Altassan Alaa, Saleh Anwar, Alashwali Hanaa, Hamed Marwa, Muthana Najat
Department of Mathematics, Faculty of Science, King Abdulaziz University, 21589, Jeddah, Saudi Arabia.
Department of Mathematics and Statistics, College of Science, University of Jeddah, 23218, Jeddah, Saudi Arabia.
Sci Rep. 2025 Jul 22;15(1):26683. doi: 10.1038/s41598-025-12179-0.
Cancer is a life-threatening disease that can attack humans at any part of the body as a consequence of abnormal cell growth and proliferation, leading to tumors that can be fatal. Breast cancer is one of the deadliest ailments in the world after lung cancer. Through hormonal and genetic changes that occur in DNA, breast cancer can affect women. The quantitative structural-property relationship (QSPR) is used to provide a comprehensive study of 16 drugs involved in the treatment of breast cancer. According to their chemical structure, the drugs being studied are modeled as molecular graphs. The purpose of this study is to examine the utility of new entire neighborhood topological indices in characterizing the physicochemical properties of a range of breast cancer drugs. Cubic regression analysis was initially employed, followed by multiple linear regression modeling to enhance the correlation between the entire neighborhood topological indices and some properties of the aforementioned drugs. The analysis results are presented and discussed, leading to conclusions about the potential of these new indices for pharmaceutical and chemical research on breast cancer treatments.
癌症是一种危及生命的疾病，由于细胞异常生长和增殖，它可以侵袭人体的任何部位，导致可能致命的肿瘤。乳腺癌是继肺癌之后世界上最致命的疾病之一。通过DNA中发生的激素和基因变化，乳腺癌会影响女性。定量结构-性质关系（QSPR）用于对16种治疗乳腺癌的药物进行全面研究。根据其化学结构，所研究的药物被建模为分子图。本研究的目的是检验新的全邻域拓扑指数在表征一系列乳腺癌药物的物理化学性质方面的效用。最初采用三次回归分析，随后进行多元线性回归建模，以增强全邻域拓扑指数与上述药物某些性质之间的相关性。给出并讨论了分析结果，得出了关于这些新指数在乳腺癌治疗药物和化学研究中的潜力的结论。
