly, the immunodominant epitopes expressed within the ROP2, MIC3, and GRA7 proteins of T. gondii were identified. Subsequently, six B-cell epitopes, five CTL epitopes, and five HTL epitopes were combined to generate a multi-epitope vaccine, and the 50S ribosomal protein L7/L12 was added as an adjuvant to boost the vaccine’s immunogenicity. All these epitopes were found to be antigenic, nonallergenic, nontoxic, and nonhuman homologs. The designed vaccine construct has a molecular weight of 51 kDa, an antigenicity score of 0.6182, and a solubility of 0.903461. Likewise, the candidate vaccine was immunogenic, nonallergenic, and stable. Molecular docking analysis revealed stable interactions between the vaccine construct and the TLR-4 immune receptor. Meanwhile, the stability of the developed vaccine was validated using molecular dynamics simulation. In silico, the vaccine construct was able to trigger primary immune responses. However, further laboratory-based assessments are needed to confirm its efficacy and safety.

Immunoinformatics-Aided Analysis of RSV Fusion and Attachment Glycoproteins to Design a Potent Multi-Epitope Vaccine

Respiratory syncytial virus (RSV) usually causes respiratory tract infections of upper airways in infants and young children. Despite recent medical advances, no approved vaccine is available to control RSV infections. Therefore, we conducted an immunoinformatics study to design and evaluate a potential multi-epitope vaccine against RSV. Sequence-based analyses of the glycoproteins F and G revealed a total of eight CD8 T-cell and three CD4 T-cell epitopes after considering antigenicity, binding affinity and other parameters. Molecular docking analysis confirmed that these T-cell epitopes developed strong structural associations with HLA allele(s). By integrating these prioritized epitopes with linkers and a cholera toxin-derived adjuvant, a multi-epitope vaccine was designed. The developed vaccine was found to be stable, non-allergenic, flexible and antigenic. Molecular docking analysis revealed a striking mean HADDOCK score (−143.3) of top-ranked vaccine-TLR cluster and a Gibbs free energy change (ΔG) value of −11.3 kcal mol−1. As per computational immune simulation results, the vaccine generated a high titer of antibodies (especially IgM) and effector T-cells. Also, codon optimization and in silico cloning ensured the increased expression of vaccine in Escherichia coli. Altogether, we anticipate that the multi-epitope vaccine reported in this study will stimulate humoral and cellular responses against RSV infection, subject to follow-up experimental validation.

In silico design of a multi-epitope vaccine against HPV16/18

BACKGROUND

Cervical cancer is the fourth most common cancer affecting women and is caused by human Papillomavirus (HPV) infections that are sexually transmitted. There are currently commercially available prophylactic vaccines that have been shown to protect vaccinated individuals against HPV infections, however, these vaccines have no therapeutic effects for those who are previously infected with the virus. The current study's aim was to use immunoinformatics to develop a multi-epitope vaccine with therapeutic potential against cervical cancer.

RESULTS

In this study, T-cell epitopes from E5 and E7 proteins of HPV16/18 were predicted. These epitopes were evaluated and chosen based on their antigenicity, allergenicity, toxicity, and induction of IFN-γ production (only in helper T lymphocytes). Then, the selected epitopes were sequentially linked by appropriate linkers. In addition, a C-terminal fragment of Mycobacterium tuberculosis heat shock protein 70 (HSP70) was used as an adjuvant for the vaccine construct. The physicochemical parameters of the vaccine construct were acceptable. Furthermore, the vaccine was soluble, highly antigenic, and non-allergenic. The vaccine's 3D model was predicted, and the structural improvement after refinement was confirmed using the Ramachandran plot and ProSA-web. The vaccine's B-cell epitopes were predicted. Molecular docking analysis showed that the vaccine's refined 3D model had a strong interaction with the Toll-like receptor 4. The structural stability of the vaccine construct was confirmed by molecular dynamics simulation. Codon adaptation was performed in order to achieve efficient vaccine expression in Escherichia coli strain K12 (E. coli). Subsequently, in silico cloning of the multi-epitope vaccine was conducted into pET-28a ( +) expression vector.

CONCLUSIONS

According to the results of bioinformatics analyses, the multi-epitope vaccine is structurally stable, as well as a non-allergic and non-toxic antigen. However, in vitro and in vivo studies are needed to validate the vaccine's efficacy and safety. If satisfactory results are obtained from in vitro and in vivo studies, the vaccine designed in this study may be effective as a therapeutic vaccine against cervical cancer.

PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling

Background

Computational methods based on initial screening and prediction of peptides for desired functions have proven to be effective alternatives to lengthy and expensive biochemical experimental methods traditionally utilized in peptide research, thus saving time and effort. However, for many researchers, the lack of expertise in utilizing programming libraries, access to computational resources, and flexible pipelines are big hurdles to adopting these advanced methods.

