The interactions of ligand-functionalized nanoparticles with the cell membrane affect cellular uptake, cytotoxicity, and related behaviors, but relating these interactions to ligand properties remains challenging. In this work, we perform coarse-grained molecular dynamics simulations to study how the adsorption of ligand-functionalized cationic gold nanoparticles (NPs) to a single-component lipid bilayer (as a model cell membrane) is influenced by ligand end group lipophilicity. A set of 2-nm diameter NPs, each coated with a monolayer of organic ligands that differ only in their end groups, was simulated to mimic NPs recently studied experimentally. Metadynamics calculations were performed to determine key features of the free energy landscape for adsorption as a function of the distance of the NP from the bilayer and the number of NP-lipid contacts. These simulations revealed that NP adsorption is thermodynamically favorable for all NPs due to the extraction of lipids from the bilayer and into the NP monolayer. To resolve ligand-dependent differences in adsorption behavior, string method calculations were performed to compute minimum free energy pathways for adsorption. These calculations revealed a surprising non-monotonic dependence of the free energy barrier for adsorption on ligand end group lipophilicity. Large free energy barriers are predicted for the least lipophilic end groups because favorable NP-lipid contacts are initiated only through the unfavorable protrusion of lipid tail groups out of the bilayer. The smallest free energy barriers are predicted for end groups of intermediate lipophilicity which promote NP-lipid contacts by intercalating within the bilayer. Unexpectedly, large free energy barriers are also predicted for the most lipophilic end groups which remain sequestered within the ligand monolayer rather than intercalating within the bilayer. These trends are broadly in agreement with past experimental measurements and reveal how subtle variations in ligand lipophilicity dictate adsorption mechanisms and associated kinetics by influencing the interplay of lipid-ligand interactions.
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Predicting the Physicochemical Properties and Biological Activities of Monolayer-Protected Gold Nanoparticles Using Simulation-Derived Descriptors
Gold nanoparticles are versatile materials for biological applications because their properties can be modulated by assembling ligands on their surface to form monolayers. However, the physicochemical properties and behaviors of monolayer-protected nanoparticles in biological environments are difficult to anticipate because they emerge from the interplay of ligand–ligand and ligand–solvent interactions that cannot be readily inferred from ligand chemical structure alone. In this work, we demonstrate that quantitative nanostructure–activity relationship (QNAR) models can employ descriptors calculated from molecular dynamics simulations to predict nanoparticle properties and cellular uptake. We performed atomistic molecular dynamics simulations of 154 monolayer-protected gold nanoparticles and calculated a small library of simulation-derived descriptors that capture nanoparticle structural and chemical properties in aqueous solution. We then parametrized QNAR models using interpretable regression algorithms to predict experimental measurements of nanoparticle octanol–water partition coefficients, zeta potentials, and cellular uptake obtained from a curated database. These models reveal that simulation-derived descriptors can accurately predict experimental trends and provide physical insight into what descriptors are most important for obtaining desired nanoparticle properties or behaviors in biological environments. Finally, we demonstrate model generalizability by predicting cell uptake trends for 12 nanoparticles not included in the original data set. These results demonstrate that QNAR models parametrized with simulation-derived descriptors are accurate, generalizable computational tools that could be used to guide the design of monolayer-protected gold nanoparticles for biological applications without laborious trial-and-error experimentation.
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- Award ID(s):
- 2044997
- NSF-PAR ID:
- 10318686
- Date Published:
- Journal Name:
- ACS nano
- ISSN:
- 1936-0851
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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ConspectusGold nanoparticles (AuNPs) exhibit unique size- and shape-dependent properties not obtainable at the macroscale. Gold nanorods (AuNRs), with their morphology-dependent optical properties, ability to convert light to heat, and high surface-to-volume ratios, are of great interest for biosensing, medicine, and catalysis. While the gold core provides many fascinating properties, this Account focuses on AuNP soft surface coatings, which govern the interactions of nanoparticles with the local environments. Postmodification of AuNP surface chemistry can greatly alter NP colloidal stability, nano-bio interactions, and functionality. Polyelectrolyte coatings provide controllable surface-coating thickness and charge, which impact the composition of the acquired corona in biological settings. Covalent modification, in which covalently bound ligands replace the original capping layer, is often performed with thiols and disulfides due to their ability to replace native coatings. N-heterocyclic carbenes and looped peptides expand the possible functionalities of the ligand layer.The characterization of surface ligands bound to AuNPs, in terms of ligand density and dynamics, remains a challenge. Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for understanding molecular structures and dynamics. Our recent NMR work on AuNPs demonstrated that NMR data were obtainable for ligands on NPs with diameters up to 25 nm for the first time. This was facilitated by the strong proton NMR signals of the trimethylammonium headgroup, which are present in a distinct regime from other ligand protons’ signals. Ligand density analyses showed that the smallest AuNPs (below 4 nm) had the largest ligand densities, yet spin–spin T2 measurements revealed that these smallest NPs also had the most mobile ligand headgroups. Molecular dynamics simulations were able to reconcile these seemingly contradictory results.While NMR spectroscopy provides ligand information averaged over many NPs, the ligand distribution on individual particles’ surfaces must also be probed to fully understand the surface coating. Taking advantage of improvements in electron energy loss spectroscopy (EELS) detectors employed with scanning transmission electron microscopy (STEM), a single-layer graphene substrate was used to calibrate the carbon K-edge EELS signal, allowing quantitative imaging of the carbon atom densities on AuNRs with sub-nanometer spatial resolution. In collaboration with others, we revealed that the mean value for surfactant-bilayer-coated AuNRs had 10–30% reduced ligand density at the ends of the rods compared to the sides, confirming prior indirect evidence for spatially distinct ligand densities.Recent work has found that surface ligands on nanoparticles can, somewhat surprisingly, enhance the selectivity and efficiency of the electrocatalytic reduction of CO2 by controlling access to the active site, tuning its electronic and chemical environment, or denying entry to impurities that poison the nanoparticle surface to facilitate reduction. Looking to the future, while NMR and EELS are powerful and complementary techniques for investigating surface coatings on AuNPs, the frontier of this field includes the development of methods to probe the surface ligands of individual NPs in a high-throughput manner, to monitor nano-bio interactions within complex matrices, and to study structure–property relationships of AuNPs in biological systems.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1021/acsnano.2c00301
