QSPR Analysis of Some Novel Drugs Used in Blood Cancer Treatment Via Degree Based Topological Indices and Regression Models

被引:84
作者
Zaman, Shahid [1 ]
Yaqoob, Hafiza Sana Arbab [1 ]
Ullah, Asad [2 ,3 ]
Sheikh, Mariam [1 ]
机构
[1] Univ Sialkot, Dept Math, Sialkot, Pakistan
[2] Karakoram Int Univ Gilgit, Dept Math Sci, Gilgit, Pakistan
[3] Karakoram Int Univ Gilgit Baltistan, Dept Math Sci, Gilgit 15100, Pakistan
关键词
Anti-cancer drugs; graph theory; topological indices; QSPR analysis; regression models; ATOM-BOND CONNECTIVITY; GRAPH-THEORY; NETWORK;
D O I
10.1080/10406638.2023.2217990
中图分类号
O62 [有机化学];
学科分类号
070303 ; 081704 ;
摘要
Topological indices (TIs) have several biological applications in the treatment of blood cancer. TIs can be used to predict the efficacy of drugs in cancer treatment by providing information about the molecular structures of the drugs and their related properties. By analyzing the degree-based TIs of different drugs, researchers can identify the most effective drugs for treating specific types of blood cancer. Additionally, TIs can also be used to predict the toxicity of drugs, which is essential for developing safe and effective treatments. Furthermore, TIs can aid in the discovery and design of new drugs by providing insights into the relationship between molecular structure and biological activity. This article focuses on the applications of topological indices (TIs) in predicting the physical and biological properties of novel drugs used in the treatment of blood cancer. The drugs glasdegib, palbociclib, and daunorubicin are analyzed using degree-based topological indices computed through edge partitioning. A quantitative structure-property relationship (QSPR) model is then developed using linear regression to predict the properties such as boiling point (BP), flash point (FP), molar volume (MV), molecular weight, and complexity. The results demonstrate the potential of topological indices as a tool for drug discovery and design in the field of cancer treatment.
引用
收藏
页码:2458 / 2474
页数:17
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