Results

To address the above mentioned barriers, we have implemented the peptide design and analysis under Galaxy (PDAUG) package, a Galaxy-based Python powered collection of tools, workflows, and datasets for rapid in-silico peptide library analysis. In contrast to existing methods like standard programming libraries or rigid single-function web-based tools, PDAUG offers an integrated GUI-based toolset, providing flexibility to build and distribute reproducible pipelines and workflows without programming expertise. Finally, we demonstrate the usability of PDAUG in predicting anticancer properties of peptides using four different feature sets and assess the suitability of various ML algorithms.

Conclusion

PDAUG offers tools for peptide library generation, data visualization, built-in and public database peptide sequence retrieval, peptide feature calculation, and machine learning (ML) modeling. Additionally, this toolset facilitates researchers to combine PDAUG with hundreds of compatible existing Galaxy tools for limitless analytic strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04727-6.

Prediction and evaluation of multi epitope based sub-unit vaccine against Salmonella typhimurium

Salmonella enteric serovar Typhimurium is the most common enteric pathogen in humans and animals. Consumption of contaminated food or water triggers inflammation that allows Salmonella to spread into the gut and causes gastrointestinal diseases. The infection spreads by intestinal invasion, phagocyte internalization and subsequent dissemination in many other patients. This research used TolA, a Salmonella typhimurium membrane protein, to computationally design a multi-epitope vaccine against the pathogen. Complete consistency of the candidate vaccine was checked In silico, and molecular dynamics simulations confirmed the vaccine's stability. According to docking report, the vaccine has a good affinity with toll-like receptors. In silico cloning and codon optimization techniques improved the vaccine's efficacy in Salmonella typhimurium manifestation process. The candidate vaccine induced an efficient immune response, as determined by In silico immune simulation. Computational studies revealed that the engineered multi-epitope vaccine is structurally stable, capable of eliciting particular immunological reactions, and therefore a candidate for a latent Salmonella typhimurium vaccine. However, wet lab studies and further investigations are required to confirm the results.

Genetic variability of the HPV16 early genes and LCR. Present and future perspectives

Human papillomavirus 16 (HPV16) infection is the aetiologic factor for the development of cervical dysplasia and is regarded as highly carcinogen, because it is implicated in more than 50% of cervical cancer cases, worldwide. The tumourigenic potential of HPV16 has triggered the extensive sequence analysis of viral genome in order to identify nucleotide variations and amino acid substitutions that influence viral oncogenicity and subsequently the initiation and progression of cervical cancer. Nowadays, specific mutations of HPV16 DNA have been associated with an increased risk of high-grade squamous intraepithelial lesions and invasive cervical cancer (ICC) development, including E6: Q14H, H78Y, L83V, Ε7: N29S, S63F, E2: H35Q, P219S, T310K, E5: I65V, whereas highly conserved regions of viral DNA have been extensively characterised. In addition, numerous novel HPV16 mutations are observed among the studied populations from various geographic regions, hence advocating that different HPV16 strains seem to emerge with different tumourigenic capacities. The present review focuses on the variability of the early genes and the long control region, emphasising on the association of specific mutations with the development of severe dysplasia. Finally, it evaluates whether specific regions of HPV16 DNA are able to serve as valuable biomarkers for cervical cancer risk.

A Computational Reverse Vaccinology Approach for the Design and Development of Multi-Epitopic Vaccine Against Avian Pathogen Mycoplasma gallisepticum

Avian mycoplasma is a bacterial disease causing chronic respiratory disease (CRD) in poultry industries with high economic losses. The eradication of this disease still remains as a challenge. A multi-epitope prophylactic vaccine aiming the antigenic proteins of Mycoplasma gallisepticum can be a capable candidate to eradicate this infection. The present study is focused to design a multi-epitope vaccine candidate consisting of cytotoxic T-cell (CTL), helper T-cell (HTL), and B-cell epitopes of antigenic proteins, using immunoinformatics strategies. The multi-epitopic vaccine was designed, and its tertiary model was predcited, which was further refined and validated by computational tools. After initial validation, molecular docking was performed between multi-epitope vaccine construct and chicken TLR-2 and 5 receptors, which predicted effective binding. The in silico results specify the structural stability, precise specificity, and immunogenic response of the designed multi-epitope vaccine, and it could be an appropriate vaccine candidate for the M. gallisepticum infection.

