Enhancing Drug Solubility and Bioavailability Through Cyclodextrin Inclusion Complexes: An Integrative Molecular Meta-Modeling Approach

Cyclodextrin inclusion complexes are increasingly used to increase drug solubility and bioavailability. This study integrates molecular modeling and meta-analysis to evaluate the pharmacokinetic performance and molecular stability of various cyclodextrin-drug systems. A meta-analysis of 11 studies was performed to assess effect sizes for maximum concentration ([Formula: see text] and area under curve (AUC), revealing substantial heterogeneity and overall improvement in drug exposure. Molecular docking, Molecular Dynamics (MD) simulations and free energy calculations were used to investigate the stability of the selected host-guest systems. Compared with the atorvastatin (ATV)/HP-[Formula: see text]-cyclodextrin system, the Compound K/[Formula: see text]-cyclodextrin complex exhibited the highest binding affinity with greater pharmacokinetic effect sizes. SBE-[Formula: see text]-CD was identified as the most effective cyclodextrin for enhancing bioavailability, whereas [Formula: see text]-CD was the least effective. To further explore these findings, four ligands, ATV, [Formula: see text]-caryophyllene, koumine and Compound K, were selected on the basis of their solubility (log[Formula: see text] values. A stronger affinity for SBE-[Formula: see text]-CD over [Formula: see text]-CD was observed for all tested compounds. This trend was confirmed through replicate MD simulations of Compound K and koumine, which revealed greater stability with SBE-[Formula: see text]-CD. These effects are attributed to the extended hydrophobic cavity of SBE-[Formula: see text]-CD and reduced electrostatic repulsion, emphasizing the role of molecular shape and hydrophobicity in complex stability. This integrated analysis highlights the potential of SBE-[Formula: see text]-CD to improve drug bioavailability through stable inclusion complex formation. These findings provide a mechanistic basis for cyclodextrin selection in formulation development. However, further clinical studies are needed to validate these computational predictions.