ABSTRACT
Four new rotenoid glycosides, namely amorphaside A-D (1-4), along with four known ones (5-8) were isolated from the seeds of Amorpha fruticosa. Their chemical structures and absolute configurations were elucidated by HRESIMS, NMR and CD spectra, as well as deduction from biosynthesis route. The sugar units were determined by acid hydrolysis, appropriate derivatization and HPLC analysis. The in vitro anti-proliferative activities of all compounds were evaluated against MCF-7 and HCT-116 cell lines. The results showed that compounds 1-3 had no effect on cell proliferation in the two cell lines even with the concentration of 50 µM, and compounds 4, 7 and 8 had selective cytotoxicity against MCF-7 with IC50 values of 3.90, 0.95 and 34.08 µM, respectively, while compounds 5 and 6 both showed significant cytotoxicity to the two cell lines with IC50 values less than 2.00 µM, even better than the positive control cisplatin. These preliminary results indicated that compounds 5 and 6 might be valuable to anticancer drug candidates.
Subject(s)
Antineoplastic Agents, Phytogenic/pharmacology , Fabaceae/chemistry , Flavonoids/pharmacology , Glycosides/pharmacology , Seeds/chemistry , Antineoplastic Agents, Phytogenic/isolation & purification , Cell Proliferation , Drug Screening Assays, Antitumor , Flavonoids/chemistry , Flavonoids/isolation & purification , Glycosides/chemistry , Glycosides/isolation & purification , HCT116 Cells , Humans , MCF-7 Cells , Molecular StructureABSTRACT
The genetic code is not random but instead is organized in such a way that single nucleotide substitutions are more likely to result in changes between similar amino acids. This fidelity, or error minimization, has been proposed to be an adaptation within the genetic code. Many models have been proposed to measure this adaptation within the genetic code. However, we find that none of these consider codon usage differences between species. Furthermore, use of different indices of amino acid physicochemical characteristics leads to different estimations of this adaptation within the code. In this study, we try to establish a more accurate model to address this problem. In our model, a weighting scheme is established for mistranslation biases of the three different codon positions, transition/transversion biases, and codon usage. Different indices of amino acids' physicochemical characteristics are also considered. In contrast to pervious work, our results show that the natural genetic code is not fully optimized for error minimization. The genetic code, therefore, is not the most optimized one for error minimization, but one that balances between flexibility and fidelity for different species.
