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• W2746750801 abstract "Peptide-functionalized (PF) hydrogels are being widely investigated by the tissue engineering and regenerative medicine communities for a broad range of applications because of their unique potential to mimic the natural extracellular matrix and promote tissue regeneration. In order for these complex material systems to perform their intended bioactive function (e.g., cell signaling), the peptides that are tethered to the hydrogel matrix must be accessible at the hydrogel surface for cell–receptor binding. The factors influencing the surface accessibility of the tethered peptide mainly include the length of the tethers, the loading (i.e., concentration) of the peptide, and the association between the tethered peptide and the hydrogel matrix. In the present work, the authors developed coarse-grained molecular models based on the all-atom polymer consistent force field for a type of poly(ethylene glycol)-based PF hydrogel and conducted molecular simulations to investigate the distribution of the peptide within the hydrogel and its surface accessibility as a function of tether length and peptide concentration. The calculated results of the effects of these design parameters on the surface accessibility of the peptide agree very well with corresponding experimental measurements in which peptide accessibility was quantified by the number of cells attached to the hydrogel surface per unit area. The developed modeling methods are able to provide unique insights into the molecular behavior of PF hydrogels and the distribution of the tethered peptides, which can serve as a guide for hydrogel design optimization." @default.
• W2746750801 created "2017-08-31" @default.
• W2746750801 creator A5019943617 @default.
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• W2746750801 date "2017-08-01" @default.
• W2746750801 modified "2023-10-15" @default.
• W2746750801 title "Molecular modeling to predict peptide accessibility for peptide-functionalized hydrogels" @default.
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• W2746750801 doi "https://doi.org/10.1116/1.4992101" @default.
• W2746750801 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5562506" @default.
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• W2746750801 hasPublicationYear "2017" @default.
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