Immunoinformatics design of multiepitopes peptide-based universal cancer vaccine using matrix metalloproteinase-9 protein as a target

Design and In Silico Validation of a Novel MZF-1-Based Multi-Epitope Vaccine to Combat Metastatic Triple Negative Breast Cancer

Immunotherapy is emerging as a potential therapeutic strategy for triple negative breast cancer (TNBC) owing to the immunogenic landscape of its tumor microenvironment. Interestingly, peptide-based cancer vaccines have garnered a lot of attention as one of the most promising cancer immunotherapy regimens. Thus, the present study intended to design a novel, efficacious peptide-based vaccine against TNBC targeting myeloid zinc finger 1 (MZF1), a transcription factor that has been described as an oncogenic inducer of TNBC metastasis. Initially, the antigenic peptides from MZF1 were identified and evaluated based on their likelihood to induce immunological responses. The promiscuous epitopes were then combined using a suitable adjuvant (50S ribosomal L7/L12 protein) and linkers (AAY, GPGPG, KK, and EAAAK) to reduce junctional immunogenicity. Furthermore, docking and dynamics analyses against TLR-4 and TLR-9 were carried out to understand more about their structural stability and integrity. Finally, the constructed vaccine was subjected to in silico cloning and immune simulation studies. Overall, the findings imply that the designed chimeric vaccine could induce strong humoral and cellular immune responses in the desired organism. In light of these findings, the final multi-epitope vaccine could be used as an effective prophylactic treatment for TNBC and may pave the way for future research.

Designing multi-epitope vaccine against important colorectal cancer (CRC) associated pathogens based on immunoinformatics approach

BACKGROUND

It seems that several members of intestinal gut microbiota like Streptococcus bovis, Bacteroides fragilis, Helicobacter pylori, Fusobacterium nucleatum, Enterococcus faecalis, Escherichia coli, Peptostreptococcus anaerobius may be considered as the causative agents of Colorectal Cancer (CRC). The present study used bioinformatics and immunoinformatics approaches to design a potential epitope-based multi-epitope vaccine to prevent CRC with optimal population coverage.

METHODS

In this study, ten amino acid sequences of CRC-related pathogens were retrieved from the NCBI database. Three ABCpred, BCPREDS and LBtope online servers were considered for B cells prediction and the IEDB server for T cells (CD4⁺ and CD8⁺) prediction. Then, validation, allergenicity, toxicity and physicochemical analysis of all sequences were performed using web servers. A total of three linkers, AAY, GPGPG, and KK were used to bind CTL, HTL and BCL epitopes, respectively. In addition, the final construct was subjected to disulfide engineering, molecular docking, immune simulation and codon adaptation to design an effective vaccine production strategy.

RESULTS

A total of 19 sequences of different lengths for linear B-cell epitopes, 19 and 18 sequences were considered as epitopes of CD4⁺ T and CD8⁺ cells, respectively. The predicted epitopes were joined by appropriate linkers because they play an important role in producing an extended conformation and protein folding. The final multi-epitope construct and Toll-like receptor 4 (TLR4) were evaluated by molecular docking, which revealed stable and strong binding interactions. Immunity simulation of the vaccine showed significantly high levels of immunoglobulins, helper T cells, cytotoxic T cells and INF-γ.

CONCLUSION

Finally, the results showed that the designed multi-epitope vaccine could serve as an excellent prophylactic candidate against CRC-associated pathogens, but in vitro and animal studies are needed to justify our findings for its use as a possible preventive measure.

Genetic Interference of FGFR3 Impedes Invasion of Upper Tract Urothelial Carcinoma Cells by Alleviating RAS/MAPK Signal Activity

