Evidence map›Paper›PMID 42749953›Full record

ArticleJournal of molecular modeling2026

Experimental and molecular dynamics investigation of ZnO nanoparticle size effects on sunscreen performance and skin-lipid interactions.

Nigar Kantarci-Carsibasi, Melis Ersoy, Rana Tosun, Shirin Tarbiat

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Article in Journal of molecular modeling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Nigar Kantarci-CarsibasiDepartment of Chemical Engineering, Uskudar University, 34662, Istanbul, Turkey. nigar.carsibasi@uskudar.edu.tr.ORCID https://orcid.org/0000-0003-1013-6668
Melis ErsoyDepartment of Chemical Engineering, Uskudar University, 34662, Istanbul, Turkey.
Rana TosunDepartment of Chemical Engineering, Uskudar University, 34662, Istanbul, Turkey.
Shirin TarbiatDepartment of Molecular Biology and Genetics, Uskudar University, 34662, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextZinc oxide (ZnO) nanoparticles are widely used as inorganic UV filters in sunscreen formulations; however, particle size can influence photoprotective efficacy, formulation stability, cosmetic properties, and interactions with the skin barrier. This study experimentally investigated the effect of ZnO nanoparticle size on sunscreen performance and complemented these findings with molecular dynamics (MD) simulations to characterize ZnO-stratum corneum (SC) interactions at the molecular level. SPF increased from 1.24 in the ZnO-free control to 2.61 and 3.23 in formulations containing 18 nm and 30-50 nm ZnO nanoparticles, respectively. Despite its higher SPF, the 30-50 nm formulation exhibited phase separation, increased pH, and pronounced whitening after skin application, whereas the 18 nm formulation showed a more balanced physical stability, skin-compatible pH, and cosmetic performance. MD simulations further demonstrated that both crystal-derived ZnO and a 1 nm ZnO nanoparticle remained preferentially localized at the SC lipid interface without evidence of deeper penetration. Persistently negative ZnO-SC interaction energies, together with density-depth and spatial projection analyses, supported sustained association and interfacial retention of ZnO within the SC lipid environment, with no deeper penetration observed within the 100 ns simulation timescale. Overall, the 18 nm ZnO formulation provided the most favorable balance between photoprotection, formulation stability, skin compatibility, and cosmetic acceptability, while the computational findings provided molecular-level support for the interfacial retention of ZnO within the SC lipid matrix.

methodsThree sunscreen formulations were prepared: a ZnO-free control and formulations containing 5% (w/w) ZnO nanoparticles with particle sizes of 18 nm or 30-50 nm. The formulations were characterized by in vitro sun protection factor (SPF), pH, physical stability, and skin-application assessments. To investigate ZnO-skin interactions at the molecular level, 100 ns all-atom MD simulations were performed using a representative SC lipid model composed of ceramides, cholesterol, and free fatty acids. Two complementary ZnO representations, a crystal-derived ZnO model and a computationally tractable 1 nm ZnO nanoparticle model, were evaluated. ZnO localization and retention within the lipid matrix were characterized using interaction-energy profiles, trajectory-density analysis, density-depth distributions, and spatial projection analyses.

Indexed as

LipidsMolecular Dynamics SimulationNanoparticlesSkinSunscreening AgentsZinc OxideHumansParticle SizeLipidsSunscreening AgentsZinc OxideMolecular dynamics simulationNanoparticle-skin interactionsSkin adsorptionStratum corneum lipid modelZinc oxide nanoparticles

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.