Evaluation of the Whole Proteome of Achromobacter xylosoxidans to Identify Vaccine Targets for mRNA and Peptides-Based Vaccine Designing Against the Emerging Respiratory and Lung Cancer-Causing Bacteria

Exploring the impact of taurine on the biochemical properties of urate oxidase: response surface methodology and molecular dynamics simulation

This paper investigates the impact of taurine as an additive on the structural and functional stability of urate oxidase. First, the effect of the processing parameters for the stabilization of Urate Oxidase (UOX) using taurine was examined using the response surface methodology (RSM) and the central composite design (CCD) model. Also, the study examines thermodynamic and kinetic parameters as well as structural changes of urate oxidase with and without taurine. Fluorescence intensity changes indicated static quenching during taurine binding. The obtained result indicates that taurine has the ability to preserve the native structural conformation of UOX. Furthermore, molecular dynamics simulation is conducted in order to get insights into the alterations in the structure of urate oxidase in the absence and presence of taurine under optimal conditions. The molecular dynamics simulation section investigated the formation of hydrogen bonds (H-bonds) between different components as well as analysis of root mean square deviation (RMSD), root mean square fluctuations (RMSF) and secondary structure. Lower Cα-RMSD and RMSF values indicate greater stabilization of the taurine-treated UOX structure compared to the free enzyme. The results of molecular docking indicate that the binding of taurine to the UOX enzyme through hydrophobic interactions is associated with a negative value for the Gibbs free energy.

Exploring and targeting potential druggable antimicrobial resistance targets ArgS, SecY, and MurA in Staphylococcus sciuri with TCM inhibitors through a subtractive genomics strategy

Staphylococcus sciuri (also currently Mammaliicoccus sciuri) are anaerobic facultative and non-motile bacteria that cause significant human pathogenesis such as endocarditis, wound infections, peritonitis, UTI, and septic shock. Methicillin-resistant S. sciuri (MRSS) strains also infects animals that include healthy broilers, cattle, dogs, and pigs. The emergence of MRSS strains thereby poses a serious health threat and thrives the scientific community towards novel treatment options. Herein, we investigated the druggable genome of S. sciuri by employing subtractive genomics that resulted in seven genes/proteins where only three of them were predicted as final targets. Further mining the literature showed that the ArgS (WP_058610923), SecY (WP_058611897), and MurA (WP_058612677) are involved in the multi-drug resistance phenomenon. After constructing and verifying the 3D protein homology models, a screening process was carried out using a library of Traditional Chinese Medicine compounds (consisting of 36,043 compounds). The molecular docking and simulation studies revealed the physicochemical stability parameters of the docked TCM inhibitors in the druggable cavities of each protein target by identifying their druggability potential and maximum hydrogen bonding interactions. The simulated receptor-ligand complexes showed the conformational changes and stability index of the secondary structure elements. The root mean square deviation (RMSD) graph showed fluctuations due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points where the pattern of the RMSD and root mean square fluctuation (RMSF) (< 1.0 Å) support any major domain shifts within the structural framework of the protein-ligand complex and placement of ligand was well complemented within the binding site. The β-factor values demonstrated instability at few points while the radius of gyration for structural compactness as a time function for the 100-ns simulation of protein-ligand complexes showed favorable average values and denoted the stability of all complexes. It is assumed that such findings might facilitate researchers to robustly discover and develop effective therapeutics against S. sciuri alongside other enteric infections.

Advances in Computational and Bioinformatics Tools and Databases for Designing and Developing a Multi-Epitope-Based Peptide Vaccine

A vaccine is defined as a biologic preparation that trains the immune system, boosts immunity, and protects against a deadly microbial infection. They have been used for centuries to combat a variety of contagious illnesses by means of subsiding the disease burden as well as eradicating the disease. Since infectious disease pandemics are a recurring global threat, vaccination has emerged as one of the most promising tools to save millions of lives and reduce infection rates. The World Health Organization reports that immunization protects three million individuals annually. Currently, multi-epitope-based peptide vaccines are a unique concept in vaccine formulation. Epitope-based peptide vaccines utilize small fragments of proteins or peptides (parts of the pathogen), called epitopes, that trigger an adequate immune response against a particular pathogen. However, conventional vaccine designing and development techniques are too cumbersome, expensive, and time-consuming. With the recent advancement in bioinformatics, immunoinformatics, and vaccinomics discipline, vaccine science has entered a new era accompanying a modern, impressive, and more realistic paradigm in designing and developing next-generation strong immunogens. In silico designing and developing a safe and novel vaccine construct involves knowledge of reverse vaccinology, various vaccine databases, and high throughput techniques. The computational tools and techniques directly associated with vaccine research are extremely effective, economical, precise, robust, and safe for human use. Many vaccine candidates have entered clinical trials instantly and are available prior to schedule. In light of this, the present article provides researchers with up-to-date information on various approaches, protocols, and databases regarding the computational designing and development of potent multi-epitope-based peptide vaccines that can assist researchers in tailoring vaccines more rapidly and cost-effectively.

