QSPR Modeling of Anticancer Drugs Using Uphill Topological Indices

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DOI: https://doi.org/10.28924/2291-8639-23-2025-327
Published: Dec 12, 2025
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Anwar Saleh, Sara Bazhear, Najat Muthana, QSPR Modeling of Anticancer Drugs Using Uphill Topological Indices, Int. J. Anal. Appl., 23 (2025), 327.

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Anwar Saleh, Sara Bazhear, Najat Muthana

Abstract

Over the past thirty years, cancer has affected more than ten million people worldwide annually. While diverse treatments exist (chemotherapy, surgery, radiation, immunotherapy, stem cell transplants), anti-cancer drugs remain essential. This research introduces five novel uphill topological indices derived from molecular graphs to establish Quantitative Structure-Property Relationships (QSPR) for ten essential anticancer drugs: carmustine, convolutamine F, raloxifene, tambjamine K, pierocellin B, caulibugulone E, convolutamide A, daunorubicin, deguelin, and podophyllotoxin. Power regression analysis correlated these indices with six experimental properties: boiling point (BP), melting point (MP), enthalpy (E), molar refraction (MR), molar volume (MV), and surface tension (ST). Results demonstrate statistically significant correlations (p < 0.05), with the uphill sigma index (UPSIG) emerging as the optimal predictor for BP (R2 = 0.929), MP (R 2 = 0.907), and E (R2 = 0.828), while the uphill Albertson index (UPAL) excelled for MV (R2 = 0.918). Predictive validity was confirmed via multilinear regression (R2 > 0.934 for BP/E/MV/MR), establishing these indices as powerful tools for rational anticancer drug design.

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