Immunoinformatics Approach to Design Multi-Epitope-Based Vaccine against Machupo Virus Taking Viral Nucleocapsid as a Potential Candidate

Integrating 16S rRNA profiling and in-silico analysis for an epitope-based vaccine strategy against Achromobacter xylosoxidans infection

Achromobacter xylosoxidans is an aerobic, catalase-positive, non-pigment-forming, Gram-negative, and motile bacterium. It potentially causes a wide range of human infections in cystic fibrosis and non-cystic fibrosis patients. However, developing a safe preventive or therapeutic solution against A. xylosoxidans remains challenging. This study aimed to construct an epitope-based vaccine candidate using immunoinformatic techniques. A. xylosoxidans was isolated from an auto workshop in Lahore, and its identification was confirmed through 16S rRNA amplification and bioinformatic analysis. Two protein targets with GenBank accession numbers AKP90890.1 and AKP90355.1 were selected for the vaccine construct. Both proteins exhibited antigenicity, with scores of 0.757 and 0.580, respectively and the epitopes were selected based on the IC50 value using the ANN 4.0 and NN-align 2.3 epitope prediction method for MHC I and MHC II epitopes respectively and predicted epitopes were analyzed for antigenicity, allergenicity and pathogenicity. The vaccine construct demonstrated structural stability, thermostability, solubility, and hydrophilicity. The vaccine produced 250 B-memory cells per mm3 and approximately 16,000 IgM + IgG counts, indicating an effective immune response against A. xylosoxidans. Moreover, the vaccine candidate interacted stably with toll-like receptor 5, a pattern recognition receptor, with a confidence score of 0.98. These results highlight the potency of the designed vaccine candidate, suggesting its potential to withstand rigorous in vitro and in vivo clinical trials. This epitope-based vaccine could serve as the first preventive immunotherapy against A. xylosoxidans infections, addressing this bacterium's health and financial burdens. The findings demonstrate the value of employing immunoinformatic tools in vaccine development, paving the way for more precise and tailored approaches to combating microbial threats.

Emerging Trends of Gold Nanostructures for Point-of-Care Biosensor-Based Detection of COVID-19

In 2019, a worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged. SARS-CoV-2 is the deadly microorganism responsible for coronavirus disease 2019 (COVID-19), which has caused millions of deaths and irreversible health problems worldwide. To restrict the spread of SARS-CoV-2, accurate detection of COVID-19 is essential for the identification and control of infected cases. Although recent detection technologies such as the real-time polymerase chain reaction delivers an accurate diagnosis of SARS-CoV-2, they require a long processing duration, expensive equipment, and highly skilled personnel. Therefore, a rapid diagnosis with accurate results is indispensable to offer effective disease suppression. Nanotechnology is the backbone of current science and technology developments including nanoparticles (NPs) that can biomimic the corona and develop deep interaction with its proteins because of their identical structures on the nanoscale. Various NPs have been extensively applied in numerous medical applications, including implants, biosensors, drug delivery, and bioimaging. Among them, point-of-care biosensors mediated with gold nanoparticles (GNPSs) have received great attention due to their accurate sensing characteristics, which are widely used in the detection of amino acids, enzymes, DNA, and RNA in samples. GNPS have reconstructed the biomedical application of biosensors because of its outstanding physicochemical characteristics. This review provides an overview of emerging trends in GNP-mediated point-of-care biosensor strategies for diagnosing various mutated forms of human coronaviruses that incorporate different transducers and biomarkers. The review also specifically highlights trends in gold nanobiosensors for coronavirus detection, ranging from the initial COVID-19 outbreak to its subsequent evolution into a pandemic.

Targeting human inosine 5' monophosphate dehydrogenase type 2 for anti-dengue lead identification - a computational approach

Dengue is a rapidly evolving arboviral disease that mainly affects tropical and subtropical regions of the world. The lack of therapeutic drugs and effective vaccines suggests that further resources need to be investigated. The effectiveness of the existing dengue vaccine is improbable as its efficacy depends on prior exposure to the dengue virus(DENV). Although the mechanism underlying the action of bioactive compounds to limit viral replication is less studied and still needs to be further explored, medicinal plants are excellent alternatives to combat DENV infection. In the current study, an in silico screening of phytochemicals from Annona reticulata Linn. against human Impdh2 was performed using Autodock Vina. Daucosterol (-9.0 kcal/mol) and Kaurenoic acid (-8.5 kcal/mol) were chosen as the top hits based on molecular interaction analysis. The hits were further exposed to pharmacokinetics and toxicity properties to determine their drug-like parameters. Molecular dynamics simulation studies of the Impdh2-top hits were carried out to investigate their kinetic behaviour and structural stabilities. The binding free energies of the Impdh2-hit complexes were determined using MM-PBSA analysis. According to the overall conclusions of the study, Daucosterol showed good binding affinity and high structural stability to the binding site residues of the target, therefore it is recommended as a lead compound against dengue.Communicated by Ramaswamy H. Sarma.

