Identification and Design of a Next-Generation Multi Epitopes Bases Peptide Vaccine Candidate Against Prostate Cancer: An In Silico Approach

The Role of ERα and ERβ in Castration-Resistant Prostate Cancer and Current Therapeutic Approaches

Castration-resistant prostate cancer, or CRPC, is an aggressive stage of prostate cancer (PCa) in which PCa cells invade nearby or other parts of the body. When a patient with PCa goes through androgen deprivation therapy (ADT) and the cancer comes back or worsens, this is called CRPC. Instead of androgen-dependent signalling, recent studies show the involvement of the estrogen pathway through the regulation of estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ) in CRPC development. Reduced levels of testosterone due to ADT lead to low ERβ functionality in inhibiting the proliferation of PCa cells. Additionally, ERα, which possesses androgen independence, continues to promote the proliferation of PCa cells. The functions of ERα and ERβ in controlling PCa progression have been studied, but further research is needed to elucidate their roles in promoting CRPC. Finding new ways to treat the disease and stop it from becoming worse will require a clear understanding of the molecular processes that can lead to CRPC. The current review summarizes the underlying processes involving ERα and ERβ in developing CRPC, including castration-resistant mechanisms after ADT and available medication modification in mitigating CRPC progression, with the goal of directing future research and treatment.

Predicting epitopes for vaccine development using bioinformatics tools

Epitope-based DNA vaccine development is one application of bioinformatics or in silico studies, that is, computational methods, including mathematical, chemical, and biological approaches, which are widely used in drug development. Many in silico studies have been conducted to analyze the efficacy, safety, toxicity effects, and interactions of drugs. In the vaccine design process, in silico studies are performed to predict epitopes that could trigger T-cell and B-cell reactions that would produce both cellular and humoral immune responses. Immunoinformatics is the branch of bioinformatics used to study the relationship between immune responses and predicted epitopes. Progress in immunoinformatics has been rapid and has led to the development of a variety of tools that are used for the prediction of epitopes recognized by B cells or T cells as well as the antigenic responses. However, the in silico approach to vaccine design is still relatively new; thus, this review is aimed at increasing understanding of the importance of in silico studies in the design of vaccines and thereby facilitating future research in this field.

In-Silico Vaccine Design Based on a Novel Vaccine Candidate Against Infections Caused by Acinetobacter baumannii

Acinetobacter baumannii is notorious for causing serious infections of the skin, lungs, soft tissues, bloodstream, and urinary tract. Despite the overwhelming information available so far, there has still been no approved vaccine in the market to prevent these infections. Therefore, this study focuses on developing a rational vaccine design using the technique of epitope mapping to curb the infections caused by A. baumannii. An outer membrane protein with immunogenic potential as well as all the properties of a good vaccine candidate was selected and used to calculate epitopes for selection on the basis of a low percentile rank, high binding scores, good immunological properties, and non-allergenicity. Thus, a 240 amino-acid vaccine sequence was obtained by manually joining all the epitopes in sequence-wise manner with the appropriate linkers, namely AAY, GPGPG, and EAAAK. Additionally, a 50S ribosomal protein L7/L12, agonist to the human innate immune receptors was attached to the N-terminus to increase the overall immune response towards the vaccine. As a result, enhanced overall protein stability, expression, immunostimulatory capabilities, and solubility of the designed construct were observed. Molecular dynamic simulations revealed the compactness and stability of the polypeptide construct. Moreover, molecular docking exhibited strong binding of the designed vaccine with TLR-4 and TLR-9. In-silico immune simulations indicated an immense increment in T-cell and B-cell populations. Bioinformatic tools also significantly assisted with optimizing codons which allowed for successful cloning of constructs into desired host vectors. Using in-silico tools to design a vaccine against A. baumannii demonstrated that this construct could pave the way for successfully combating infections caused by multidrug-resistant bacteria.

