一种基于图形的计算方法,用于在药物设计中建模物理化学性质.
Ibrahim Al-Dayel1, Meraj Ali Khan1, Muhammad Faisal Hanif2
1Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), P.O. Box 65892, 11566, Riyadh, Saudi Arabia.
Scientific reports
|July 2, 2025
概括
数学模型使用分子结构预测药物特性,如沸点和稳定性. 四位数模型对抗生素和神经病药物具有更高的准确性,有助于药物开发.
科学领域:
- 药用化学 医学化学
- 计算化学计算化学
- 药理学 药理学是指药理学的学科.
背景情况:
- 物理化学性质决定了药物的稳定性,生物可用性和治疗疗效.
- 了解结构-属性关系对于药物设计和开发至关重要.
研究的目的:
- 使用数学建模预测抗生素和神经病药物的关键物理化学性质.
- 探索定量结构-属性关系 (QSPR) 分析对药物优化的有用性.
主要方法:
- 使用修改后的基于度的拓索引作为分子描述符.
- 使用线性和二次回归模型进行定量结构与属性关系 (QSPR) 分析.
- 预测的物理化学性质包括沸点,蒸发的度,闪点和折.
主要成果:
- 与线性模型相比,二次回归模型对大多数属性显示出优异的预测性能.
- 高的R平方值和低的误差率表明模型的准确性很好.
- 拓描述符有效地将分子结构与物理化学性质相关联.
结论:
- 数学建模和QSPR分析,特别是二次模型,是预测药物的物理化学性能的强大工具.
- 拓描述符为早期药物查和优化提供了一种有价值的方法.
- 这种方法可以加速开发有效的抗生素和神经病药物.
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