Search Results (847)

Background/Objectives: Streptococcus suis is an important zoonotic pathogen responsible for severe infections in animals and humans, and the emergence of diverse strains has reduced the effectiveness of conventional antimicrobial therapies. Since there is no broadly protective vaccine, there is a need for new vaccination strategies that focus on conserved antigens from a variety of strains. This study aimed to design and evaluate a multi-epitope vaccine candidate against diverse S. suis strains using an integrated pangenome-guided reverse vaccinology approach. Methods: To design a multi-epitope vaccine (MEV) candidate against diverse S. suis, an integrated computational framework was employed, incorporating pangenome analysis, subtractive proteomics, reverse vaccinology, immunoinformatics, structural modeling, molecular docking, molecular dynamics simulation, immune simulation, and in silico cloning. The conserved core proteins were systematically screened for essential, non-homologous, antigenic, non-allergenic and non-toxic vaccine candidates for epitope prediction. Results: A total of 7421 gene families, including 1169 conserved core genes, were identified through pangenome analysis of 24 complete S. suis genomes. Three computationally prioritized candidate proteins were identified through sequential subtractive proteomics: sucrose phosphorylase, peptidoglycan hydrolase PcsB and an RND transporter-associated adaptor protein, annotated in the source database as an RND efflux transporter periplasmic adaptor subunit. We selected eight cytotoxic T-lymphocyte (CTL) epitopes, five helper T-lymphocyte (HTL) epitopes, and three linear B-cell epitopes with favorable predicted immunological properties to develop a 397-amino acid multi-epitope vaccine construct that contains the S. suis 50S ribosomal protein L7/L12 adjuvant with rationally designed peptide linkers. The vaccine construct exhibited favorable physicochemical properties, predicted structural stability, and high antigenicity scores. The predicted combined HLA population coverage of the selected CTL and HTL epitopes was 90.77% across the populations included in the analysis. Immune simulation predicted patterns consistent with humoral and cellular immune activation, including sustained IgG production, elevated IFN-γ and IL-2 secretion, efficient antigen clearance, and generation of immunological memory, whereas molecular docking and molecular dynamics simulations characterized the predicted interaction and conformational behavior of the MEV–TLR1/TLR2 complex. Codon optimization (CAI = 0.996) and in silico cloning into the pET-30a(+) expression vector supported the potential feasibility of recombinant expression in Escherichia coli. Conclusions: In this study, a rationally designed multi-epitope vaccine candidate against diverse S. suis strains was developed using an integrated pangenome-guided reverse vaccinology approach. Based on these computational analyses, the proposed vaccine candidate showed favorable predicted immunogenicity, predicted structural quality, predicted HLA population coverage, and expression feasibility, providing a foundation for future experimental validation and development of a vaccine against diverse S. suis. Full article

Usutu virus is an emerging mosquito-borne flavivirus with an expanding geographic distribution and increasing public health relevance, yet no licensed vaccine is currently available. This study used an integrated reverse vaccinology strategy to identify conserved immunogenic regions from the Envelope protein and NS5 protein, and construct a multi-epitope vaccine. Following sequential computational screening, the retained T-cell and B-cell epitopes satisfied the predefined selection criteria, while selected T-cell epitopes achieved an estimated 96.41% global population coverage. The final vaccine consisted of 240 amino acids and incorporated an adjuvant together with peptide linkers. Computational characterization indicated favorable physicochemical features and a refined three-dimensional model with improved stereochemical characteristics. Receptor-binding analyses predicted favorable interactions with TLR2 and TLR4, producing weighted docking scores of −1326.1 and −1230.2, respectively. Molecular dynamics simulation further characterized the temporal behavior of the vaccine–TLR2 complex, while MM-GBSA analysis yielded an estimated binding energy of −74.78 kcal/mol. C-ImmSim predicted enhanced humoral and cellular immune-response patterns following repeated antigen administration, including increased simulated antibody levels and changes in immune-cell populations. All findings in this study are based on in silico analyses and represent computational predictions rather than experimentally confirmed results. Further experimental validation is required to verify the predicted properties, immunogenicity, and protective potential of the proposed vaccine candidate. Full article