Synergistic effects of exosomal crocin or curcumin compounds and HPV L1-E7 polypeptide vaccine construct on tumor eradication in C57BL/6 mouse model

Cervical cancer is the most common malignant tumor in females worldwide. Human papillomavirus (HPV) infection is associated with the occurrence of cervical cancer. Thus, developing an effective and low-cost vaccine against HPV infection, especially in developing countries is an important issue. In this study, a novel HPV L1-E7 fusion multiepitope construct designed by immunoinformatics tools was expressed in bacterial system. HEK-293T cells-derived exosomes were generated and characterized to use as a carrier for crocin and curcumin compounds. The exosomes loaded with crocin and curcumin compounds as a chemotherapeutic agent (ExoCrocin and ExoCurcumin) were used along with the L1-E7 polypeptide for evaluation of immunological and anti-tumor effects in C57BL/6 mouse model. In vitro studies showed that ExoCrocin and ExoCurcumin were not cytotoxic at a certain dose, and they could enter tumor cells. In vivo studies indicated that combination of the L1-E7 polypeptide with ExoCrocin or ExoCurcumin could produce a significant level of immunity directed toward Th1 response and CTL activity. These regimens showed the protective and therapeutic effects against tumor cells (the percentage of tumor-free mice: ~100%). In addition, both ExoCrocin and ExoCurcumin represented similar immunological and anti-tumor effects. Generally, the use of exosomal crocin or curcumin forms along with the L1-E7 polypeptide could significantly induce T-cell immune responses and eradicate tumor cells.

Immunoinformatics driven construction of multi-epitope vaccine candidate against Ascaris lumbricoides using its entire immunogenic epitopes

OBJECTIVE

Ascaris lumbricoides infects 80 million people per year, causing malnutrition, stunted growth of children etc., but there is no vaccine available against it. We aimed to design a multimeric-subunit vaccine using comprehensive immunoinformatic approach.

RESEARCH DESIGN AND METHODS

The T and B cell epitopes were shortlisted on antigenicity, allergenicity, and toxicity from proteome data and joined with appropriate linkers. The physical characteristics of vaccine candidate was calculated and docking/molecular dynamic simulation performed to validate its robustness. The multimeric protein was codon optimized and in-silico cloned in pET28b.

RESULTS

From the 23,604 proteins of Ascaris, we filtered based on epitope prediction, localization, antigenicity, and allergenicity. Prepared a vaccine of 534 amino acid long, 56.31 kD weight and pI 4.52. Physiochemical features showed it is soluble, highly antigenic and non-allergenic. Its tertiary structure was forecasted, certified, and refined. The immunoinformatic simulation studies showed it to be potent T and B cell stimulator.

CONCLUSIONS

We identified highly antigenic peptides of Ascaris from its proteome with good potential to induce innate as well as humoral immune response. These peptides were used to design a chimeric vaccine against Ascariasis infection, which can be used for prophylactic purpose but needs experimental and clinical validation.

Pharmacoinformatics and molecular dynamics simulation studies reveal potential covalent and FDA-approved inhibitors of SARS-CoV-2 main protease 3CLpro

The SARS-CoV-2 was confirmed to cause the global pandemic of coronavirus disease 2019 (COVID-19). The 3-chymotrypsin-like protease (3CLpro), an essential enzyme for viral replication, is a valid target to combat SARS-CoV and MERS-CoV. In this work, we present a structure-based study to identify potential covalent inhibitors containing a variety of chemical warheads. The targeted Asinex Focused Covalent (AFCL) library was screened based on different reaction types and potential covalent inhibitors were identified. In addition, we screened FDA-approved protease inhibitors to find candidates to be repurposed against SARS-CoV-2 3CLpro. A number of compounds with significant covalent docking scores were identified. These compounds were able to establish a covalent bond (C-S) with the reactive thiol group of Cys145 and to form favorable interactions with residues lining the substrate-binding site. Moreover, paritaprevir and simeprevir from FDA-approved protease inhibitors were identified as potential inhibitors of SARS-CoV-2 3CLpro. The mechanism and dynamic stability of binding between the identified compounds and SARS-CoV-2 3CLpro were characterized by molecular dynamics (MD) simulations. The identified compounds are potential inhibitors worthy of further development as COVID-19 drugs. Importantly, the identified FDA-approved anti-hepatitis-C virus (HCV) drugs paritaprevir and simeprevir could be ready for clinical trials to treat infected patients and help curb COVID-19. Communicated by Ramaswamy H. Sarma.

Designing a multi-epitope vaccine candidate to combat MERS-CoV by employing an immunoinformatics approach

Currently, no approved vaccine is available against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes severe respiratory disease. The spike glycoprotein is typically considered a suitable target for MERS-CoV vaccine candidates. A computational strategy can be used to design an antigenic vaccine against a pathogen. Therefore, we used immunoinformatics and computational approaches to design a multi-epitope vaccine that targets the spike glycoprotein of MERS-CoV. After using numerous immunoinformatics tools and applying several immune filters, a poly-epitope vaccine was constructed comprising cytotoxic T-cell lymphocyte (CTL)-, helper T-cell lymphocyte (HTL)-, and interferon-gamma (IFN-γ)-inducing epitopes. In addition, various physicochemical, allergenic, and antigenic profiles were evaluated to confirm the immunogenicity and safety of the vaccine. Molecular interactions, binding affinities, and the thermodynamic stability of the vaccine were examined through molecular docking and dynamic simulation approaches, during which we identified a stable and strong interaction with Toll-like receptors (TLRs). In silico immune simulations were performed to assess the immune-response triggering capabilities of the vaccine. This computational analysis suggested that the proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat viral infections; however, experimental evaluations remain necessary to verify the exact safety and immunogenicity profile of this vaccine.

