Abstract Breast cancer is a major worldwide health concern, highlighting the necessity of efficient drugs evaluation methods. Degree-based topological indices are essential tools in chem-informatics for examining the physicochemical properties and chemical structure of drug compounds. This work used Revan and Hyper-Revan topological indices obtained from the molecular graphs of 22 breast cancer drugs to evaluate them using Quantitative Structure-Property Relationship (QSPR) modeling. Six physicochemical properties: molecular weight, boiling point, flash point, complexity, exact mass and topological polar surface area were correlated with these indices using Multiple Linear Regression (MLR) models. Using several important topological indices, complexity has demonstrated significant findings with a strong correlation and RMSE values (R=0.990 and RMSE= 62.087) for the features of the drugs under consideration. TOP-SIS and VIKOR, two Multi-Criteria Decision Making (MCDM) techniques, were used to rank the drugs. Abraxane, Everolimus, and Docetaxel were the top competitors according to the TOPSIS ranking. Based on compromise solutions, VIKOR study consistently ranked Abraxane, Everolimus, and Docetaxel among the best.The potential of integrating regression modeling, topological indices, and decision-making tools for effective medication screening and prioritizing is highlighted by this integrated method.
Saranya et al. (Tue,) studied this question.