Evaluation and Designing of Epitopic-Peptide Vaccine Against Bunyamwera orthobunyavirus Using M-Polyprotein Target Sequences

Bunyamwera orthobunyavirus and its serogroup can cause several diseases in humans, cattle, ruminants, and birds. The viral M-polyprotein helps the virus to enter the host body. Therefore, this protein might serve as a potential vaccine target against Bunyamwera orthobunyavirus. The present study applied the immunoinformatics technique to design an epitopic vaccine component that could protect against Bunyamwera infection. Phylogenetic analysis revealed the presence of conserved patterns of M-polyprotein within the viral serogroup. Three epitopes common for both B-cell and T-cell were identified, i.e., YQPTELTRS, YKAHDKEET, and ILGTGTPKF merged with a specific linker peptide to construct an active vaccine component. The low atomic contact energy value of docking complex between human TLR4 (TLR4/MD2 complex) and vaccine construct confirms the elevated protein–protein binding interaction. Molecular dynamic simulation and normal mode analysis illustrate the docking complex’s stability, especially by the higher Eigenvalue. In silico cloning of the vaccine construct was applied to amplify the desired vaccine component. Structural allocation of both the vaccine and epitopes also show the efficacy of the developed vaccine. Hence, the computational research design outcomes support that the peptide-based vaccine construction is a crucial drive target to limit the infection of Bunyamwera orthobunyavirus to an extent.

Biopolymer and Biomaterial Conjugated Iron Oxide Nanomaterials as Prostate Cancer Theranostic Agents: A Comprehensive Review

Prostate cancer (PCa) is the most common malignancy in men and the leading cause of death for men all over the world. Early diagnosis is the key to start treatment at an early stage of PCa and to reduce the death toll. Generally, PCa expresses characteristic morphologic features and serum biomarkers; however, early diagnosis is challenging due to its heterogeneity and long-term indolent phase in the early stage. Following positive diagnosis, PCa patients receive conventional treatments including surgery, radiation therapy, androgen deprivation therapy, focal therapy, and chemotherapy to enhance survival time and alleviate PCa-related complications. However, these treatment strategies have both short and long-term side effects, notably impotence, urinary incontinence, erectile dysfunctions, and recurrence of cancer. These limitations warrant the quest for novel PCa theranostic agents with robust diagnostic and therapeutic potentials to lessen the burden of PCa-related suffering. Iron oxide nanoparticles (IONPs) have recently drawn attention for their symmetrical usage in the diagnosis and treatment of several cancer types. Here, we performed a systematic search in four popular online databases (PubMed, Google Scholar, Scopus, and Web of Science) for the articles regarding PCa and IONPs. Published literature confirmed that the surface modification of IONPs with biopolymers and diagnostic biomarkers improved the early diagnosis of PCa, even in the metastatic stage with reliable accuracy and sensitivity. Furthermore, fine-tuning of IONPs with biopolymers, nucleic acids, anticancer drugs, and bioactive compounds can improve the therapeutic efficacy of these anticancer agents against PCa. This review covers the symmetrical use of IONPs in the diagnosis and treatment of PCa, investigates their biocompatibility, and examines their potential as PCa theranostic agents.

A Novel Multi-Epitopic Peptide Vaccine Candidate Against Helicobacter pylori: In-Silico Identification, Design, Cloning and Validation Through Molecular Dynamics

Helicobacter pylori is a highly potential pathogen to colonize in the human stomach. This bacterial strain is now alarming serious health concern all over the world. Combating through available drugs is a difficult task due to lack of appropriate common targets against genetically diverse strains. Therefore, the developments of effective targets vaccines require alternative strategies to eliminate the H. pylori infection. In this study, we developed a novel vaccine construct using B-cell derived T-cell epitopes from four target antigenic proteins (HpaA, FlaA, FlaB and Omp18), and found the induction of possible immune response using advanced immunoinformatics approaches. In order to boost immune system, we tagged adjuvant (50S ribosomal protein L7/L12) with a suitable linker at the N-terminus side of vaccine sequence. Protein–protein docking between human Toll like receptor 5 (TLR5) and vaccine construct help to predict the way of inductive signaling that leads to immune-response. The calculated negative score (− 151.4, + / − 8.7) of molecular docking complex signify the best binding interface. Molecular dynamics simulation studies confirmed the proper docking between TLR5 and vaccine candidate. Moreover, Normal mode analysis (NMA) calculates the molecular motion of the docking complex. The low eigenvalue (2.935e⁻⁰⁵) indicates the stable and flexible molecular motion in the binding interaction side. Finally, in-silico cloning of vaccine candidate was performed using expression vector pET28b (+) with the optimized restriction sites.