Computational insights into pediatric adenovirus inhibitors: in silico strategies for drug repurposing

Human adenovirus (HADV) infection can pose a serious threat to children, leading to a variety of respiratory illnesses and other complications. Particularly, children with weak immune systems are vulnerable to severe adenovirus infections with high mortality. The main focus of this study is to propose new antiviral agents as lead HADV inhibitors for children. So, several antiviral agents used in children were subjected to finding new HADV inhibitors using important computational methods of molecular docking, molecular dynamics (MD) simulation, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) binding free energy calculations, density functional theory (DFT), and pharmacokinetic analysis. Molecular docking of standard cidofovir along with other ligands, suggested that sofosbuvir has the highest binding energy (-10.8 kcal/mol), followed by baloxavir marboxil (-10.36 kcal/mol). Further, the analysis of molecular interactions using MD simulation (100 ns) and MM-PBSA indicated that baloxavir marboxil has formed the most stable protein-ligand complex with HADV, followed by sofosbuvir. The binding free energies of baloxavir marboxil and sofosbuvir were found to be -61.724 kJ/mol and -48.123 kJ/mol, respectively. The DFT and drug-likeness properties of these compounds were also investigated. Overall, two antiviral agents, such as baloxavir marboxil, and sofosbuvir are suggested as lead repurposed candidates against HADV.Communicated by Ramaswamy H. Sarma.

Identification of Bacterial Strains and Development of anmRNA-Based Vaccine to Combat Antibiotic Resistance in Staphylococcus aureus via In Vitro and In Silico Approaches

The emergence of antibiotic-resistant microorganisms is a significant concern in global health. Antibiotic resistance is attributed to various virulent factors and genetic elements. This study investigated the virulence factors of Staphylococcus aureus to create an mRNA-based vaccine that could help prevent antibiotic resistance. Distinct strains of the bacteria were selected for molecular identification of virulence genes, such as spa, fmhA, lukD, and hla-D, which were performed utilizing PCR techniques. DNA extraction from samples of Staphylococcus aureus was conducted using the Cetyl Trimethyl Ammonium Bromide (CTAB) method, which was confirmed and visualized using a gel doc; 16S rRNA was utilized to identify the bacterial strains, and primers of spa, lukD, fmhA, and hla-D genes were employed to identify the specific genes. Sequencing was carried out at Applied Bioscience International (ABI) in Malaysia. Phylogenetic analysis and alignment of the strains were subsequently constructed. We also performed an in silico analysis of the spa, fmhA, lukD, and hla-D genes to generate an antigen-specific vaccine. The virulence genes were translated into proteins, and a chimera was created using various linkers. The mRNA vaccine candidate was produced utilizing 18 epitopes, linkers, and an adjuvant, known as RpfE, to target the immune system. Testing determined that this design covered 90% of the population conservancy. An in silico immunological vaccine simulation was conducted to verify the hypothesis, including validating and predicting secondary and tertiary structures and molecular dynamics simulations to evaluate the vaccine’s long-term viability. This vaccine design may be further evaluated through in vivo and in vitro testing to assess its efficacy.

Particle Nanoarchitectonics for Nanomedicine and Nanotherapeutic Drugs with Special Emphasis on Nasal Drugs and Aging

Aging is a multifunctional physiological manifestation. The nasal cavity is considered a major site for easy and cost-effective drug and vaccine administration, due to high permeability, low enzymatic activity, and the presence of a high number of immunocompetent cells. This review article primarily focuses on aging genetics, physical parameters, and the use of nanoparticles as delivery systems of drugs and vaccines via the nasal cavity. Studies have identified various genes involved in centenarian and average-aged people. VEGF is a key mediator involved in angiogenesis. Different therapeutic approaches induce vascular function and angiogenesis. FOLR1 gene codes for folate receptor alpha protein that helps in regulating the transport of vitamin B folate, 5-methyltetrahydrofolate and folate analogs inside the cell. This gene also aids in slowing the aging process down by cellular regeneration and promotes healthy aging by reducing aging symptoms. It has been found through the literature that GATA 6, Yamanaka factors, and FOLR1 work in synchronization to induce healthy and delayed aging. The role and applications of genes including CBS, CISD, SIRT 1, and SIRT 6 play a significant role in aging.

Chain-Engineering-Based De Novo Drug Design against MPXVgp169 Virulent Protein of Monkeypox Virus: A Molecular Modification Approach

The unexpected appearance of the monkeypox virus and the extensive geographic dispersal of cases have prompted researchers to concentrate on potential therapeutic approaches. In addition to its vaccine build techniques, there should be some multiple integrated antiviral active compounds because of the MPV (monkeypox virus) outbreak in 2022. This study offers a computational engineering-based de novo drug discovery mediated by random antiviral active compounds that were screened against the virulent protein MPXVgp169, as one of the key players directing the pathogenesis of the virus. The screening of these candidates was supported by the use of 72 antiviral active compounds. The top candidate with the lowest binding affinity was selected for the engineering of chains or atoms. Literature assisted to identify toxic chains or atoms that were impeding the stability and effectiveness of antiviral compounds to modify them for enhanced efficacy. With a binding affinity of -9.4 Kcal/mol after chain, the lipophilicity of 0.41, the water solubility of 2.51 as soluble, and synthetic accessibility of 6.6, chain-engineered dolutegravir was one of the best active compounds, as proved by the computational engineering analysis. This study will revolutionize the era of drug engineering as a potential therapeutic strategy for monkeypox infection.