Background: Angiostrongylus cantonensis is a neurotropic nematode recognized as the leading cause of eosinophilic meningitis worldwide. Despite its growing medical importance, therapeutic options for angiostrongyliasis remain limited, highlighting the need for new anthelmintic agents. Methods: The anthelmintic activity of andrographolide, a diterpene lactone isolated from Cymbopogon schoenanthus, was evaluated against first-stage (L1) larvae, infective third-stage (L3) larvae, and adult worms of A. cantonensis using motility-based phenotypic assays. Toxicity was assessed in mammalian cell models and Caenorhabditis elegans, and drug-likeness and ADMET properties were evaluated using in silico approaches. Results: Andrographolide exhibited concentration-dependent activity across all developmental stages, with EC₅₀ values of 12.5, 11.2, and 7.3 µM for L1, L3, and adult worms, respectively. These EC₅₀ values were similar to those of albendazole, with no statistically significant differences detected for any developmental stage. No toxicity was detected at the highest concentrations tested in mammalian cell models (CC₅₀ > 500 µM) or C. elegans (LD₅₀ > 1000 µM), supporting a preliminary selectivity profile. The in silico analyses predicted compliance with major drug-likeness rules, absence of PAINS alerts, high gastrointestinal absorption, and low probabilities of hepatotoxicity, nephrotoxicity, and neurotoxicity. Conclusions: Andrographolide represents a promising in vitro anthelmintic hit against A. cantonensis and warrants further preclinical investigation. Full article

Multicomponent antibiotic–anti-inflammatory systems have recently attracted considerable attention, as this combination is becoming a standard therapy for infectious diseases. This study aimed to develop a multicomponent system comprising norfloxacin (NOR), an old fluoroquinolone antibiotic, and niflumic acid (NIF), another old, poorly soluble anti-inflammatory drug, to improve the physicochemical properties, antibiotic potency, and anti-inflammation effect, as well as their safety. First, a phase diagram was constructed to ensure solid-state reaction and to predict its stoichiometry; subsequently, the multicomponent system was prepared by solvent-drop grinding. The product was analyzed by a series of thermal analyses and powder X-ray diffraction (PXRD). Next, Fourier-transform infrared spectroscopy and nuclear magnetic resonance elucidated the molecular interactions, and the final 3D structure was determined by single-crystal X-ray diffraction, followed by Hirshfeld surface analysis. Afterward, the solubility and chemical stability were assessed using high-performance liquid chromatography, and the physical stability of the multicomponent system was evaluated by PXRD. Antimicrobial potency against Gram-negative and Gram-positive bacteria, as well as anti-inflammatory activity in vivo, were also evaluated. The results demonstrated that a newly formed antibiotic–anti-inflammatory multicomponent system, named norfloxacin–niflumate (NORNIF), in a salt dihydrate form, significantly improved the stability and antibiotic potency of NOR, including against the resistant microbe, as well as the solubility and in vivo anti-inflammatory effect of NIF simultaneously. In addition, preliminary in silico studies using Swiss-ADME and ProTox-3 predicted that the salt was well absorbed in the gastrointestinal tract and could be classified as toxicity class 4 (non-toxic). Full article