Recent progress on MHC-I epitope prediction in tumor immunotherapy

Tumor immunotherapy has now become one of the most potential therapy for those intractable cancer diseases. The antigens on the cancer cell surfaces are the keys for the immune system to recognize and eliminate them. As reported, the immunogenicity of the tumor antigens could be determined by the binding between the key epitope peptides and MHC molecules. In recent years, the approaches to anticipate the peptides from the candidate epitopes have gradually changed into more efficient methods. Including the improved conventional methods, more diverse methods were coming into view. Here we review the anticipated methods of the tumor associated epitopes that specifically bind with major histocompatibility complex (MHC) class I molecules, and the recent advances and applications of those epitope prediction methods.

Peptide-based therapeutic cancer vaccine: Current trends in clinical application

The peptide‐based therapeutic cancer vaccines have attracted enormous attention in recent years as one of the effective treatments of tumour immunotherapy. Most of peptide‐based vaccines are based on epitope peptides stimulating CD8⁺ T cells or CD4⁺ T helper cells to target tumour‐associated antigens (TAAs) or tumour‐specific antigens (TSAs). Some adjuvants and nanomaterials have been exploited to optimize the efficiency of immune response of the epitope peptide to improve its clinical application. At present, numerous peptide‐based therapeutic cancer vaccines have been developed and achieved significant clinical benefits. Similarly, the combination of peptide‐based vaccines and other therapies has demonstrated a superior efficacy in improving anti‐cancer activity. We delve deeper into the choices of targets, design and screening of epitope peptides, clinical efficacy and adverse events of peptide‐based vaccines, and strategies combination of peptide‐based therapeutic cancer vaccines and other therapies. The review will provide a detailed overview and basis for future clinical application of peptide‐based therapeutic cancer vaccines.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Cancer Immunoprevention: Current Status and Future Directions

Cancer is one of the most serious diseases affecting health and the second leading cause of death worldwide. Despite the development of various therapeutic modalities to deal with cancer, limited improvement in overall survival of patients has been yielded. Since there is no certain cure for cancer, detection of premalignant lesions, and prevention of their progression are vital to the decline of high morbidity and mortality of cancer. Among approaches to cancer prevention, immunoprevention has gained further attention in recent years. Deep understanding of the tumor/immune system interplay and successful prevention of virally-induced malignancies by vaccines have paved the way toward broadening cancer immunoprevention application. The identification of tumor antigens in premalignant lesions was the turning point in cancer immunoprevention that led to designing preventive vaccines for various malignancies including multiple myeloma, colorectal, and breast cancer. In addition to vaccines, immune checkpoint inhibitors are also being tested for the prevention of oral squamous cell carcinoma (SCC), and imiquimod which is an established drug for the prevention of skin SCC, is a non-specific immunomodulator. Herein, to provide a bench-to-bedside understanding of cancer immunoprevention, we will review the role of the immune system in suppression and promotion of tumors, immunoprevention of virally-induced cancers, identification of tumor antigens in premalignant lesions, and clinical advances of cancer immunoprevention.

In silico prediction of T-cell and B-cell epitopes of human papillomavirus type 16 L1 protein

Human papillomavirus type 16 (HPV-16) is one of the most important cause of developing cervical cancer. Therefore, effective epitope-based vaccine design for HPV-16 would be of major medical benefit. The aim of our study was to identify B- and T-cell epitopes of HPV-16 L1 protein. In this study, the HPV-16 L1 gene was isolated from HPV recovered from five vaginal swab samples using specific primers and finally sequenced. The ExPASy translate tool (http://web.expasy.org/translate/) was used to convert nucleotide sequence into amino acid sequence. Bioinformatic analysis was employed to predict suitable B- and T-cell epitopes and immunogenicity, allergenicity, and toxicity of predicted epitopes were then evaluated. Afterward, the selected T-cell epitopes were docked using Molegro Virtual Docker software. The two epitopes ₂₀₇ AMDFTTLQA₂₁₅ and ₂₀₀ MVDTGFGAM₂₀₈ have showed a very strong binding affinity to HLA-A0201 and HLA-B3501 molecules, respectively. Outcome of B-cell epitope prediction showed that epitope ₄₇₅ KAKPKFTLGKRK ATPTTSSTSTTAKRKK₅₀₂ contained overlapped epitope, which might be the epitope associated with the production of neutralizing antibody response. Based on this finding, the predicted B- and T-cell epitopes are promising targets for epitope-based vaccine development against HPV-16. Further in vivo and in vitro experiments are needed to confirm our findings.

