超分子DDMC/紫杉醇复合物靶向黑色素瘤的鲁棒控制系统。

IF 1.4 4区 生物学 Q4 CELL BIOLOGY
Y Onishi, Y Eshita, R-C Ji, T Kobayashi, M Onishi, M Mizuno, J Yoshida, N Kubota
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引用次数: 2

摘要

以PTX为客体,DDMC为宿主,制备了deae -葡聚糖- mma共聚物(DDMC)-紫杉醇(PTX)偶联物。证实B16F10黑色素瘤细胞对PTX具有耐药性,DDMC-PTX偶联物具有良好的抗癌活性,符合Hill方程。通过BIBO稳定性证实了变构系统在肿瘤微环境中的稳健性。通过传递函数解释的反馈控制系统非常稳定,并通过循环显示系统的可持续性,并且在没有癌细胞耐药性的情况下显示出优越的抗癌活性。该信号系统在肿瘤微环境中的框图使用了其环路传递函数G(s)和外力dN(s)。这种初始响应是理想的,没有输出响应的时间滞后。DDMC-PTX的细胞死亡率更多地依赖于Hill系数n而不是Michaelis常数Km。这意味着这种与微管蛋白的超分子反应遵循“诱导拟合模型”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robust control system for targeting melanoma by a supermolecular DDMC/paclitaxel complex.

A DEAE-dextran-MMA copolymer (DDMC)-paclitaxel (PTX) conjugate was prepared using PTX as the guest and DDMC as the host. The resistance of B16F10 melanoma cells to PTX was confirmed, while the DDMC-PTX conjugate showed excellent anticancer activity that followed the Hill equation. The robustness in the tumor microenvironment of the allosteric system was confirmed via BIBO stability. This feedback control system, explained via a transfer function, was very stable and showed the sustainability of the system via a loop, and it showed superior anti-cancer activity without drug resistance from cancer cells. The block diagram of this signal system in the tumor microenvironment used its loop transfer function G(s) and the dN(s) of the external force. This indicial response is an ideal one without a time lag for the outlet response. The cell death rate of DDMC-PTX is more dependent on the Hill coefficient n than on the Michaelis constant Km. This means that this supermolecular reaction with tubulin follows an "induced fit model".

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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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