Mathematical Modeling of Anticancer Drugs Using Distance-based Topological Indices
Abstract
We examine the suitability of distance-based topological indices in modeling and forecasting the physicochemical properties of a selection of key drugs like Trastuzumab, Tamoxifen, paclitaxel, Ibritumomab, Gemcitabine, Fluorouracil (5-FU), and Doxorubicin. Four different indices—Mostar, Szeged, Trinajstić, and Padmakar–Ivan (PI)—were derived from molecular graphs for each drug. Quadratic models showed appreciable correlations between these indices and principal physicochemical properties like molecular weight and melting points. Topological indices are seen to forecast physicochemical properties effectively, making them useful aids in drug design, optimization, and discovery. The mathematical models shed light on structural complications affecting drug efficacy and pharmacokinetics, proving graph-theoretical methods effective in predicting.
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