Sep 2026· International Journal of Biological Macromolecules· pp.
154313
· 0 citations· 53 references
Medicine
TL;DR
It is demonstrated that simple amino acid substitutions in L-PGDS can optimize drug binding, improve solubility, and suppress drug release, thus providing a basis for affinity-driven design of protein-based DDSs.
Abstract
Drug leakage from delivery vehicles is a major limitation of drug delivery systems (DDSs) for cancer chemotherapy because premature release of loaded drugs reduces therapeutic efficacy and increases off-target toxicity. We previously developed a DDS for the poorly water-soluble anti-cancer drug SN-38 using lipocalin-type prostaglandin D synthase (L-PGDS). To suppress drug leakage, in this study we generated an L-PGDS mutant (M94W-M145W) with enhanced binding affinity for SN-38 by introducing amino acid substitutions into the ligand-binding cavity. Docking simulations identified residues involved in SN-38 recognition, and selected residues were replaced with tryptophan to strengthen ligand binding. The dissociation constant of the M94W-M145W mutant for SN-38 was 2.7 ± 0.4 μM, approximately 4-fold lower than that of L-PGDS. In addition, 1 mM M94W-M145W enhanced the solubility of SN-38 by approximately 3.3-fold compared with 1 mM L-PGDS. In vitro release assays showed that the SN-38/M94W-M145W complex released SN-38 more slowly than the SN-38/L-PGDS complex. We also determined the crystal structure of the 10-O-(3-fluoropropyl)-substituted SN-38 derivative/M94W-M145W complex. The overall structure of M94W-M145W retained the typical lipocalin fold, indicating that these substitutions do not alter the global protein architecture. Two SN-38 derivative molecules were accommodated within the cavity through hydrogen bonding and hydrophobic interactions, including π-π stacking interactions introduced by the substituted tryptophan residues. These findings demonstrate that simple amino acid substitutions in L-PGDS can optimize drug binding, improve solubility, and suppress drug release, thus providing a basis for affinity-driven design of protein-based DDSs.
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