Scouting the receptor-binding domain of SARS coronavirus 2: a comprehensive immunoinformatics inquisition

Aim: December 2019 witnessed the emergence of a worldwide outbreak of a novel strain of coronavirus (CoV) termed SARS-CoV-2. Several preventive strategies are being developed, such as vaccines, to stop the spread of infection. Materials & methods: A comprehensive immunoinformatics approach was used to map conserved peptide sequences on the receptor binding domain of SARS-CoV-2 for their B-cell, T-helper & T-cytotoxic cell epitope profiles. Results & conclusion: The antigenic B-cell epitopes were LFRKSN and SYGFQPT. Among T-cell epitopes, CVADYSVLY and FTNVYADSF exhibited affinity for MHC class I, while YRLFRKSNL and VYAWNRKRI exhibited affinity for of MHC class II alleles. The overlapping epitope between B- and T-cells was YRLFRKSNL. The deployment of these epitopes in potential vaccine development against COVID-19 may help in slowing down the SARS-CoV-2 spread.

New novel non-MHC genes were identified for cervical cancer with an integrative analysis approach of transcriptome-wide association study

Although genome-wide association studies (GWAS) have successfully identified multiple genetic variants associated with cervical cancer, the functional role of those variants is not well understood. To bridge such gap, we integrated the largest cervical cancer GWAS (N = 9,347) with gene expression measured in six human tissues to perform a multi-tissue transcriptome-wide association study (TWAS). We identified a total of 20 associated genes in the European population, especially four novel non-MHC genes (i.e. WDR19, RP11-384K6.2, RP11-384K6.6 and ITSN1). Further, we attempted to validate our results in another independent cervical cancer GWAS from the East Asian population (N = 3,314) and re-discovered four genes including WDR19, HLA-DOB, MICB and OR2B8P. In our subsequent co-expression analysis, we discovered SLAMF7 and LTA were co-expressed in TCGA tumor samples and showed both WDR19 and ITSN1 were enriched in "plasma membrane". Using the protein-protein interaction analysis we observed strong interactions between the proteins produced by genes that are associated with cervical cancer. Overall, our study identified multiple candidate genes, especially four non-MHC genes, which may be causally associated with the risk of cervical cancer. However, further investigations with larger sample size are warranted to validate our findings in diverse populations.

Long non-coding RNA AK001903 regulates tumor progression in cervical cancer

A majority of cervical cancers are squamous cell carcinomas, arising from the squamous (flattened) epithelial cells that line the cervix. Long noncoding RNAs (lncRNAs) are a unique class of messenger RNA-like transcripts of at least 200 nucleotides in length with no significant protein-coding capacity. Aberrant lncRNA expression is emerging as a major component of the cancer transcriptome. In the present study, lncRNA microarrays were conducted to investigate the differentially expression lncRNAs in cervical cancer (CC) tissues compared with peritumoral tissues. Then, the most significantly upregulated lncRNA, which was lncRNA-AK001903 was selected to conduct further experiments. Real-time Quantitative polymerase chain reaction was conducted to investigate lncRNA-AK001903 expression in CC tissues and Hela, Siha, Ca Ski, C33a, H8 (HPV-immortalized cervical epithelial cell line) cell lines, and in situ hybridization histochemistry (ISHH) was performed to detect lncRNA-AK001903 expression level in different CC stages. The effect of lncRNA-AK001903 on cell proliferation, invasion and migration was assessed after knockdown of lncRNA-AK001903. The findings of the study confirmed that lncRNA-AK001903 was upregulated in CC cells and tissues compared with normal cell line H8 and peritumoral tissues. ISHH demonstrated that the expression level of lncRNA-AK001903 was connected with International Federation of Gynecology and Obstetrics (2018) stage of CC. Knockdown of lncRNA-AK001903 inhibited cell proliferation, invasion and migration in Ca Ski cells. In conclusion, lncRNA-AK001903 was demonstrated to be an oncogenic lncRNA that promotes tumor progression and may be an effective target for CC treatment in the near future.

A Putative Prophylactic Solution for COVID-19: Development of Novel Multiepitope Vaccine Candidate against SARS-COV-2 by Comprehensive Immunoinformatic and Molecular Modelling Approach

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the World Health Organization has declared it a pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. The urgency of the situation requires the development of SARS-CoV-2-based vaccines. Immunoinformatic and molecular modelling are time-efficient methods that are generally used to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines has proved to be a promising immunization strategy against viruses and pathogens, thus inducing more comprehensive protective immunity. The current study demonstrated a comprehensive in silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in Escherichia coli. Despite that this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can be present as a better prophylactic solution against COVID-19.

