衍生物的物理化学性质的预测能力,使用基于末端顶点的Ve度
Muhammad Naeem1, Abdul Rauf2, Muhammad Waleed Mumtaz3
1Department of Mathematics, School of Natural Sciences, National University of Sciences and Technology (NUST), Islamabad, Pakistan.
Journal of biomolecular structure & dynamics
|October 28, 2023
概括
本研究引入了一种新的定量结构-活性关系 (QSPR) 模型,用于使用基于边缘的 entropies 预测衍生物的物理化学性质. 该模型准确地预测了临界温度和摩尔折射率等属性,突出了拓索引在化学中的实用性.
科学领域:
- 化学信息学 化学信息学
- 计算化学计算化学
- 物理化学 物理化学
背景情况:
- 拓指数对于将化学结构与反应性和特性相关联至关重要.
- 量化结构-活性关系 (QSPR) 模型化学行为使用拓描述符.
- 衍生物表现出不同的物理化学特性,受其结构的影响.
研究的目的:
- 提出一个QSPR模型,将衍生物的边缘与其物理化学性质联系起来.
- 开发和使用基于Maple的算法来计算这些.
- 评估各种物理化学性质的拓指数的预测能力.
主要方法:
- 为计算开发基于Maple的算法.
- 应用量化结构-活动关系 (QSPR) 进行相关性分析.
- 使用SPSS进行统计分析,以评估拟议模型的意义.
主要成果:
- 在以边缘为基础的 entropies和物理化学性质的末端顶点的 ve 度之间建立了显著的 QSPR.
- 诸如临界压力,亨利定律常数,临界温度,吉布的能量,logP,临界体积和摩尔折射率等属性得到了准确的预测.
- 兰迪奇,巴拉班和重新定义的第三个扎格勒布都显示出最强的相关性.
结论:
- 拟议的QSPR模型有效预测衍生物的物理化学性质.
- 基于边缘的值在定量结构-活动关系中作为有价值的描述符.
- 拓指数,特别是兰迪奇,巴拉班和重新定义的第三个扎格勒布,提供了与化学性质的强有力的相关性.
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