Authors
Masatoshi Nakatsuji, Haruka Muroya, Rina Okubo, Yoshiaki Teraoka, Mihoro Yamada, Keisuke Nishide, Haruna Yoshida, Kousuke Furuta, Reina Koyama, Tatsuya Kida, Hisashi Doi, Shigenori Nishimura, Takashi Inui
Published in
International journal of biological macromolecules. Pages 154313. Sep 01, 2026. Epub Sep 01, 2026.
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.
PMID:
42680028
Bibliographic data and abstract were imported from PubMed on 02 Sep 2026.
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