Upper tract urothelial cancer (UTUC) is a less common disease in Western countries but has a high level of prevalence in Asian populations. Compared to bladder cancer, unique etiologic and genomic factors are involved in UTUC. Fibroblast growth factor receptor 3 (FGFR3) up-regulation has been proposed as a promising target for bladder cancer therapy. In this study, we aimed to profile the expression of FGFR3 in Asian and Caucasian UTUC tissues and to evaluate the in vitro therapeutic efficacy of small interference RNA (siRNA)-mediated FGFR3 silencing in UTUC treatment. The FGFR3 expression levels in renal pelvis tissues and microarray sections from Asian and Caucasian patients with UTUC, respectively, were measured via immunohistochemistry. The BFTC-909 and UM-UC-14 UTUC cell lines were used to examine the effects of FGFR3 silencing on proliferation, migration, epithelial-mesenchymal transition (EMT) marker expression, and signaling machinery. FGFR3 expression increased as the TNM stage increased in both Asian and Caucasian UTUC tumors, and no statistical difference was identified between the two groups. In vitro studies demonstrated that FGFR3 siRNA delivery significantly inhibited proliferation and migration and suppressed the expression of EMT markers and transcription factors in UTUC cells. Mechanistically, FGFR3 silencing alleviated the constitutive expression of RAS and the phosphorylation of MAPK signaling mediators, including ERK1/2 and JNK1/2. FGFR3 silencing elicited an apoptosis-inducing effect similar to that of FGFR inhibition. Conclusion: siRNA-targeted FGFR3 expression may impede the expansion and invasion of UTUC cells by alleviating the RAS/MAPK signaling pathway. The genetic interference of FGFR3 expression via siRNA in UTUC cells may constitute a useful therapeutic strategy.

Immunoinformatics Approach for Epitope-Based Vaccine Design: Key Steps for Breast Cancer Vaccine

Vaccines are an upcoming medical intervention for breast cancer. By targeting the tumor antigen, cancer vaccines can be designed to train the immune system to recognize tumor cells. Therefore, along with technological advances, the vaccine design process is now starting to be carried out with more rational methods such as designing epitope-based peptide vaccines using immunoinformatics methods. Immunoinformatics methods can assist vaccine design in terms of antigenicity and safety. Common protocols used to design epitope-based peptide vaccines include tumor antigen identification, protein structure analysis, T cell epitope prediction, epitope characterization, and evaluation of protein-epitope interactions. Tumor antigen can be divided into two types: tumor associated antigen and tumor specific antigen. We will discuss the identification of tumor antigens using high-throughput technologies. Protein structure analysis comprises the physiochemical, hydrochemical, and antigenicity of the protein. T cell epitope prediction models are widely available with various prediction parameters as well as filtering tools for the prediction results. Epitope characterization such as allergenicity and toxicity can be done in silico as well using allergenicity and toxicity predictors. Evaluation of protein-epitope interactions can also be carried out in silico with molecular simulation. We will also discuss current and future developments of breast cancer vaccines using an immunoinformatics approach. Finally, although prediction models have high accuracy, the opposite can happen after being tested in vitro and in vivo. Therefore, further studies are needed to ensure the effectiveness of the vaccine to be developed. Although epitope-based peptide vaccines have the disadvantage of low immunogenicity, the addition of adjuvants can be a solution.

Screening of B-cell epitopes of Der-p1 and Der-p2 major aeroallergens by computational approach for designing immunotherapeutics

Introduction and Aim: Allergic diseases are IgE-mediated hypersensitivity reactions affecting approximately 30% of the general population globally. Dermatophagoides pteronyssinus (Der-p) is the most prevalent house dust mite (HDM) species consisting of 23 mite allergen groups. Among these, group 1 and 2 are major allergenic proteins, which causes allergic asthma in 80% of sensitized individuals, with elevated IgE titres in the serum. This study involves in silico analysis of potential B-cell epitopes of group 1 and group 2 of Der-p, which can be utilized in designing immunotherapeutic vaccines.   Materials and Methods: Allergen sequences obtained from the database- International Union of Immunological Societies (IUIS), for predicting of B-cell epitopes. The physiochemical properties and secondary structures of the obtained sequence were evaluated. The sequences were further subjected to determining antigenicity, surface accessibility, and prediction of linear and discontinuous B-cell epitope by utilizing IEDB tools.   Results: The linear and discontinuous B-cell epitopes of Der-p1 and Der-p2 aeroallergen were predicted. Further, Der-p1 and Der-p2 showed 6 linear epitopes each respectively. Conformational epitopes predicted were 123 of Der-p1 and 72 of Der-p2 respectively, by the ElliPro tool. Based on the structure, antigenicity, and surface accessibility, only 10% of Der-p1 and Der-p2 which binds to B-cell epitopes are linear and the majority are discontinuous.   Conclusion: The linear and conformational epitopes of Der-p1 and Der-p2 are predicted using in silico tools. These identified epitopes might be useful for developing epitope-based immunotherapeutics for HDM allergy.