In-silico identification of subunit vaccine candidates against lung cancer-associated oncogenic viruses

Globally, ~20% of cancer malignancies are associated with virus infections. Lung cancer is the most prevalent cancer and has a 10% 5-year survival rate when diagnosed at stage IV. Cancer vaccines and oncolytic immunotherapy are promising treatment strategies for better clinical outcomes in advanced-stage cancer patients. Here, we used a reverse vaccinology approach to devise subunit vaccine candidates against lung cancer-causing oncogenic viruses. Protein components (945) from nine oncogenic virus species were systematically analyzed to identify epitope-based subunit vaccine candidates. Best vaccine candidates were identified based on their predicted ability to stimulate humoral and cell-mediated immunity and avoid self-tolerance. Using a rigorous integrative approach, we identified 125 best antigenic epitopes with predicted B-cell, T-cell, and/or MHC-binding capability and vaccine adjuvant potential. Thirty-two of these antigenic epitopes were predicted to have IL-4/IFN-gamma inducing potential and IL-10 non-inducing potential and were predicted to bind 15 MHC-type I and 49 MHC-type II alleles. All 32 epitopes were non-allergenic and 31 were non-toxic. The identified epitopes showed good conservancy and likely bind a broad class of human HLA alleles, indicating promiscuous potential. The majority of best antigenic epitopes were derived from Human papillomavirus and Epstein-Barr virus proteins. Of the 32 epitopes, 25 promiscuous epitopes were related to E1 and E6 envelope genes and were present in multiple viral strains/species, potentially providing heterologous immunity. Further validating our results, 38 antigenic epitopes were also present in the largest experimentally-validated epitope resource, Immune Epitope Database and Analysis Resource. We further narrowed the selection to 29 antigenic epitopes with the highest immunogenic/immune-boosting potential. These epitopes possess tremendous therapeutic potential as vaccines against lung cancer-causing viruses and should be validated in future experiments. All findings are available at https://webs.iiitd.edu.in/raghava/vlcvirus/.

Designing of a novel multi-epitope peptide based vaccine against Brugia malayi: An in silico approach

In spite of the tremendous efforts of the World Health Organization, scientific and medical community to eradicate lymphatic filariasis (LF) within 2020, the disease is still taking a huge toll on mankind throughout the globe. The current therapeutic strategies and solution measures against this alarming condition are suffering from a number of limitations such as inadequate effectiveness of the drugs against the adult-stage parasites, low bioavailability, and emergence of resistance. Considering this situation, development of the new therapeutics are urgently needed to combat human LF, especially targeting the adult filarial nematodes. Brugia malayi, the causative parasite for the human brugian filariasis majorly found in the countries of the South-Asia. In this study, we have designed a vaccine candidate using B-cell and T-cell epitopes derived from the aspartic protease of B. malayi (BmASP-1) and found to display significant humoral and cell mediated immune responses using in-silico approaches. Protein-protein docking between the human Toll-like receptor 4 (TLR4) and the vaccine candidate helped us to predict the way of inductive signaling that leads to immune-response. Molecular dynamics (MD) simulation studies further confirmed the proper docking between the TLR4 and vaccine candidate. Moreover, in-silico cloning of the vaccine element within the expression vector was found useful to optimize the restriction sites as well as to determine the primer location. Taken together, the in-silico vaccine candidate depicted in this study promises could be a useful therapeutic option for treating LF and experimental validation of this study is expected to strengthen the candidature of the said vaccine in the future.