顶点-边加权分子图：拓扑指数及其与癌症治疗常用药物理化性质相关性的研究
Vertex-Edge Weighted Molecular Graphs: A study on topological indices and their relevance to physicochemical properties of drugs in use cancer treatment
AI总结：
本研究将定量构效关系分析应用于顶点-边加权分子图，提出新的权重计算方法，经48种抗癌药物验证，其拓扑指数与药物理化性质的相关性优于传统未加权分子图方法。
摘要：
定量构效关系（QSPR）分析在预测药物化合物的理化性质和生物活性方面发挥着关键作用，可为药物设计与优化提供助力。本研究聚焦于在顶点与边加权（VEW）分子图框架下应用QSPR，探究其在药物研究中的价值。研究以48种用于治疗多种癌症的药物及其理化性质为考察对象，以过往研究为基础。我们提出了一种计算顶点与边权重的新方法，并以药物Busulfan（白消安）为例进行说明，强调了考虑原子性质和键间动力学的重要性。采用线性回归模型的统计分析显示，拓扑指数与药物理化性质之间的相关性得到增强。与过往针对未加权分子图的研究相比，我们的方法实现了性能提升。
英文摘要：
Quantitative Structure-Property Relationship (QSPR) analysis plays a crucial role in predicting physicochemical properties and biological activities of pharmaceutical compounds, aiding in drug design and optimization. This study focuses on leveraging QSPR within the framework of vertex and edge weighted (VEW) molecular graphs, exploring their significance in drug research. By examining 48 drugs in used in the treatment of various cancers and their physicochemical properties, previous studies serve as a foundation for our research. Introducing a novel methodology for computing vertex and edge weights, exemplified by the drug Busulfan, we highlight the importance of considering atomic properties and inter-bond dynamics. Statistical analysis, employing linear regression models, reveals enhanced correlations between topological indices and physicochemical properties of drugs. Comparison with previous studies on unweighted molecular graphs highlights the enhancements achieved with our approach.
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