Oncologic drug development is lengthy (~14 years) and expensive (~1.2 billion USD) with low clinical trial success rates (4.1%). Big data and artificial intelligence (AI) are widely proposed as tools to address these challenges. In this review, we examine the current performance and future potential of big data and AI applied to preclinical discovery and development, clinical trials, and the regulatory approval process. We first examine the data foundation required for effective AI, including data harmonization, data commons, and analytical tools. We then assess preclinical applications spanning target identification, compound-library curation, virtual ligand screening, generative chemical design, and high-throughput and high-content screening. In clinical development, we consider the use of big data and AI for outcome prediction, trial design, external and synthetic control arms, adaptive monitoring, and in silico trials. Finally, we discuss how post-approval electronic health records can generate real-world data and real-world evidence to support drug repurposing and improve future oncology drug discovery. Big data is conventionally characterized by a series of “Vs.” In this review, we have used seven “Vs” spanning descriptive and constraining properties of big data and a singular outcome. We have proposed an eighth, Vernacular, a constraint defined as the combined alignment of data semantics and terminology, data representation, data exchange, and data governance across heterogeneous, independently generated datasets to promote interoperability and combined analysis. Although cancer data exhibit substantial Volume, Velocity, and Variety, they remain distributed across fragmented repositories that often cannot be readily integrated. We conclude with a discussion of tabulated resources currently available for the application of big data and AI to oncologic therapeutics. Full article

Objectives: Herpetrione (HPE) is a bioactive lignan recognized for its hepatoprotective properties; however, it exhibits limited oral bioavailability. This study aimed to classify HPE within the framework of the biopharmaceutics classification system (BCS) and to develop a nanoparticle formulation. Methods: To this end, a comprehensive investigation was conducted, encompassing computer prediction analysis, equilibrium solubility measurements across the gastrointestinal pH range, Caco-2 bidirectional transportation, in situ single-pass intestinal perfusion (SPIP), and molecular docking with P-glycoprotein (P-gp). Results: In silico analyses suggested that HPE possesses low solubility and low permeability characteristics. Experimental assays revealed pH-dependent solubility and inherently low aqueous dissolution. Unlike the computer prediction results, Caco-2 studies revealed moderate permeability but a high efflux ratio, suggestive of possible P-gp substrate activity for HPE, a finding further supported by molecular docking simulations. Conversely, SPIP studies demonstrated that the effective permeability (P_eff) of jejunal intestinal segments exceeded the high-permeability threshold, thereby classifying HPE as a high-permeability drug. Based on these findings, HPE was classified as a BCS class II compound. To overcome its solubility-limited absorption, a nanoparticle was developed, resulting in a marked enhancement of both solubility and dissolution rates. Conclusions: These findings underscore the importance of integrating experimental biopharmaceutical evaluations with computational tools when designing delivery systems for natural products. Full article

Imidazoles have been proven to be very effective pesticides, especially against phytopathogenic fungi and insects. Due to their negative effects on the environment, only a few imidazoles have been approved for use by the European Commission (EC). There is an urgent need to develop new imidazole derivatives with high efficiency and a wide spectrum of action against numerous pests that are, at the same time, safe for the environment and beneficial for organisms and humans. In order to reduce expensive and time-consuming experiments, an in silico approach based on quantitative structure–activity relationship (QSAR) models is valuable for predicting the toxicity of new or untested chemicals. In this study, we used the Vega and ChemFREE web platforms to evaluate the pesticide similarity, environmental risk properties, and ecotoxicological effects of imidazole derivatives designed for potential synthesis. Adamantane-, alkyl-, and triazole-amide, ester, carbamate, and ketone derivatives were filtered for the evaluated properties, and four alkyl-amides were highlighted as potentially effective and environmentally safe antifungal, herbicidal, and insecticidal agents. Molecular docking studies indicated the possible mechanism of action of the antifungal, herbicidal, insecticidal, and antibacterial activities of the observed compounds and revealed structural features important for binding to specific receptors. Full article

