Molecular dynamics-driven and biophysically validated excipient selection for BDNF cubosome formulation.
📄 Abstract
The formulation of therapeutic proteins such as Brain-Derived Neurotrophic Factor (BDNF) remains difficult because of their inherent instability and limited bioavailability, especially in central nervous system delivery. In this study, we propose an integrated computational-experimental workflow for the rational selection of excipients to optimize BDNF-loaded cubosomal formulations. Structure-based computational analyses-including SiteMap evaluation, molecular docking, and molecular dynamics (MD) simulations-were used to characterize potential binding sites, and assess the molecular compatibility of lipids, stabilizers, and hydrotropes with BDNF. Among the screened excipients, phytantriol showed the most favorable polar and hydrophobic interactions with the protein, while Tween 80 and PEG 200 were identified as the preferred stabilizer and hydrotrope, respectively. The MD trajectories revealed that protein-excipient contacts were transient yet overall stabilizing, helping the protein maintain its conformational integrity under simulated conditions. Experimental confirmation using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy supported these observations by demonstrating that BDNF's secondary structure was preserved in the presence of the selected excipients. This study provides molecular-level insight into excipient-protein interactions and demonstrates a predictive strategy for guiding the design of stable neurotrophin formulations.