A Nano-QSAR Model for the Cytotoxicity of Doxorubicin Prodrug Micelles in Multidrug-Resistant Cancer Cells

Abstract Nano-QSAR modeling provides a cost-effective approach for predicting the toxic effects of nanoparticles by reducing the experimental effort and improving the predictive accuracy. Cytotoxicity is the degree of toxicity of the particles toward the cells. In this study, a nano-QSAR model was developed for estimating the cytotoxicity (pIC50) of doxorubicin prodrug micelles on MCF-7/ADR cells by using degree-based topological indices and physicochemical properties such as particle size and polydispersity index. Doxorubicin is a leading anticancer drug, and using it as a nanomedicine, doxorubicin prodrug loaded micelles, improves the therapeutic efficiency, reduces the side effects, and lowers the multidrug-resistance of tumor cells to doxorubicin. Multiple linear regression analysis was used for the model development. The developed model exhibited a meaningful preliminary correlation, with a R2 value exceeding 0.6, between the topological and physicochemical descriptors and the cytotoxicity. As a proof of concept, this proposed model illustrates the potential significance of topological indices as structural descriptors in nano-QSAR modeling for predicting the cytotoxicity of the prodrug micellar system.