2. Academic Validation
  3. Structure-Selective Polydopamine Coating on Drug Nanoparticles

Structure-Selective Polydopamine Coating on Drug Nanoparticles

  • ACS Appl Mater Interfaces. 2026 Feb 4;18(4):6452-6463. doi: 10.1021/acsami.5c19920.
Danna Niezni 1,  Dana Meron Azagury 1,  Maytal Avrashami 1,  Orr Bar-Natan 1 2,  Yosi Shamay 1
Affiliations

Affiliations

  • 1 Department of Biomedical Engineering Technion - Israel Institute of Technology, Haifa, 32000, Israel.
  • 2 The Norman Seiden Multidisciplinary Program for Nanoscience and Nanotechnology, Technion - Israel Institute of Technology, Haifa, 32000, Israel.
PMID: 41582522 DOI: 10.1021/acsami.5c19920
Abstract

Polydopamine (PDA) is widely regarded as a universal coating material with substrate-independent adhesion. Here we report the first demonstration of selective PDA coating on small molecule drugs, revealing unexpected structure-dependent behavior that challenges this paradigm. Systematic screening of 30 chemotherapeutic agents in IR783-stabilized nanoparticles (>90% drug loading) showed dramatic coating variations governed by molecular structure rather than conventional hydrophobic or π-π interactions. Using Dragon molecular descriptors and principal component analysis, we developed a predictive decision tree model based on nitrogen content and bonding topology that correctly classified 80% of validation compounds. Coating selectivity correlates primarily with nitrogen percentage and N-C-N motifs, fundamentally expanding the understanding of PDA surface chemistry beyond nonselective adhesion mechanisms. Representative drugs (trametinib, dasatinib) demonstrated that PDA coating significantly improves colloidal stability and reduces aggregation without compromising drug loading or release kinetics. In vivo evaluation in HCT116 xenografts confirmed superior efficacy over free drug with improved formulation stability. These findings establish PDA coating selectivity as a previously unrecognized material phenomenon and provide computational tools for rational nanoparticle surface design.

Keywords

decision tree; drug delivery; nanomedicine; nanoparticles; nanoprecipitation; polydopamine.

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