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人工智能辅助的模型可以预测用C60烯衍生物修饰的化疗药物

Jonathan-Siu-Loong Robles-Hernández¹, Dora Iliana Medina², Katerin Aguirre-Hurtado³

¹Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico.

Beilstein journal of nanotechnology

|September 25, 2024

概括

富勒烯衍生物通过改善与CXCR7蛋白的相互作用来增强乳腺癌药物输送. 定量模型预测了这些相互作用,为先进的纳米载体化疗铺平了道路.

科学领域:

计算化学是一种计算化学.
纳米技术纳米技术
药理学药理学是指药理学的学科.

背景情况:

乳腺癌化疗面临着药物的有效性和输送方面的挑战.
富勒烯衍生物为改善药物向提供了作为纳米载体的潜力.
了解药物蛋白相互作用对于优化化疗至关重要.

研究的目的:

研究烯衍生物作为乳腺癌药物的纳米载体.
模拟和预测药物富勒烯复合物的与CXCR7蛋白质的结合相互作用.
开发预测性的定量结构-活动关系 (QSAR) 和定量结构-属性关系 (QSPR) 模型.

主要方法:

使用了定量结构-活动关系 (QSAR) 和定量结构-属性关系 (QSPR) 模型.
采用了针对CXCR7蛋白的分子对接模拟.
使用量子化学 (DFTB3) 和人工智能 (AI) 的计算能量描述器.
应用了皮尔森的硬软酸理论和多重线性回归.

主要成果:

与单独的药物相比,药物富勒烯复合体与CXCR7的相互作用增强.
确定了不同药物复合物的特定和不同的结合点.
使用人工智能识别的关键变量开发了具有平均绝对百分比误差低于12%的预测模型.
通过将DFTB3与传统密度函数理论进行比较,验证了计算方法.

结论:

富勒烯基纳米载体显著改善乳腺癌治疗中的药物相互作用.
预测性QSAR/QSPR模型可以准确预测药物-富勒伦-CXCR7结合.
这项研究支持开发基于富勒的先进纳米载体,用于增强化疗.

关键词:

CXCR7CXCR7CXCR7CXCR7CXCR7CXCR7CXCR7CXCR7CXCR7CXCR7 在QSAR中使用QSAR.乳腺癌乳腺癌乳腺癌药物纳米载体药物纳米载体

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