Resisting Resistance to Immune Checkpoint Therapy: A Systematic Review

The treatment landscape in oncology has witnessed a major revolution with the introduction of checkpoint inhibitors: anti-PD1, anti-PDL1 and anti-CTLA-4. These agents enhance the immune response towards cancer cells instead of targeting the tumor itself, contrary to standard chemotherapy. Although long-lasting durable responses have been observed with immune checkpoints inhibitors, the response rate remains relatively low in many cases. Some patients respond in the beginning but then eventually develop acquired resistance to treatment and progress. Other patients having primary resistance never respond. Multiple studies have been conducted to further elucidate these variations in response in different tumor types and different individuals. This paper provides an overview of the mechanisms of resistance to immune checkpoint inhibitors and highlights the possible therapeutic approaches under investigation aiming to overcome such resistance in order to improve the clinical outcomes of cancer patients.

Enhanced Thermostability and Enzymatic Activity of Cel6A Variants from Thermobifida fusca by Empirical Domain Engineering (Short Title: Domain Engineering of Cel6A)

Cellulases are a set of lignocellulolytic enzymes, capable of producing eco-friendly low-cost renewable bioethanol. However, low stability and hydrolytic activity limit their wide-scale applicability at the industrial scale. In this work, we report the domain engineering of endoglucanase (Cel6A) of Thermobifida fusca to improve their catalytic activity and thermal stability. Later, enzymatic activity and thermostability of the most efficient variant named as Cel6A.CBC was analyzed by molecular dynamics simulations. This variant demonstrated profound activity against soluble and insoluble cellulosic substrates like filter paper, alkali-treated bagasse, regenerated amorphous cellulose (RAC), and bacterial microcrystalline cellulose. The variant Cel6A.CBC showed the highest catalysis of carboxymethyl cellulose (CMC) and other related insoluble substrates at a pH of 6.0 and a temperature of 60 °C. Furthermore, a sound rationale was observed between experimental findings and molecular modeling of Cel6A.CBC which revealed thermostability of Cel6A.CBC at 26.85, 60.85, and 74.85 °C as well as structural flexibility at 126.85 °C. Therefore, a thermostable derivative of Cel6A engineered in the present work has enhanced biological performance and can be a useful construct for the mass production of bioethanol from plant biomass.

Isolation of Antidiabetic Withanolides from Withania coagulans Dunal and Their In Vitro and In Silico Validation

Withania coagulans (W. coagulans) is well-known in herbal medicinal systems for its high biological potential. Different parts of the plant are used against insomnia, liver complications, asthma, and biliousness, as well as it is reported to be sedative, emetic, diuretic, antidiabetic antimicrobial, anti-inflammatory, antitumor, hepatoprotective, antihyperglycemic, cardiovascular, immuno-suppressive and central nervous system depressant. Withanolides present in W. coagulans have attracted an immense interest in the scientific field due to their diverse therapeutic applications. The current study deals with chemical and biological evaluation of chloroform, and n-butanol fractions of W. coagulans. The activity-guided fractionation of both extracts via multiple chromatographic steps and structure elucidation of pure isolates using spectroscopies (NMR, mass spectrometry, FTIR and UV-Vis) led to the identification of a new withanolide glycoside, withacogulanoside-B (1) from n-butanol extract and five known withanolides from chloroform extract [withanolid J (2), coagulin E (3), withaperuvin C (4), 27-hydroxywithanolide I (5), and ajugin E (6)]. Among the tested compounds, compound 5 was the most potent α-glucosidase inhibitor with IC₅₀ = 66.7 ± 3.6 µM, followed by compound 4 (IC₅₀: 407 ± 4.5 µM) and compound 2 (IC₅₀: 683 ± 0.94 µM), while no antiglycation activity was observed with the six isolated compounds. Molecular docking was used to predict the binding potential and binding site interactions of these compounds as α-glucosidase inhibitors. Consequently, this study provides basis to discover specific antidiabetic compounds from W. coagulans.

A candidate multi-epitope vaccine against SARS-CoV-2

In the past two decades, 7 coronaviruses have infected the human population, with two major outbreaks caused by SARS-CoV and MERS-CoV in the year 2002 and 2012, respectively. Currently, the entire world is facing a pandemic of another coronavirus, SARS-CoV-2, with a high fatality rate. The spike glycoprotein of SARS-CoV-2 mediates entry of virus into the host cell and is one of the most important antigenic determinants, making it a potential candidate for a vaccine. In this study, we have computationally designed a multi-epitope vaccine using spike glycoprotein of SARS-CoV-2. The overall quality of the candidate vaccine was validated in silico and Molecular Dynamics Simulation confirmed the stability of the designed vaccine. Docking studies revealed stable interactions of the vaccine with Toll-Like Receptors and MHC Receptors. The in silico cloning and codon optimization supported the proficient expression of the designed vaccine in E. coli expression system. The efficiency of the candidate vaccine to trigger an effective immune response was assessed by an in silico immune simulation. The computational analyses suggest that the designed multi-epitope vaccine is structurally stable which can induce specific immune responses and thus, can be a potential vaccine candidate against SARS-CoV-2.

HPV16-E7 Protein T Cell Epitope Prediction and Global Therapeutic Peptide Vaccine Design Based on Human Leukocyte Antigen Frequency: An In-Silico Study

Cervical cancer is the second most common leading cause of women's death due to cancer worldwide, about 528,000 patients’ cases and 266,000 deaths per year, related to human papillomavirus (HPV). Peptide-based vaccines being safe, stable, and easy to produce have demonstrated great potential to develop therapeutic HPV vaccine. In this study, the major histocompatibility complex (MHC) class I, class II T cell epitopes of HPV16-E7 were predicted. Therefore, we designed a plan to find the most effective peptides to prompt appropriate immune responses. For this purpose, retrieving protein sequences, conserved region identification, phylogenic tree construction, T cell epitope prediction, epitope-predicted population coverage calculation, and molecular docking were performed consecutively and most effective immune response prompting peptides were selected. Based on different tools index, six CD8+ T cells and six CD4+ epitopes were chosen. This combination of 12 epitopes created a putative global vaccine with a 95.06% population coverage. These identified peptides can be employed further for peptide analysis and can be used as a peptide or poly-epitope candidates for therapeutic vaccine studies to treat HPV-associated cancers.

Development of multi-epitope chimeric vaccine against Taenia solium by exploring its proteome: an in silico approach

Objective: Taenia solium is a neglected tropical disease; larvae of this parasite infect central nervous system i.e. Neurocysticercosis, and adults mature and survive into intestine i.e. Taeniasis. Globally more than 50 million people are at the risk of infection. This is one of the main etiological agents for onset of new early epilepsy in developing countries. However, there is no vaccine available to protect human from its infection. Hence, there is an urgent need for a good vaccine.Methods: We applied immune-informatics approach to design a multi-epitope chimeric vaccine consisting of both B and T-cell epitopes.Results: From the whole transcriptome of Taenia, we identified five suitable peptides present on cell membrane, epitope identification on these peptides were done by using various immunoinformatic software. Physiochemical properties were determined and the tertiary structure of vaccine was predicted, validated and refined, and to increase antigenicity we added linker to them. Best-modeled protein-complex was used for docking study with TLR1-2, TLR4, TLR3 and TLR7 and stability of molecular complex was determined by molecular dynamics simulation.Conclusions: Overall, we attempted to design an efficient subunit chimeric vaccine, which could stimulate humoral and cellular immune responses and could protect against both neurocysticercosis and taeniasis.

Development of HPV16,18,31,45 E5 and E7 peptides-based vaccines predicted by immunoinformatics tools

Objectives

Viral oncoproteins are ideal targets in therapeutic vaccines for functional inhibition of human papillomaviruses (HPVs). Herein, we designed the peptide constructs derived from E5 and E7 oncoproteins of high-risk HPV types 16, 18, 31 and 45 using the bioinformatics tools and investigated their potency in mice.

Results

The framework of the combined in silico/in vivo analysis included (1) to determine physicochemical properties of the designed constructs, (2) to identify potential IFN-γ-inducing epitopes, (3) to assess allergenicity, (4) to recognize linear and discontinuous B cell epitopes using modeling and validation of 3D structure of the designed constructs, and (5) to evaluate immune responses and tumor growth in vivo. Our in silico data determined high potency of the HPV_16,18,31,45 E5 and HPV_16,18,31,45 E7 peptides for trigger B- and T-cell responses, and IFN-γ secretion. In vivo study indicated that the mixture of E5 and E7 immunodominant peptides from four types of high-risk HPV could induce Th1 immune response, and protect completely mice against TC-1 tumor cells.

Conclusion

Generally, the combined in silico/in vivo approaches showed the ability of the designed E5 and E7 peptide constructs from four major high-risk HPV types for development of therapeutic vaccines.

Electronic supplementary material

The online version of this article (10.1007/s10529-020-02792-6) contains supplementary material, which is available to authorized users.

Therapeutic Vaccines for HPV-Associated Malignancies

Human papillomavirus (HPV)-related malignancies are responsible for almost all cases of cervical cancer in women, and over 50% of all cases of head and neck carcinoma. Worldwide, HPV-positive malignancies account for 4.5% of the global cancer burden, or over 600,000 cases per year. HPV infection is a pressing public health issue, as more than 80% of all individuals have been exposed to HPV by age 50, representing an important target for vaccine development to reduce the incidence of cancer and the economic cost of HPV-related health issues. The approval of Gardasil^® as a prophylactic vaccine for high-risk HPV 16 and 18 and low-risk HPV6 and 11 for people aged 11-26 in 2006, and of Cervarix^® in 2009, revolutionized the field and has since reduced HPV infection in young populations. Unfortunately, prophylactic vaccination does not induce immunity in those with established HPV infections or HPV-induced neoplasms, and there are currently no therapeutic HPV vaccines approved by the US Food and Drug Administration. This comprehensive review will detail the progress made in the development of therapeutic vaccines against high-risk HPV types, and potential combinations with other immunotherapeutic agents for more efficient and rational designs of combination treatments for HPV-associated malignancies.

