关于抗结核药物距离基指标计算的新方法
On Novel Approach for Computing Distance based Indices of Anti-tuberculosis Drugs
AI总结：
提出一种基于度数和距离的拓扑指标新方法，用于评估抗结核药物分子结构，并通过QSPR研究显示其与物理属性显著相关，有望减少临床试验需求。
摘要：
本研究旨在利用基于度数的拓扑指标和新型距离基指标来评估抗结核药物的分子结构。我们可以将化学排列表示为图，其中原子作为顶点，连接作为边。在此，多重键被视为多重边，并包含了所有氢原子。此外，我们考虑了三维分子图。因此，实际键长被用于计算新的距离基指标。与众多研究相比，这是一个显著的改进。此外，对这些指标的研究包括对定量结构-性质关系（QSPR）的研究。研究证明了这些指标与抗结核药物的物理属性之间存在显著的相关性。在此，由于我们减少了文献中一些现有的关键假设，化学家和制药专业人员可能通过采用这一理论模型来潜在地消除临床试验的需要。这些模型将使他们能够预测抗结核药物的特性。
英文摘要：
This work aims to assess the molecular architectures of anti-tuberculosis drugs using both degree-based topological indices and novel distance based indices. We can represent the chemical arrangement as a graph, with atoms serving as the vertices and connections as the edges. Here, the multi bonds were considered as multi edges and included all the hydrogen atoms. Also, we consider three dimensional molecular graph. As a result, the actual bond lengths have been used for computation of new distance based indices. Compared to numerous studies, this is a significant improvement. Furthermore, the investigation of these indices includes a study on the quantitative structure-property relationship (QSPR). The research demonstrates a notable correlation between these indicators and the physical attributes of anti-tuberculosis drugs. Here, Since we reduced the some of existing critical assumptions in the literature, chemists and pharmaceutical professionals might potentially eliminate the need for clinical trials by employing this theoretical model. These models would enable them to predict the characteristics of anti-tuberculosis medications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