Background: Nigella sativa L. is a medicinal plant widely recognized for its diverse pharmacological properties. This study aimed to evaluate the antioxidant, diuretic, and cytotoxic effects of an aqueous seed extract and its effects on selected biochemical parameters in rats. The pharmacokinetic potential of identified bioactive compounds was also investigated in silico. Methods: The aqueous extract was prepared by maceration. Antioxidant activity was assessed using DPPH, reducing power, and total antioxidant capacity (TAC) assays. We evaluated the diuretic effect in vivo in Wistar rats by measuring urinary concentrations of Na⁺, K⁺, Cl⁻, and creatinine, using furosemide as a reference drug. Cytotoxicity was assessed in splenocytes and thymocytes. We analyzed seven identified compounds in silico for physicochemical properties, Lipinski compliance, intestinal absorption, cytochrome P₄₅₀ inhibition, and blood–brain barrier permeability. Results: The extract showed significant antioxidant activity, with a DPPH IC₅₀ of 0.254 ± 0.002 mg/mL and a TAC of 125.01 ± 4.220 mg AAE/g. It significantly increased urinary electrolyte and urinary concentration, indicating a diuretic effect lower than that of furosemide. Plasma analyses showed decreased electrolyte concentrations and increased creatinine levels. Cell viability exceeded 90%, indicating no significant cytotoxicity. Most compounds complied with Lipinski’s rule of five and showed favorable predicted intestinal absorption, with limited cytochrome P₄₅₀ inhibition. Several compounds were predicted to cross the blood–brain barrier. Conclusions: The aqueous extract of N. sativa demonstrated antioxidant and diuretic activities without significant cytotoxicity. These findings support its pharmacological potential and warrant further investigation of its mechanisms of action and therapeutic relevance. Full article

The argan tree (Argania spinosa) is an endemic Moroccan species known for its primary product, argan oil, which possesses exceptional nutritional and medicinal properties. The current study aimed to evaluate and compare the antidiabetic and antioxidant activities of argan oil obtained from the introduced and native argan tree in eastern Morocco, to analyze its chemical composition using HPLC-DAD and GC-MS, and to investigate the molecular mechanisms behind the obtained pharmacological activities through an in silico pharmacological networking and molecular docking study. The results revealed that argan oil from all three regions of Morocco (Oujda, Agadir, and Chouihya) is rich in oleic and linoleic acids as major constituents, along with the presence of significant tocopherols. Regarding the antioxidant assays, including DPPH radical scavenging and iron-reducing power tests, argan oil from Oujda exhibited the highest activity, with the lowest IC₅₀ values of 15.25 ± 0.022 mg/mL and 28.5 ± 1.7 mg/mL, respectively. Concerning the antidiabetic activity, we found that oil from Chaouihya showed the strongest α-amylase inhibition, while Oujda oil had the highest antiglycation activity, indicating that even introduced argan trees retain potent bioactivity. The results of the in silico investigation suggested that tocopherols may contribute to the antioxidant and antidiabetic potential of argan oil, showing predicted antioxidant activity (Pa = 0.843–0.967) and favorable binding affinities toward iNOS (ΔG = −9.3 kcal mol⁻¹) and α-glucosidase (ΔG = −8.2 kcal mol⁻¹). The identified fatty acids also showed predicted insulin-promoting activity (Pa = 0.59–0.75) and moderate enzyme-binding potential. Pharmacological network analysis identified 51 shared genes associated with antioxidant, antidiabetic, and argan-related targets, with enrichment of the AGE–RAGE signaling pathway. These computational findings provide possible molecular associations that may help explain the observed biological activities, although they remain predictive and require experimental validation. Overall, the in silico analysis suggests that tocopherols could be among the contributors to the multi-target profile of Argania spinosa oil, while fatty acids may provide complementary effects related to glycemic regulation. Full article

