Quantitative correlation of spectroscopic signatures with ligand-protein interactions in anti-cancer drug Afinitor:...

A detailed molecular-level understanding of anticancer drugs is essential for improving therapeutic efficacy and guiding rational drug design. Everolimus (Afinitor), a clinically important inhibitor of the mammalian target of rapamycin (mTOR) pathway, is widely used in cancer therapy; however, a quantitatively grounded relationship between its spectroscopic characteristics and ligand-protein interactions remains insufficiently explored. In this study, an integrated experimental-computational approach was employed, combining FT-IR spectroscopy, UV-Vis spectroscopy, and molecular docking simulations. Spectroscopic analyses were used to characterise functional groups and electronic structure, while docking simulations were performed to investigate interactions with FK506 binding protein (FKBP12) and the FKBP-rapamycin binding (FRB) domain. FT-IR analysis revealed a high density of oxygen-containing functional groups, including hydroxyl and carbonyl moieties, with vibrational frequencies indicative of a strongly polarised electronic environment. Molecular docking demonstrated favourable binding affinities with FKBP12 (- 9.7 and - 9.6 kcal·mol⁻¹) and the FRB domain (- 8.5 and - 6.6 kcal·mol⁻¹). Detailed interaction analysis showed that these functional groups correspond to specific interacting atoms (e.g., O66, O67, O63, and O36), forming quantifiable hydrogen bonds (1.7-2.9 Å) and electrostatic interactions (~ 4.37 Å) with key residues such as TYR82, THR85, and GLU54. The UV-Vis absorption maximum at 278 nm corresponds to a HOMO-LUMO energy gap of 4.46 eV, indicating moderate electronic polarizability that supports charge redistribution during binding. The study establishes a quantitative and mechanistically grounded structure-spectra-interaction relationship, demonstrating that spectroscopic observables encode the local electronic environment governing ligand-protein interaction propensity. Binding affinity is shown to arise from a cooperative network of multiple non-covalent interactions enabled by the spatial distribution of functional groups. This integrated framework provides predictive insight into drug-protein interactions and offers a robust foundation for the rational design and optimisation of mTOR-targeting therapeutics.