Immunoinformatics- and Bioinformatics-Assisted Computational Designing of a Novel Multiepitopes Vaccine Against Cancer-Causing Merkel Cell Polyomavirus

Merkel cell polyomavirus (MCV) contains double-stranded DNA as its genome and is the fifth polyomavirus that infects humans. The virus causes Merkel cell carcinoma (aggressive skin cancer). Till present, no proper drug or vaccines are available to treat/prevent the virus infection and stop the emergence of Merkel cell carcinoma. In this study, computational vaccine design strategies were applied to design a chimeric-epitopes vaccine against the virus. The complete proteome comprised of four proteins was filtered through various vaccine candidacy parameters and as such two proteins, namely, capsid protein VP1 and capsid protein VP2, were considered as good vaccine targets. Furthermore, they harbor safe and potential B and T cell epitopes, which can be used in a chimeric multiepitopes-based vaccine design. The epitopes of the vaccine have maximum world population coverage of 95.04%. The designed vaccine structure was modeled in 3D that reported maximum residues in favored regions (95.7%) of the Ramachandran plot. The interactions analysis with different human immune receptors like TLR3, MHC-I, and MHC-II illustrated vaccine's good binding affinity and stable dynamics. The structural deviations of the vaccine receptor(s) complexes are within 5 Å, where majority of the receptors residues remain in good equilibrium in the simulation time. Also, the vaccine was found to form between 60 and 100 hydrogen bonds to receptors. The vaccine stimulated strong immune responses in addition to interferon and cytokines. The strength of vaccine-receptor(s) binding was further affirmed by binding energies estimation that concluded <-150.32 kcal/mol of net binding energy. All these findings suggest the vaccine as a promising candidate that needs further experimental testing to disclose its real immune protective efficacy. Furthermore, the designed vaccine might accelerate vaccine development against the MCV and could save time and expenses.

A Vaccine Construction against COVID-19-Associated Mucormycosis Contrived with Immunoinformatics-Based Scavenging of Potential Mucoralean Epitopes

Mucormycosis is a group of infections, caused by multiple fungal species, which affect many human organs and is lethal in immunocompromised patients. During the COVID-19 pandemic, the current wave of mucormycosis is a challenge to medical professionals as its effects are multiplied because of the severity of COVID-19 infection. The variant of concern, Omicron, has been linked to fatal mucormycosis infections in the US and Asia. Consequently, current postdiagnostic treatments of mucormycosis have been rendered unsatisfactory. In this hour of need, a preinfection cure is needed that may prevent lethal infections in immunocompromised individuals. This study proposes a potential vaccine construct targeting mucor and rhizopus species responsible for mucormycosis infections, providing immunoprotection to immunocompromised patients. The vaccine construct, with an antigenicity score of 0.75 covering, on average, 92-98% of the world population, was designed using an immunoinformatics approach. Molecular interactions with major histocompatibility complex-1 (MHC-I), Toll-like receptors-2 (TLR2), and glucose-regulated protein 78 (GRP78), with scores of -896.0, -948.4, and -925.0, respectively, demonstrated its potential to bind with the human immune receptors. It elicited a strong predicted innate and adaptive immune response in the form of helper T (Th) cells, cytotoxic T (TC) cells, B cells, natural killer (NK) cells, and macrophages. The vaccine cloned in the pBR322 vector showed positive amplification, further solidifying its stability and potential. The proposed construct holds a promising approach as the first step towards an antimucormycosis vaccine and may contribute to minimizing postdiagnostic burdens and failures.

