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Chew AK, Pedersen JA, Van Lehn RC. Predicting the Physicochemical Properties and Biological Activities of Monolayer-Protected Gold Nanoparticles Using Simulation-Derived Descriptors. ACS Nano 2022; 16:6282-6292. [PMID: 35289596 DOI: 10.1021/acsnano.2c00301] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
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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Affiliation(s)
- Alex K Chew
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Joel A Pedersen
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Reid C Van Lehn
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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Liu Y, Yan B, Winkler DA, Fu J, Zhang A. Competitive Inhibition Mechanism of Acetylcholinesterase without Catalytic Active Site Interaction: Study on Functionalized C 60 Nanoparticles via in Vitro and in Silico Assays. ACS Appl Mater Interfaces 2017; 9:18626-18638. [PMID: 28492309 DOI: 10.1021/acsami.7b05459] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Acetylcholinesterase (AChE) activity regulation by chemical agents or, potentially, nanomaterials is important for both toxicology and pharmacology. Competitive inhibition via direct catalytic active sites (CAS) binding or noncompetitive inhibition through interference with substrate and product entering and exiting has been recognized previously as an AChE-inhibition mechanism for bespoke nanomaterials. The competitive inhibition by peripheral anionic site (PAS) interaction without CAS binding remains unexplored. Here, we proposed and verified the occurrence of a presumed competitive inhibition of AChE without CAS binding for hydrophobically functionalized C60 nanoparticles (NPs) by employing both experimental and computational methods. The kinetic inhibition analysis distinguished six competitive inhibitors, probably targeting the PAS, from the pristine and hydrophilically modified C60 NPs. A simple quantitative nanostructure-activity relationship (QNAR) model relating the pocket accessible length of substituent to inhibition capacity was then established to reveal how the geometry of the surface group decides the NP difference in AChE inhibition. Molecular docking identified the PAS as the potential binding site interacting with the NPs via a T-shaped plug-in mode. Specifically, the fullerene core covered the enzyme gorge as a lid through π-π stacking with Tyr72 and Trp286 in the PAS, while the hydrophobic ligands on the fullerene surface inserted into the AChE active site to provide further stability for the complexes. The modeling predicted that inhibition would be severely compromised by Tyr72 and Trp286 deletions, and the subsequent site-directed mutagenesis experiments proved this prediction. Our results demonstrate AChE competitive inhibition of NPs without CAS participation to gain further understanding of both the neurotoxicity and the curative effect of NPs.
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Affiliation(s)
- Yanyan Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences , Beijing 100085, China
- College of Resources and Environment, University of Chinese Academy of Sciences , Beijing 100190, China
| | - Bing Yan
- School of Chemistry and Chemical Engineering, Shandong University , Jinan 250100, China
- School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University , Guangzhou 510632, China
| | - David A Winkler
- CSIRO Manufacturing , Clayton 3168, Australia
- Monash Institute of Pharmaceutical Sciences , Parkville 3052, Australia
- Latrobe Institute for Molecular Science , Bundoora, 3046, Australia
- School of Chemical and Physical Science, Flinders University , Bedford Park 5042, Australia
| | - Jianjie Fu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences , Beijing 100085, China
- College of Resources and Environment, University of Chinese Academy of Sciences , Beijing 100190, China
| | - Aiqian Zhang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences , Beijing 100085, China
- College of Resources and Environment, University of Chinese Academy of Sciences , Beijing 100190, China
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