A multi-epitope based vaccine against the surface proteins expressed in cyst and trophozoite stages of parasite Entamoeba histolytica

Entamoeba histolytica, an anaerobic parasite, infects humans and other primates and causes fatal diseases, such as amebiasis, amebic liver abscesses, and many others. Thousands of people are infected and dying due to the need for a proper protective cure, especially in poor sanitizing regions, such as Latin America, Asia, and Africa. Around 10% of the world population is infected by E. histolytica every year. Consequently, novel preventive approaches are required to eliminate the threats of the parasite. A designed vaccine targeting the exposed proteins that are common between cyst and trophozoite stages of the parasite's life cycle would be an effective way to repress the impact of the parasite. Therefore, an in silico bioinformatics approach was performed to design an effective vaccine targeting surface proteins common between both stages of the parasite's life cycle using B-cell and T-cell epitopes. The epitopes derived from the conserved portions of the proteins and their corresponding isomers specific to the parasite suggested that the vaccine could benefit cross-protection. Furthermore, the three-dimensional structure of the designed vaccine was modelled, refined, and validated using multiple bioinformatics tools. The physiological properties and solubility were also predicted using different algorithmic tools and found to be highly soluble in nature. The vaccine was found interactcted with TLR immune receptors, and the stability was observed via dynamics simulation. Codon optimization and cloning were performed for expression analysis. Immune simulation prediction anticipated significant immune responses with a high IgG and IgM antibodies expression, Th and Tc cells population, B-cell population, memory cells, INF-γ, and IL-2 cytokines. Therefore, the constructed multi-epitope putative vaccine can effectively neutralize the parasite's harmful effects.

The Advantage of Using Immunoinformatic Tools on Vaccine Design and Development for Coronavirus

After the outbreak of SARS-CoV-2 by the end of 2019, the vaccine development strategies became a worldwide priority. Furthermore, the appearances of novel SARS-CoV-2 variants challenge researchers to develop new pharmacological or preventive strategies. However, vaccines still represent an efficient way to control the SARS-CoV-2 pandemic worldwide. This review describes the importance of bioinformatic and immunoinformatic tools (in silico) for guide vaccine design. In silico strategies permit the identification of epitopes (immunogenic peptides) which could be used as potential vaccines, as well as nonacarriers such as: vector viral based vaccines, RNA-based vaccines and dendrimers through immunoinformatics. Currently, nucleic acid and protein sequential as well structural analyses through bioinformatic tools allow us to get immunogenic epitopes which can induce immune response alone or in complex with nanocarriers. One of the advantages of in silico techniques is that they facilitate the identification of epitopes, while accelerating the process and helping to economize some stages of the development of safe vaccines.

Subtractive proteomics assisted therapeutic targets mining and designing ensemble vaccine against Candida auris for immune response induction

The emergence of variants and the reports of co-infection caused by Candida auris in COVID-19 patients adds a further complication to the global pandemic situation. To date, no effective therapy is available for C. auris infections. Thus, characterization of therapeutic targets and designing effective vaccine candidates using subtractive proteomics and immune-informatics approaches is useful tool in controlling the emerging infections associated with SARS-CoV-2. In the current study, subtractive proteomics-assisted annotation of the vaccine targets was performed, which revealed seven vaccine targets. An immunoinformatic-driven approach was then employed to map protein-specific and proteome-wide immunogenic peptides (CTL, B cell, and HTL) for the design of multi-epitope vaccine candidates (MEVCs). The results demonstrated that the vaccine candidates possess strong antigenic features (>0.4 threshold score) and are classified as non-allergenic. Validation of the designed MEVCs through molecular docking, in-silico cloning, and immune simulation further demonstrated the efficacy of the vaccines by producing immune factor titers (ranging from 2500 to 16000 au/mL) i.e., IgM, IgG, IL-6, and Interferon-α. In conclusion, the current study provides a strong impetus in designing anti-fungal strategies against Candida auris.

Whole Proteome-Based Therapeutic Targets Annotation and Designing of Multi-Epitope-Based Vaccines against the Gram-Negative XDR-Alcaligenes faecalis Bacterium

This study involved therapeutic targets mining for the extremely drug-resistant bacterial species called Alcaligenes faecalis, which is known to infect humans. The infections caused by this species in different parts of the human body have been linked with a higher degree of resistance to several classes of antibiotics. Meanwhile, alternate therapeutic options are needed to treat these bacterial infections in clinical settings. In the current study, a subtractive proteomics approach was adapted to annotate the whole proteome of Alcaligenes faecalis and prioritize target proteins for vaccine-related therapeutics design. This was followed by targeted protein-specific immune epitope prediction and prioritization. The shortlisted epitopes were further subjected to structural design and in silico validation of putative vaccines against Alcaligenes faecalis. The final vaccine designs were also evaluated for potential interaction analysis with human TLR-2 through molecular docking. Finally, the putative vaccines were subjected to in silico cloning and immune simulation approaches to ensure the feasibility of the target-specific vaccine constructs in further experimental designs.