Antimicrobial resistance is a growing global health challenge, highlighting the need for new bioactive compounds from medicinal plants. Vepris nobilis is traditionally used in East Africa for treating infections and respiratory disorders; however, its essential oil (EO) composition and antimicrobial mechanisms remain poorly characterized. This study investigated the chemical composition and antimicrobial activity of V. nobilis EO, along with an in silico evaluation of its major constituent, germacrene D. The EO was extracted by hydrodistillation and analyzed using gas chromatography-mass spectrometry (GC–MS). Its antimicrobial activity was evaluated against 26 bacterial and 4 fungal strains using disc diffusion, broth microdilution, and MBC/MFC (Minimum Bactericidal Concentration/Minimum Fungicidal Concentration) assays. Germacrene D showed stronger activity than the EO, particularly against both multidrug resistant (MDR) and non-MDR Gram-negative bacterial strains (MIC = 10 µg/mL), with bactericidal and fungicidal effect. Molecular docking of germacrene D against two clinically relevant enzymes—dehydrosqualene synthase (CrtM) from Staphylococcus aureus and SWISS-modeled sterol 14-α-demethylase (CYP51) from Penicillium funiculosum—suggested potential interactions with both targets, with a favorable predicted binding affinity for CrtM (−7.654 kcal/mol) and for CYP51 (−5.898 kcal/mol). These findings provide preliminary insights into a possible antimicrobial mechanism, although experimental validation is needed to confirm this hypothesis. ADMET analysis suggested favorable drug-like properties despite limited solubility. These findings provide scientific support for the traditional use of V. nobilis leaves in the treatment of respiratory infections and highlight germacrene D as a promising lead compound for further antimicrobial development. Full article

Over more than a decade of development, various data-driven computational approaches based on the physicochemical properties of proteins have been developed for estimating the aggregation potential of proteins. The currently available algorithms and models enable a sequence-based design strategy to predict regions prone to transform into liquid–liquid phase-separated (LLPS) condensed or solidified aggregated states; for the latter, one can distinguish amyloid and prion-like aggregates. In this study, we performed a comprehensive in silico experiment; more than 40 models were used to test amino acid sequences of various proteins known to aggregate in neurodegenerative diseases, certain progressive myoclonic epilepsies and mental illnesses. Altogether, 20 proteins were analyzed and their proneness to aggregate or condensate was discussed in view of their possible normal and/or toxic function. The reported large set of computational models enables highly accurate predictions of proteins that are prone to aggregation and/or condensation. Furthermore, such aggregation profiling can be performed for any protein sequence of interest. Full article

Olopatadine (OLO) is a second-generation antihistamine approved for the treatment of allergic conjunctivitis as ophthalmic and nasal solutions. Due to its intrinsic absorption in the near-UV region (approximately 300 nm), OLO may be susceptible to photodegradation and understanding this behavior is essential for ensuring the quality and safety of OLO-containing pharmaceutical formulations. The forced photodegradation of OLO was investigated under UV/Vis irradiation (300–800 nm) over a wide pH range. Photodegradation kinetics was evaluated using a selective LC-UV method. OLO degradation followed first-order kinetics, with rate constants ranging from 3.45 × 10⁻⁵ to 6.91 × 10⁻⁵ s⁻¹, corresponding to degradation levels in the range 45.54–81.95%. Photodegradation products were characterized using UHPLC-HRMS/MS, leading to the identification of twelve, including seven previously unreported compounds. Seven degradants were isolated by preparative LC-UV and their structures were confirmed by NMR spectroscopy, including three newly reported compounds. The potential toxicity of all identified photodegradants was evaluated using the in silico tools OSIRIS Property Explorer and Toxtree. Five products were predicted to exhibit reproductive toxicity and irritation potential, whereas one compound showed a potential tumorigenic risk. Overall, this study provides comprehensive insight into the photostability of OLO and the formation of its photodegradation products. Full article

