Predictive Qualitative Structure–Property Relationships in Cyclometalated NHC Platinum(II) Complexes: Decoding Biological Activities Using Topological Indices
Muhammad Danish, Tehreem Liaquat, Syed Rizwan Shafqat, Kanwal Shahzadi · ChemistrySelect · 2025
Abstract This study investigates the predictive capacity of degree‐based topological indices (TIs) in assessing molecular properties relevant to drug development, specifically targeting platinum(II) complexes with potential anticancer applications. Utilizing graph–theoretical techniques and edge partition methods, we compute various TIs and apply linear regression to establish quantitative structure–property relationship (QSPR) models. Among the indices analyzed, the geometric–arithmetic (GA) index shows the highest correlation with both formula weight ( r = 0.943) and ring double bond equivalent ( r = 0.942), indicating its effectiveness as a predictive descriptor. Other indices such as Zagreb indices and Randic index also demonstrate significant associations. These results underscore the utility of mathematical descriptors in forecasting biological and physicochemical properties, offering a computational framework for screening and optimizing drug‐like compounds.