This study determined the effect of light intensity and photoperiod on the dry cell weight and total amount of carotenoids in four isolates of purple non-sulfur bacteria obtained from shaded and exposed microhabitats of a mangrove ecosystem in Kota Kinabalu, Sabah, Malaysia. The initial isolation of the bacteria was carried out using synthetic 112 medium under anaerobic conditions (2.5 klx) at 30 ± 2°C. On the basis of colony appearance, cell morphology, gram staining, motility test, and 16S rRNA gene sequencing analyses, all four bacteria were identified as Afifella marina. One of the bacterial isolates, designated as Af. marina strain ME, which was extracted from an exposed mud habitat within the mangrove ecosystem, showed the highest yield in dry cell weight (4.32± 0.03 g/l) as well as total carotenoids (0.783 ± 0.002 mg/g dry cell weight). These values were significantly higher than those for dry cell weight (3.77 ± 0.02g/l ) and total carotenoid content (0.706 ± 0.008 mg/g) produced by the isolates from shaded habitats. Further analysis of the effect of 10 levels of light intensity on the growth characteristics of Af. marina strain ME showed that the optimum production of dry cell weight and total carotenoids was achieved at different light intensities and incubation periods. The bacterium produced the highest dry cell weight of 4.98 g/l at 3 klx in 72 h incubation, but the carotenoid production of 0.783 mg/g was achieved at 2.5 klx in 48 h incubation. Subsequent analysis of the effect of photoperiod on the production of dry cell weight and total carotenoids at optimum light intensities (3 and 2.5 klx, respectively) revealed that 18 and 24 h were the optimum photoperiods for the production of dry cell weight and total carotenoids, respectively. The unique growth characteristics of the Af. marina strain ME can be exploited for biotechnology applications.
Lassa hemorrhagic fever, caused by Lassa mammarenavirus (LASV) infection, accumulates up to 5000 deaths every year. Currently, there is no vaccine available to combat this disease. In this study, a library of 200 bioactive compounds was virtually screened to study their drug-likeness with the capacity to block the α-dystroglycan (α-DG) receptor and prevent LASV influx. Following rigorous absorption, distribution, metabolism, and excretion (ADME) and quantitative structure-activity relationship (QSAR) profiling, molecular docking was conducted with the top ligands against the α-DG receptor. The compounds chrysin, reticuline, and 3-caffeoylshikimic acid emerged as the top three ligands in terms of binding affinity. Post-docking analysis revealed that interactions with Arg76, Asn224, Ser259, and Lys302 amino acid residues of the receptor protein were important for the optimum binding affinity of ligands. Molecular dynamics simulation was performed comprehensively to study the stability of the protein-ligand complexes. In-depth assessment of root-mean-square deviation (RMSD), root mean square fluctuation (RMSF), polar surface area (PSA), B-Factor, radius of gyration (Rg), solvent accessible surface area (SASA), and molecular surface area (MolSA) values of the protein-ligand complexes affirmed that the candidates with the best binding affinity formed the most stable protein-ligand complexes. To authenticate the potentialities of the ligands as target-specific drugs, an in vivo study is underway in real time as the continuation of the research.
The HER2-positive patients occupy ~ 30% of the total breast cancer patients globally where no prevalent drugs are available to mitigate the frequent metastasis clinically except lapatinib and neratinib. This scarcity reinforced researchers' quest for new medications where natural substances are significantly considered. Valuing the aforementioned issues, this research aimed to study the ERBB2-mediated string networks that work behind the HER2-positive breast cancer formation regarding co-expression, gene regulation, GAMA-receptor-signaling pathway, cellular polarization, and signal inhibition. Following the overexpression, promotor methylation, and survivability profiles of ERBB2, the super docking position of HER2 was identified using the quantum tunneling algorithm. Supramolecular docking was conducted to study the target specificity of EPA and DHA fatty acids followed by a comprehensive molecular dynamic simulation (100 ns) to reveal the RMSD, RMSF, Rg, SASA, H-bonds, and MM/GBSA values. Finally, potential drug targets for EPA and DHA in breast cancer were constructed to determine the drug-protein interactions (DPI) at metabolic stages. Considering the values resulting from the combinational models of the oncoinformatic, pharmacodynamic, and metabolic parameters, long-chain omega-3 fatty acids like EPA and DHA can be considered as potential-targeted therapeutics for HER2-positive breast cancer treatment.