Malaria is a life-threatening global disease, and despite artemisinin-based combination therapies (ACTs) as first-line treatment, emerging drug-resistant Plasmodium strains necessitate novel antimalarial agents. This study investigated the antiplasmodial potential of Eurycoma harmandiana Pierre (EH) root extract, a medicinal plant closely related to Eurycoma longifolia Jack (EL). The extract and its derived compounds were evaluated using in vitro antiplasmodial and cytotoxicity assays. The active compounds were further investigated by parasite morphological analysis, molecular docking against quadruple-mutant Plasmodium falciparum dihydrofolate reductase (qmPfDHFR), molecular dynamics (MD) simulations, and in silico prediction of drug-likeness, pharmacokinetic properties, and toxicity. The ethanolic extract exhibited potent antiplasmodial activity (IC₅₀ = 0.51 µg/mL) with low cytotoxicity (CC₅₀ = 31.68 µg/mL) and a high selectivity index (SI = 62.11). Quassinoids showed the strongest activity (IC₅₀ = 0.13–0.87 µM), whereas alkaloids displayed good to moderate activity. The extract and two promising bioactive quassinoids, eurycomanone (1) and glaucarubolone (5), disrupted intraerythrocytic parasite development. Molecular docking and MD simulations demonstrated that glaucarubolone (5) exhibited favorable predicted interactions with qmPfDHFR, along with favorable predicted drug-like properties, pharmacokinetic profiles, and low toxicity. This study provides the first report of the antiplasmodial activity of Eurycoma harmandiana, highlighting it as a promising alternative source of bioactive compounds against Plasmodium parasites. Glaucarubolone (5) may represent a promising scaffold for further investigation toward the development of novel antimalarial agents. Full article

This study investigated the neuroprotective potential of Xanthoceras sorbifolium Bunge (XSB) seed oil through fatty acid profiling, antioxidant assays, and in silico targeting of FABP7. Among the solvent-to-solid ratios tested, 1:20 (w/v) gave the highest oil yield (72.91%) and the strongest ABTS, DPPH, and FRAP activities. GC-MS identified 17 fatty acids from the 1:20 (w/v) oil extract, with linoleic acid (38.93%) and oleic acid (31.3%) as the major constituents. Following GC-MS fatty acid profiling, lipid structural characterization was performed using ¹H NMR and FT-IR. ADME/T prediction and BOILED-EGG analysis suggested favorable pharmacokinetic properties and BBB permeability for the selected fatty acids. Molecular docking and simulation revealed strong and stable interactions of five compounds with FABP7: nervonic acid (−6.1 kcal/mol), erucic acid (−6.002 kcal/mol), eicosadienoic acid (−6.08 kcal/mol), oleic acid (−6.03 kcal/mol), and linoleic acid (−6.00 kcal/mol), outperforming the native ligand, oleic acid (−5.8 kcal/mol). These findings indicate that XSB seed oil contains bioactive lipids with promising FABP7-targeted neuroprotective potential and warrant further investigation as therapeutic leads for neurodegenerative diseases. Full article

Understanding the potential mechanisms of bacterial azo dye decolorization remains a challenge due to a limited understanding of the exact stereochemical forces guiding enzyme–substrate interactions. This study addresses these interactions by evaluating the in silico binding architectures of Orange G (OG) and Congo Red (CR) against the Bacillus-derived azoreductase model AzrA (PDB ID: 3W77). Computational modeling predicted favorable thermodynamic properties within the calculated active site, yielding binding energy scores of −8.17 kcal/mol for CR and −6.63 kcal/mol for OG. These simulations identified hydrogen-bonding and aromatic π-π interactions within the predicted binding pocket. These predictions suggest potential enzyme–dye association but do not demonstrate catalytic activity or azo-bond cleavage. Independently, Bacillus cereus BC WW Saida achieved an 81% decolorization of OG within 144 h and a 70% reduction in CR within 96 h. High-performance liquid chromatography (HPLC) indicated chemical transformation, demonstrating a significant decrease in primary dye peaks alongside the emergence of novel intermediate peaks at 254 nm. Rather than definitively establishing a metabolic pathway, these outcomes deliver preliminary structural models of azoreductase-substrate affinities, offering a useful framework for the comparative evaluation of microbial catalysts for industrial effluent purification. Full article