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• W2730326934 abstract "An in-depth appreciation of how to manipulate the molecular-level recognition between peptides and aqueous materials interfaces, including nanoparticles, will advance technologies based on self-organized metamaterials for photonics and plasmonics, biosensing, catalysis, energy generation and harvesting, and nanomedicine. Exploitation of the materials-selective binding of biomolecules is pivotal to success in these areas and may be particularly key to producing new hierarchically structured biobased materials. These applications could be accomplished by realizing preferential adsorption of a given biomolecule onto one materials composition over another, one surface facet over another, or one crystalline polymorph over another. Deeper knowledge of the aqueous abiotic-biotic interface, to establish clear structure-property relationships in these systems, is needed to meet this goal. In particular, a thorough structural characterization of the surface-adsorbed peptides is essential for establishing these relationships but can often be challenging to accomplish via experimental approaches alone. In addition to myriad existing challenges associated with determining the detailed molecular structure of any molecule adsorbed at an aqueous interface, experimental characterization of materials-binding peptides brings new, complex challenges because many materials-binding peptides are thought to be intrinsically disordered. This means that these peptides are not amenable to experimental techniques that rely on the presence of well-defined secondary structure in the peptide when in the adsorbed state. To address this challenge, and in partnership with experiment, molecular simulations at the atomistic level can bring complementary and critical insights into the origins of this abiotic/biotic recognition and suggest routes for manipulating this phenomenon to realize new types of hybrid materials. For the reasons outlined above, molecular simulation approaches also face challenges in their successful application to model the biotic-abiotic interface, related to several factors. For instance, simulations require a plausible description of the chemistry and the physics of the interface, which comprises two very different states of matter, in the presence of liquid water. Also, it is essential that the conformational ensemble be comprehensively characterized under these conditions; this is especially challenging because intrinsically disordered peptides do not typically admit one single structure or set of structures. Moreover, a plausible structural model of the substrate is required, which may require a high level of detail, even for single-element materials such as Au surfaces or graphene. Developing and applying strategies to make credible predictions of the conformational ensemble of adsorbed peptides and using these to construct structure-property relationships of these interfaces have been the goals of our efforts. We have made substantial progress in developing interatomic potentials for these interfaces and adapting advanced conformational sampling approaches for these purposes. This Account summarizes our progress in the development and deployment of interfacial force fields and molecular simulation techniques for the purpose of elucidating these insights at biomolecule-materials interfaces, using examples from our laboratories ranging from noble-metal interfaces to graphitic substrates (including carbon nanotubes and graphene) and oxide materials (such as titania). In addition to the well-established application areas of plasmonic materials, biosensing, and the production of medical implant materials, we outline new directions for this field that have the potential to bring new advances in areas such as energy materials and regenerative medicine." @default.
• W2730326934 created "2017-07-14" @default.
• W2730326934 creator A5053769720 @default.
• W2730326934 date "2017-06-30" @default.
• W2730326934 modified "2023-10-12" @default.
• W2730326934 title "Pathways to Structure–Property Relationships of Peptide–Materials Interfaces: Challenges in Predicting Molecular Structures" @default.
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• W2730326934 doi "https://doi.org/10.1021/acs.accounts.7b00065" @default.
• W2730326934 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28665581" @default.
• W2730326934 hasPublicationYear "2017" @default.
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