Mohamed Shaker S. Adam , Zahraa H.A. Al-Ateya , Mohamed M. Makhlouf , Obadah S. Abdel-Rahman , Amneh Shtaiwi , Ahmed Khalil
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引用次数: 0
Abstract
According to the considered role of lipophilicity-hydrophobicity on organic Schiff base hydrazones, different substituents of phenyl, ethyl, and methyl groups were inserted in the synthetic strategy of diisatin dihydrazones (L1–4). The biochemical enhancement was evaluated depending on their inhibitive potential of the growth power of three human tumor cells, fungi, and bacteria. The biochemical assays assigned the effected role of different substituents of phenyl, ethyl, and methyl groups on the effectiveness of their diisatin dihydrazone reagents. The interacting modes with calf thymus DNA (i.e. Ct-DNA) were studied via viscometric and spectrophotometric titration.
The organo-reagent L1 with the oxalic derivative assigned a performed inhibitive action for the examined microbes and the human tumor cell lines growing up over the terephthalic (L4) > malonic (L2) > succinic (L3) ones. From Kb = binding constant, and = Gibb’s free energy values, the binding of interaction within Ct-DNA was evaluated for all compounds (L1–4), in which L1, L3, and L4 assigned the highest reactivity referring to the covalent/non-covalent modes of interaction, as given for (L1–4), 14.32, 13.28, 10.87, and 12.41 × 107 mol−1 dm3, and −45.17, −43.24, −43.75, and −44.05 kJ mol−1, respectively. DFT and docking studies were achieved to support the current work.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
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