Prediction of MAYV peptide antigens for immunodiagnostic tests by immunoinformatics and molecular dynamics simulations

The Mayaro virus is endemic to South America, and the possible involvement of Aedes spp. mosquitoes in its transmission is a risk factor for outbreaks of greater proportions. The virus causes a potentially disabling illness known as Mayaro fever, which is similar to that caused by the chikungunya virus. The cocirculation of both viruses, with their clinical and structural similarities, and the absence of prophylactic and therapeutic measures highlight the need for studies that seek to understand the Mayaro virus. Using approaches in silico, we identified an antigenic and specific epitope (p_MAYV4) in domain A of the E2 glycoprotein of the Mayaro virus. This epitope was theoretically predicted to be stable and exposed on the surface of the protein, where it showed key properties that enable its interaction with neutralizing antibodies. These characteristics make it an interesting target for the development of immunodiagnostic platforms. Molecular dynamics simulation-based structural analysis showed that the PHE95 residue in the E1 fusion loop region is conserved among Alphavirus family members. PHE95 interacts with the hydrophobic residues of the E2 glycoprotein to form a cage-shaped structure that is critical to assemble and stabilize the E1/E2 heterodimer. These results provide important insights useful for the advancement of diagnostic platforms and the study of therapeutic alternatives.

In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors

The Crimean-Congo Hemorrhagic Fever virus (CCHFV) is a segmented negative single-stranded RNA virus (-ssRNA) which causes severe hemorrhagic fever in humans with a mortality rate of ~50%. To date, no vaccine has been approved. Treatment is limited to supportive care with few investigational drugs in practice. Previous studies have identified viral RNA dependent RNA Polymerase (RdRp) as a potential drug target due to its significant role in viral replication and transcription. Since no crystal structure is available yet, we report the structural elucidation of CCHFV-RdRp by in-depth homology modeling. Even with low sequence identity, the generated model suggests a similar overall structure as previously reported RdRps. More specifically, the model suggests the presence of structural/functional conserved RdRp motifs for polymerase function, the configuration of uniform spatial arrangement of core RdRp sub-domains, and predicted positively charged entry/exit tunnels, as seen in sNSV polymerases. Extensive pharmacophore modeling based on per-residue energy contribution with investigational drugs allowed the concise mapping of pharmacophoric features and identified potential hits. The combination of pharmacophoric features with interaction energy analysis revealed functionally important residues in the conserved motifs together with in silico predicted common inhibitory binding modes with highly potent reference compounds.

Mutagenesis of DsbAss is Crucial for the Signal Recognition Particle Mechanism in Escherichia coli: Insights from Molecular Dynamics Simulations

The disulfide bond signal sequence (DsbAss) protein is characterized as an important virulence factor in gram-negative bacteria. This study aimed to analyze the "alanine" alteration in the hydrophobic (H) region of DsbAss and to understand the conformational DsbAss alteration(s) inside the fifty-four homolog (Ffh)-binding groove which were revealed to be crucial for translocation of ovine growth hormone (OGH) to the periplasmic space in Escherichia coli via the secretory (Sec) pathway. An experimental design was used to explore the hydrophobicity and alteration of alanine (Ala) to isoleucine (Ile) in the tripartite structure of DsbAss. As a result, two DsbAss mutants (Ala at positions -11 and -13) with same hydrophobicity of 1.539 led to the conflicting translocation of the active OGH gene. We performed molecular dynamics (MD) simulations and molecular mechanics generalized born surface area (MM-GBSA) binding free energy calculations to examine the interaction energetic and dynamic aspects of DsbAss/signal repetition particle 54 (SRP54) binding, which has a principle role in Escherichia coli Sec pathways. Although both DsbAss mutants retained helicity, the MD simulation analysis evidenced that altering Ala-13 changed the orientation of the signal peptide in the Ffh M binding domain groove, favored more stable interaction energies (MM-GBSA ΔG_total = -140.62 kcal mol^-1), and hampered the process of OGH translocation, while Ala-11 pointed outward due to unstable conformation and less binding energy (ΔG_total = -124.24 kcal mol^-1). Here we report the dynamic behavior of change of "alanine" in the H-domain of DsbAss which affects the process of translocation of OGH, where MD simulation and MM-GBSA can be useful initial tools to investigate the virulence of bacteria.