Polyphenolic profiling of <i>Ipomoea carnea</i> Jacq. by HPLC-DAD and its implications in oxidative stress and cancer

<p><i>Ipomoea carnea</i> Jacq<i>.</i> is an important folklore medicinal plant, assessed for its underexplored biological potential. Antioxidant, cytotoxic, antiproliferative and polyphenolic profile of whole plant was evaluated using various techniques. Maximum extract recovery (29% w/w), phenolic [13.54 ± 0.27 μg GAE/mg dry weight (DW)] and flavonoid (2.11 ± 0.10 μg QE /mg DW) content were recorded in methanol-distilled water (1:1) flower extract. HPLC-DAD analysis quantified substantial amount of six different polyphenols ranging from 0.081 to 37.95 μg/mg extract. Maximum total antioxidant and reducing potential were documented in methanol-distilled water and acetone-distilled water flower extracts (42.62 ± 0.47 and 24.38 ± 0.39 μg AAE/mg DW) respectively. Ethanol-chloroform root extract manifested highest free radical scavenging (IC₅₀ of 61.22 μg/mL) while 94.64% of the extracts showed cytotoxicity against brine shrimps. Ethanol leaf extract exhibited remarkable activity against THP-1 cell line (IC₅₀ = 8 ± 0.05 μg/mL) and protein kinases (31 mm phenotype bald zone).</p

Table_1_Precision drug design against Acidovorax oryzae: leveraging bioinformatics to combat rice brown stripe disease.docx

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.</p