AI-assisted models to predict chemotherapy drugs modified with C₆₀ fullerene derivatives.

ABSTRACT: Employing quantitative structure-activity relationship (QSAR)/ quantitative structure-property relationship (QSPR) models, this study explores the application of fullerene derivatives as nanocarriers for breast cancer chemotherapy drugs. Isolated drugs and two drug-fullerene complexes (i.e., drug-pristine C₆₀ fullerene and drug-carboxyfullerene C₆₀-COOH) were investigated with the protein CXCR7 as the molecular docking target. The research involved over 30 drugs and employed Pearson's hard-soft acid-base theory and common QSAR/QSPR descriptors to build predictive models for the docking scores. Energetic descriptors were computed using quantum chemistry at the density functional-based tight binding DFTB3 level. The results indicate that drug-fullerene complexes interac

SUBMITTER: Robles-Hernandez JS 

PROVIDER: S-EPMC11420546 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature