Background: Mammalian orthoreovirus is a ubiquitous double-stranded RNA virus that causes mild respiratory and enteric infections, primarily in infants and young children. Its significant environmental stability and association with conditions like celiac disease highlight an unmet medical need, as no licensed vaccine or antiviral treatment currently exist. Methods: An immunoinformatics-driven approach was employed to design a multi-epitope vaccine. The highly antigenic inner capsid protein Sigma-2 was used to predict cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and linear B cell epitopes using NetCTL, NetMHCpan, NetMHCIIpan, and IEDB tools. Selected epitopes were fused with appropriate linkers. The construct’s antigenicity, allergenicity, and physicochemical properties were evaluated. The tertiary structure was predicted with AlphaFold2, refined, and validated. Molecular docking with TLR2 and TLR4 was performed using HDOCK, and immune response simulation was conducted with C-ImmSim. Finally, the sequence was codon-optimized for E. coli expression using JCat. Results: The final vaccine construct comprises one CTL, four HTLs, and one B cell epitope. It is antigenic (VaxiJen score: 0.5026), non-allergenic, and non-toxic and possesses favorable physicochemical properties, including stability (instability index: 32.28). Molecular docking revealed exceptionally strong binding to key immune receptors, particularly TLR2 (docking score: −324.37 kcal/mol). Immune simulations predicted robust antibody production (elevated IgM, IgG1, and IgG2) and lasting memory cell formation. Codon optimization yielded an ideal CAI value of 0.952 and a GC content of 57.15%, confirming high potential for recombinant expression. Conclusions: This study presents a novel multi-epitope vaccine candidate against reovirus, designed to elicit broad cellular and humoral immunity. Comprehensive in silico analyses confirm its structural stability, potent interaction with innate immune receptors, and high potential for expression. These findings provide a strong rationale for further wet-lab studies to validate its efficacy and advance it as a promising prophylactic candidate.

Background: Oropouche virus (OROV), part of the Peribunyaviridae family, is an emerging pathogen causing Oropouche fever, a febrile illness endemic in South and Central America. Transmitted primarily through midge bites (Culicoides paraensis), OROV has no specific antiviral treatment or vaccine. This study aims to identify host-targeted therapeutics against OROV using computational approaches, offering a potential strategy for sustainable antiviral drug discovery. Methods: Virus-associated host targets were identified using the OMIM and GeneCards databases. The Enrichr and DSigDB platforms were used for drug prediction, filtering compounds based on Lipinski’s rule for drug likeness. A protein–protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape 3.10.3 software. Four key host targets—IL10, FASLG, PTPRC, and FCGR3A—were prioritized based on their roles in immune modulation and OROV pathogenesis. Molecular docking simulations were performed using the PyRx software to evaluate the binding affinities of selected small-molecule inhibitors—Acetohexamide, Deptropine, Methotrexate, Retinoic Acid, and 3-Azido-3-deoxythymidine—against the identified targets. Results: The PPI network analysis highlighted immune-mediated pathways such as Fc-gamma receptor signaling, cytokine control, and T-cell receptor signaling as critical intervention points. Molecular docking revealed strong binding affinities between the selected compounds and the prioritized targets, suggesting their potential efficacy as host-targeting antiviral candidates. Acetohexamide and Deptropine showed strong binding to multiple targets, indicating broad-spectrum antiviral potential. Further in vitro and in vivo validations are needed to confirm these findings and translate them into clinically relevant treatments. Conclusions: This study highlights the potential of using computational approaches to identify host-targeted therapeutics for Oropouche virus (OROV). By targeting key host proteins involved in immune modulation—IL10, FASLG, PTPRC, and FCGR3A—the selected compounds, Acetohexamide and Deptropine, demonstrate strong binding affinities, suggesting their potential as broad-spectrum antiviral candidates. Further experimental validation is needed to confirm their efficacy and potential for clinical application, offering a promising strategy for sustainable antiviral drug discovery.

Integrative bioinformatics and molecular docking unveil multi-target therapeutic mechanisms of Coptidis Rhizoma (CR) against Lewy body dementia (LBD): an in-silico approach

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impairments in social interaction and communication. According to recent research, neuroinflammation may play a role in the pathogenesis of ASD. Curcumin, the active compound in turmeric, has been demonstrated to exhibit neuroprotective, antioxidant, and anti-inflammatory properties. This review summarizes the potential mechanisms by which curcumin may influence the inflammatory pathways implicated in ASD. Curcumin can suppress nuclear factor kappa-light-chain-enhancer of activated B-cell activation, thereby reducing the levels of pro-inflammatory cytokines. In addition, it can protect mitochondrial function, upregulate antioxidant enzymes, scavenge reactive oxygen and nitrogen species, and modulate the gut–brain axis. Animal studies have shown that curcumin can improve sociability, repetitive behaviors, and enhance cognitive function in ASD models. The beneficial effects of curcumin supplementation on autism symptoms have also been documented in several small clinical trials involving children with ASD. Overall, curcumin is a natural compound with the potential to modulate neuroinflammatory pathways implicated in ASD; however, its therapeutic role remains under investigation.

The rapid emergence of multidrug-resistant Klebsiella pneumoniae has significantly reduced the effectiveness of conventional antibiotics, highlighting the need for alternative therapeutic strategies. This study employed a comprehensive in silico pipeline to identify antimicrobial peptides (AMPs) targeting the essential DNA replication initiator protein DnaA. A total of 28,361 peptide sequences were collected from publicly available AMP databases and sequentially filtered based on peptide length, net charge, GRAVY score, instability index, antimicrobial activity, toxicity, hemolytic potential, aggregation propensity, sequence similarity and favorable amphipathic properties. Four peptides satisfied all selection criteria and were subjected to structural prediction, membrane-binding analysis, protein–DNA docking, protein–peptide docking, and Normal Mode Analysis. Protein–DNA docking identified the functional DNA-binding residues of DnaA, while peptide docking demonstrated that all four peptides interacted within this region. Peptide 3 exhibited the strongest predicted interaction, with a binding energy of −61.8±5.1, a buried surface area of 1151.7±30.8 Å ² , and seven hydrogen bonds with key DnaA residues. Normal Mode Analysis further supported the structural stability of the peptide–protein complexes. These findings identify four promising AMP candidates targeting DnaA and provide a computational framework for peptide prioritization against multidrug-resistant K. pneumoniae . However, the proposed interactions remain computational predictions and require experimental validation.