Multiscale modeling unveils molecular mechanisms of deep eutectic solvent-anticancer drug interactions for rational...

Deep eutectic solvents (DESs) represent a burgeoning class of versatile media with significant potential to enhance the solubility, stability, and bioavailability of poorly water-soluble antineoplastic active pharmaceutical ingredients (AAPIs). However, the rational design of API-specific DES formulations remains impeded by an insufficient mechanistic understanding of the molecular-level interactions that govern API-DES compatibility. To address this critical gap, our study pioneers an integrated multi-scale computational strategy, synergizing free volume analysis, binding energy calculations, and hydrogen-bonding network quantification to unravel the supramolecular interplay between diverse DESs and a panel of clinically relevant AAPIs (including 5-FU, p-toluenesulfonamide (PTS), trigonelline, piperine, phloretin, nonivamide, curcumin, and erlotinib). We demonstrate that the free volume of DESs, formed from choline chloride or betaine with various hydrogen bond donors (HBDs), is dynamically altered upon AAPI incorporation, exhibiting either a "tightening" or "loosening" effect that correlates with dissolution enhancement or molecular stabilization. Interaction total energy (ΔE_t) profiles reveal strong dependencies on [HBA][HBD][AAPI] combinations, with glycerol-based DESs showing superior affinity for most AAPIs, while zwitterionic HBDs (e.g. glycine) form less stable complexes. The investigated [DES][AAPI] systems were classified into four ranks (I-IV) representing a descending gradient of predictive certainty and overall solubilization/stabilization potential. DESs such as [ChCl][PG], [ChCl][Glycerol], or [Betaine][Glycerol] appear more frequently in Classes I and IV than in Classes II and III. Given that Class I represents superior performance and Class IV represents high predictive uncertainty (rather than poor performance), the predominance of these DESs in Class I suggests a higher probability of favorable outcomes across diverse AAPIs.These insights provide a predictive framework for the rational design of DES systems tailored to specific APIs, enabling optimized solubility, stability, and controlled release in next-generation drug delivery applications.