Biomaterials, biological molecules, and polymers in developing vaccines

Vaccines have been used to train the immune system to recognize pathogens, and prevent and treat diseases, such as cancer, for decades. However, there are continuing challenges in their manufacturing, large-scale production, and storage. Some of them also show suboptimal immunogenicity, requiring additional adjuvants and booster doses. As an alternate vaccination strategy, a new class of biomimetic materials with unique functionalities has emerged in recent years. Here, we explore the current bioengineering techniques that make use of hydrogels, modified polymers, cell membranes, self-assembled proteins, virus-like particles (VLPs), and nucleic acids to deliver and develop biomaterial-based vaccines. We also review design principles and key regulatory issues associated with their development. Finally, we critically assess their limitations, explore approaches to overcome these limitations, and discuss potential future applications for clinical translation.

Exploring the cancer-testis antigen BORIS to design a novel multi-epitope vaccine against breast cancer based on immunoinformatics approaches

Recently, cancer immunotherapy has gained lots of attention to replace the current chemoradiation approaches and multi-epitope cancer vaccines are manifesting as the next generation of cancer immunotherapy. Therefore, in this study, we used multiple immunoinformatics approaches along with other computational approaches to design a novel multi-epitope vaccine against breast cancer. The most immunogenic regions of the BORIS cancer-testis antigen were selected according to the binding affinity to MHC-I and II molecules as well as containing multiple cytotoxic T lymphocyte (CTL) epitopes by multiple immunoinformatics servers. The selected regions were linked together by GPGPG linker. Also, a T helper epitope (PADRE) and the TLR-4/MD-2 agonist (L7/L12 ribosomal protein from mycobacterium) were incorporated by A(EAAAK)3A linker to form the final vaccine construct. Then, its physicochemical properties, cleavage sites, TAP transport efficiency, B cell epitopes, IFN-γ inducing epitopes and population coverage were predicted. The final vaccine construct was reverse translated, codon-optimized and inserted into pcDNA3.1 to form the DNA vaccine. The final vaccine construct was a stable, immunogenic and non-allergenic protein that contained numerous CTL epitopes, IFN-γ inducing epitopes and several linear and conformational B cell epitopes. Also, the final vaccine construct formed stable and significant interactions with TLR-4/MD-2 complex according to molecular docking and dynamics simulations. Moreover, its world population coverage for HLA-I and HLA-II were about 93% and 96%, respectively. Taking together, these preliminary results can be used as an appropriate platform for further experimental investigations.Communicated by Ramaswamy H. Sarma.

A computational study to disclose potential drugs and vaccine ensemble for COVID-19 conundrum

The nucleocapsid (N) protein of SARS-COV-2, a virus responsible for the current COVID-19 pandemic, is considered a potential candidate for the design of new drugs and vaccines. The protein is central to several critical events in virus production, with its highly druggable nature and rich antigenic determinants making it an excellent anti-viral biomolecule. Docking-based virtual screening using the Asinex anti-viral library identified binding of drug molecules at three specific positions: loop 1 region, loop 2 region and β-sheet core pockets, the loop 2 region being the most common binding and stable site for the bulk of the molecules. In parallel, the protein was characterized by vaccine design perspective and harboured three potential B cell-derived T cell epitopes: PINTNSSPD, GVPINTNSS, and DHIGTRNPA. The epitopes are highly antigenic, virulent, non-allergic, non-toxic, bind with good affinity to the highly prevalent DRB*0101 allele and show an average population coverage of 95.04%. A multi-epitope vaccine ensemble which was 83 amino acids long was created. This was highly immunogenic, robust in generating both humoral and cellular immune responses, thermally stable, and had good physicochemical properties that could be easily analyzed in in vivo and in vitro studies. Conformational dynamics of both drug and vaccine ensemble with respect to the receptors are energetically stable, shedding light on favourable conformation and chemical interactions. These facts were validated by subjecting the complexes to relative and absolute binding free energy methods of MMGB/PBSA and WaterSwap. A strong agreement on the system stability was disclosed that supported ligand high affinity potential for the receptors. Collectively, this work sought to provide preliminary experimental data of existing anti-viral drugs as a possible therapy for COVID-19 infections and a new peptide-based vaccine for protection against this pandemic virus.