[This retracts the article DOI: 10.1155/2022/6129134.].
[This retracts the article DOI: 10.1155/2022/6129134.].
[This retracts the article DOI: 10.1155/2022/9910266.].
[This retracts the article DOI: 10.1155/2022/6977424.].
[This retracts the article DOI: 10.1155/2022/4565260.].
[This retracts the article DOI: 10.1155/2022/7739734.].
[This retracts the article DOI: 10.1155/2022/3562209.].
[This retracts the article DOI: 10.1155/2022/6444367.].
[This retracts the article DOI: 10.1155/2022/8339503.].
[This retracts the article DOI: 10.1155/2022/6008603.].
The main challenges faced by medical researchers while producing novel drugs are time commitment, amplified costs, creating a safety profile for the medications, reduced solubility, and a lack of experimental data. Chemical graph theory makes an important theoretical contribution to drug development and design by investigating the structural properties of molecules. To improve drug research and assess the effectiveness of treatments, topological indices aim to provide a mathematical representation of molecular structures. In this study, the author examined a number of recently used drugs, including tamoxifen, mesterolone, anastrozole, and letrozole which are used to treat infertility. We compute the topological descriptors with the limiting behaviors associated with these pharmaceutical drugs and offer degree-based topological parameters for them. We conducted a QSPR investigation on the prospective degree-based topological descriptors using quadratic, cubic, exponential, and logarithmic regression models.