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BackgroundChemicals may lead to acute liver injuries, posing a serious threat to human health. Achieving the precise safety profile of a compound is challenging due to the complex and expensive testing procedures. In silico approaches will aid in identifying the potential risk of drug candidates in the initial stage of drug development and thus mitigating the developmental cost.MethodsIn current studies, QSAR models were developed for hepatotoxicity predictions using the ensemble strategy to integrate machine learning (ML) and deep learning (DL) algorithms using various molecular features. A large dataset of 2588 chemicals and drugs was randomly divided into training (80%) and test (20%) sets, followed by the training of individual base models using diverse machine learning or deep learning based on three different kinds of descriptors and fingerprints. Feature selection approaches were employed to proceed with model optimizations based on the model performance. Hybrid ensemble approaches were further utilized to determine the method with the best performance.ResultsThe voting ensemble classifier emerged as the optimal model, achieving an excellent prediction accuracy of 80.26%, AUC of 82.84%, and recall of over 93% followed by bagging and stacking ensemble classifiers method. The model was further verified by an external test set, internal 10-fold cross-validation, and rigorous benchmark training, exhibiting much better reliability than the published models.ConclusionThe proposed ensemble model offers a dependable assessment with a good performance for the prediction regarding the risk of chemicals and drugs to induce liver damage.

Introduction: Natural antioxidants are vital to promote health and treat critical disease conditions in the modern healthcare system. This work adds to the index of natural medicines by exploring the antioxidant potential of Dodonaea viscosa Jacq. (Plant-DV).Material and Methods: The aqueous extract of leaves and flower-containing seeds from plant-DV in freshly prepared phosphate buffer is evaluated for antioxidant potential. In vitro antioxidant potential of the nascent and oxidatively stressed extracts was analyzed through glutathione (GSH) assay, hydrogen peroxide (H2O2) scavenging effect, glutathione-S-transferase (GST) assay, and catalase (CAT) activity. In vivo therapeutic assessment is performed in Wistar Albino rats using vitamin C as a positive control. The livers and kidneys of individual animals are probed for glutathione, glutathione-S-transferase, and catalase activities.Results: flower-containing seeds have GSH contents (59.61 µM) and leaves (32.87 µM) in the fresh aqueous extracts. The hydrogen peroxide scavenging effect of leaves is superior to flower-containing seeds with 17.25% and 14.18% respectively after 30 min incubation. However, oxidatively stressed extracts with Ag(I) and Hg(II) show declining GSH and GST levels. The plant extracts are non-toxic in rats at 5000 mg/Kg body weight. Liver and kidneys homogenate reveal an increase in GSH, GST, and CAT levels after treatment with 150 ± 2 mg/kg and 300 ± 2 mg/kg body weight plant extract compared with normal saline-treated negative and vitamin C treated positive control.Discussion: The crude aqueous extracts of leaves and flower-containing seeds of plant-DV show promising antioxidant potential both in in vitro and in vivo evaluation.

Bacterial brown stripe disease caused by Acidovorax oryzae is a major threat to crop yields, and the current reliance on pesticides for control is unsustainable due to environmental pollution and resistance. To address this, bacterial-based ligands have been explored as a potential treatment solution. In this study, we developed a protein–protein interaction (PPI) network for A. oryzae by utilizing shared differentially expressed genes (DEGs) and the STRING database. Using a maximal clique centrality (MCC) approach through CytoHubba and Network Analyzer, we identified hub genes within the PPI network. We then analyzed the genomic data of the top 10 proteins, and further narrowed them down to 2 proteins by utilizing betweenness, closeness, degree, and eigenvector studies. Finally, we used molecular docking to screen 100 compounds against the final two proteins (guaA and metG), and Enfumafungin was selected as a potential treatment for bacterial resistance caused by A. oryzae based on their binding affinity and interaction energy. Our approach demonstrates the potential of utilizing bioinformatics and molecular docking to identify novel drug candidates for precision treatment of bacterial brown stripe disease caused by A. oryzae, paving the way for more targeted and sustainable control strategies. The efficacy of Enfumafungin in inhibiting the growth of A. oryzae strain RS-1 was investigated through both computational and wet lab methods. The models of the protein were built using the Swiss model, and their accuracy was confirmed via a Ramachandran plot. Additionally, Enfumafungin demonstrated potent inhibitory action against the bacterial strain, with an MIC of 100 µg/mL, reducing OD600 values by up to 91%. The effectiveness of Enfumafungin was further evidenced through agar well diffusion assays, which exhibited the highest zone of inhibition at 1.42 cm when the concentration of Enfumafungin was at 100 µg/mL. Moreover, Enfumafungin was also able to effectively reduce the biofilm of A. oryzae RS-1 in a concentration-dependent manner. The swarming motility of A. oryzae RS-1 was also found to be significantly inhibited by Enfumafungin. Further validation through TEM observation revealed that bacterial cells exposed to Enfumafungin displayed mostly red fluorescence, indicating destruction of the bacterial cell membrane.

Viruses are submicroscopic, obligate intracellular parasites that carry either DNA or RNA as their genome, protected by a capsid. Viruses are genetic entities that propagate by using the metabolic and biosynthetic machinery of their hosts and many of them cause sickness in the host. The ability of viruses to adapt to different hosts and settings mainly relies on their ability to create de novo variety in a short interval of time. The size and chemical composition of the viral genome have been recognized as important factors affecting the rate of mutations. Coronavirus disease 2019 (Covid-19) is a novel viral disease that has quickly become one of the world’s leading causes of mortality, making it one of the most serious public health problems in recent decades. The discovery of new medications to cope with Covid-19 is a difficult and time-consuming procedure, as new mutations represent a serious threat to the efficacy of recently developed vaccines. The current article discusses viral mutations and their impact on the pathogenicity of newly developed variants with a special emphasis on Covid-19. The biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), its mutations, pathogenesis, and treatment strategies are discussed in detail along with the statistical data.

The current study was intended to explore the phytochemical profiling and therapeutic activities of Putranjiva roxburghii Wall. Crude extracts of different plant parts were subjected to the determination of antioxidant, antimicrobial, antidiabetic, cytotoxic, and protein kinase inhibitory potential by using solvents of varying polarity ranges. Maximum phenolic content was notified in distilled water extracts of the stem (DW-S) and leaf (DW-L) while the highest flavonoid content was obtained in ethyl acetate leaf (EA-L) extract. HPLC-DAD analysis confirmed the presence of various polyphenols, quantified in the range of 0.02 ± 0.36 to 2.05 ± 0.18 μg/mg extract. Maximum DPPH scavenging activity was expressed by methanolic extract of the stem (MeOH-S). The highest antioxidant capacity and reducing power was shown by MeOH-S and leaf methanolic extract (MeOH-L), respectively. Proficient antibacterial activity was shown by EA-L extract against Bacillus subtilis and Escherichia coli. Remarkable α-amylase and α-glucosidase inhibition potential was expressed by ethyl acetate fruit (EA-F) and n-Hexane leaf (nH-L) extracts, respectively. In case of brine shrimp lethality assay, 41.67% of the extracts (LC50 < 50 µg/mL) were considered as extremely cytotoxic. The test extracts also showed mild antifungal and protein kinase inhibition activities. The present study explores the therapeutic potential of P. roxburghii and calls for subsequent studies to isolate new bioactive leads through bioactivity-guided isolation.