拓指数和QSPR模拟通过M多项式通过gonalgia相关的药物分子
Rong-Rong Huang1, Saood Azam2, Adnan Aslam3
1College of Pharmacy, Anhui Xinhua University, 230088, Hefei, China.
The European physical journal. E, Soft matter
|October 30, 2025
概括
来自分子结构的拓指数可以准确地预测药物特性. 总和连接性指数最好预测物理性质,而总和-巴拉班指数预测痛治疗的分区系数.
科学领域:
- *计算化学和化学信息学.
- * 图形理论在药物发现中的应用.
背景情况:
- * 拓指数量化分子结构用于属性预测.
- * 痛 (膝盖疼痛) 治疗涉及各种化学化合物.
- *M多项式为计算拓指数提供了可靠的方法.
研究的目的:
- *使用M多项式方法计算15种gonalgia药物的7度基于拓指数.
- * 在这些指数和关键的物理化学性质之间建立定量结构-性质关系 (QSPR).
- * 评估不同拓指数和回归模型的预测能力.
主要方法:
- * 分析了15种淋巴痛药物的分子图.
- * 七个拓指数 (ISI,HA,ISDD,AZI,SC,GA,SJ) 通过M多项式计算.
- * QSPR分析采用线性,多项式和对数回归模型.
主要成果:
- * 在拓指数和物理化学性质 (BP,MP,CT,CV,LogP,MR,CLogP) 之间发现了强烈的相关性.
- * 总连接性 (SC) 指数在预测沸点,点,临界温度,临界体积和摩尔折射率方面表现出色.
- * 总和-巴拉班 (SJ) 指数在预测醇-水分区系数和计算LogP方面表现优异.
- *二次回归模型始终产生了最高的预测准确性.
结论:
- * M多项式衍生拓指数为预测药物的物理化学性质提供了可靠的框架.
- * 非线性关系对于准确的定量结构与属性关系至关重要.
- *这种方法有助于制药化合物的计算设计和优化.
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