Assessing the efficacy of cinnamon compounds against H. pylori through molecular docking, MD Simulations and ADMET analyses.

Antibiotics are the drugs that are used for the management of microbial diseases. However, these conventional synthetic drugs can harmfully affect the human health. Since phytochemicals are extracted from natural sources and, are hence relatively safer for human health, they are the enticing alternatives in this regard. Cinnamon is also one of those plants which is being employed as herbal medication for centuries against certain microbial infections due its significant therapeutic effectiveness. A well-known pathogenic bacterium called H. pylori causes a wide range of illnesses in human body. This pathogen's pathogenicity is determined by certain virulent proteins. In this study, some of such proteins, which included virB4, virB8, and virB9 were selected to evaluate the therapeutic efficiency of cinnamon compounds. These proteins were identified in different isolates of H. pylori. The structural modelling of all these proteins were performed initially in order to proceed them for molecular docking analysis. While, the docking studies illustrated that one of the cinnamon compounds, cinnamyl acetate, showed significant binding interactions with virB4 and virB9. However, benzyl benzoate which is another cinnamon compound, docked well with virB8. Afterwards, the MD simulations were incorporated to explore the interaction motions and structural stability of all the docked complexes. In this regard, the resultant maps of Bfactor, eigenvalues and elastic network model, among other factors ensured the structural stabilities of all the respective complexes. After these crucial estimations, benzyl benzoate and cinnamyl acetate underwent the ADMET investigation to assess their pharmacokinetic characteristics. SwissADME and ADMETLab 2.0 server were employed for this investigation. The compiled findings these servers revealed that both, benzyl benzoate and cinnamyl acetate, exhibited a significant level of pharmacokinetic and drug-likeness conformity.

In-silico characterization of LSDV132 protein divulged its BCL-2-like nature.

Lumpy skin disease virus (LSDV) belongs to Poxviridae family. This virus possesses various proteins which impart potential functions to it including assembly of newly synthesized viruses in the replication cycle and forming their structure. LSDV132 protein is also one of such proteins. Its key characteristics were unknown because, no any relevant study was reported about it. This study aimed to investigate its characteristic features and essential functions using several bioinformatics techniques. These analyses included physiochemical characterization and exploring the crucial functional and structural perspectives. Upon analysis of the physiochemical properties, the instability index was computed to be 30.89% which proposed LSDV132 protein to be a stable protein. Afterwards, the phosphorylation sites were explored. Several sites were found in this regard which led to the hypothesis that it might be involved in the regulation of apoptosis and cell signaling, among other cellular processes. Furthermore, the KEGG analysis and the analysis of protein family classification confirmed that the LSDV132 protein possessed Poxvirus-BCL-2-like motifs, indicating that it might be responsible in modulating the apoptosis of host cells. This crucial finding suggested that the protein under study possessed BCL-2-like features. Proceeding this very important finding, the molecular docking analysis was performed. In this context, various viral BCL-2 inhibitors were retrieved from the ChEMBL database for docking purpose. The docking results revealed that pelcitoclax exhibited best docking scores i.e., -9.1841 kcal/mol, among all of the other docked complexes. This fact signified that this compound might serve as an inhibitor of LSDV132 protein.

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.