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

Abstract

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.

Keywords:

• Anti-cancer drugs
• graph theory
• topological indices
• QSPR analysis
• regression models

Acknowledgment

This research received no external funding.

Disclosure statement

The authors declare no any conflict of interest/competing interests.

Author contributions

All the authors have equally contributed to this manuscript in all stages, from conceptualization to the write-up of final draft.

Data availability statement

All data generated or analyzed during this study are included in this article.